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Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover. Evolutionary programming differs from evolution strategy ES( μ + λ {\displaystyle \mu +\lambda } ) in one detail. All individuals are selected for the new population, while in ES( μ + λ {\displaystyle \mu +\lambda } ), every individual has the same probability to be selected. It is one of the four major evolutionary algorithm paradigms. == History == It was first used by Lawrence J. Fogel in the US in 1960 in order to use simulated evolution as a learning process aiming to generate artificial intelligence. It was used to evolve finite-state machines as predictors. == See also == Artificial intelligence Genetic algorithm Genetic operator == References == == External links == The Hitch-Hiker's Guide to Evolutionary Computation: What's Evolutionary Programming (EP)? Evolutionary Programming by Jason Brownlee (PhD) Archived 2013-01-18 at the Wayback Machine
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Susan Finsen is an American philosopher, currently professor emeritus of philosophy and former chair of the department at California State University, San Bernardino. She specializes in moral philosophy, with a particular interest in animal rights, as well as philosophy of science and philosophy of biology. She is the co-author, with her husband Lawrence Finsen, of The Animal Rights Movement in America: From Compassion to Respect (1994), and is the director of Californians for the Ethical Treatment of Animals. Finsen received her PhD in philosophy from Indiana University Bloomington in 1982. Susan Finsen was formerly known as Susan K. Mills. == Notes ==
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Virophysics is a branch of biophysics in which the theoretical concepts and experimental techniques of physics are applied to study the mechanics and dynamics driving the interactions between virions and cells. == Overview == Research in virophysics typically focuses on resolving the physical structure and structural properties of viruses, the dynamics of their assembly and disassembly, their population kinetics over the course of an infection, and the emergence and evolution of various strains. The common aim of these efforts is to establish a set of models (expressions or laws) that quantitatively describe the details of all processes involved in viral infections with reliable predictive power. Having such a quantitative understanding of viruses would not only rationalize the development of strategies to prevent, guide, or control the course of viral infections, but could also be used to exploit virus processes and put virus to work in areas such as nanosciences, materials, and biotechnologies. Traditionally, in vivo and in vitro experimentation has been the only way to study viral infections. This approach for deriving knowledge based solely on experimental observations relies on common-sense assumptions (e.g., a higher virus count means a fitter virus). These assumptions often go untested due to difficulties controlling individual components of these complex systems without affecting others. The use of mathematical models and computer simulations to describe such systems, however, makes it possible to deconstruct an experimental system into individual components and determine how the pieces combine to create the infection we observe. Virophysics has large overlaps with other fields. For example, the modelling of infectious disease dynamics is a popular research topic in mathematics, notably in applied mathematics or mathematical biology. While most modelling efforts in mathematics have focused on elucidating the dynamics of spread of infectious diseases at an epidemiological scale (person-to-person), there is also important
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work being done at the cellular scale (cell-to-cell). Virophysics focuses almost exclusively on the single-cell or multi-cellular scale, utilizing physical models to resolve the temporal and spatial dynamics of viral infection spread within a cell culture (in vitro), an organ (ex vivo or in vivo) or an entire host (in vivo). == References == == External links == === Related meetings/conferences === Virophysics 2015 2nd Workshop on Virus Dynamics
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Under the Sea Wind: A Naturalist's Picture of Ocean Life (1941) is the first book written by the American marine biologist Rachel Carson. It was published by Simon & Schuster in 1941 and received very good reviews, but sold poorly. After the great success of a sequel The Sea Around Us (Oxford, 1951), it was reissued by Oxford University Press; that edition was an alternate Book-of-the-Month Club selection and became another bestseller, and has never gone out of print. It is recognized as one of the "definitive works of American nature writing," and is in print as one of the Penguin Nature Classics. Under the sea-wind was reportedly Rachel Carson's personal favourite book, although first edition copies by Simon & Schuster remain scarce. == Background == Under the Sea Wind was based on the article Undersea by Carson, published in The Atlantic Monthly in 1937. This article began as an eleven-page introduction to a government fisheries brochure, and grew into Carson's first book. Prior to publishing Undersea, she wrote marine themed radio scripts which influenced her later work. The article elaborates on ecology and the unwavering will to survive that embodies marine organisms. After the article was published, Dutch-born children's author Hendrik Van Loon became interested in Carson's work. He supported and encouraged her to continue this type of depiction of nature in her writing, as well as advising her about publishing. Carson furthered the perspectives from her article and expanded them in Under the Sea Wind, which was described as her personal favorite. The initial failure of Under the Sea Wind may have been due to the bombing of Pearl Harbor and America entering World War II the same year it was published. The book became popular after the publication of the second book in the Sea Trilogy, The
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Sea Around Us, and it was this second text that established her as a natural history author. == Description == Under the Sea Wind describes the behavior of organisms that live both on and in the sea on the Atlantic coast. Under the Sea Wind consists of three parts, each following a different organism that interacts with the sea, and viewing it from a personified organism's perspective. The first section, Edge of the Sea, follows a female sanderling Carson names Silverbar. The second section, The Gull's Way, follows a mackerel named Scomber, and the third section, River and Sea follows Anguilla, an eel. The narrative follows these creature's migration habits over the span of a year. Viewing ocean life from a broader ecological perspective was crucial to Carson, rather than just isolating parts of the sea. The term "sea wind" was Carson's way of referring to the entirety of the shore, sea, and sky. Carson had a poetic way of writing about nature, while still maintaining the scientific accuracy of her observations. Her work draws connections between nature and home, the borders of interrelated communities, and the growing separation between man and nature. Carson took inspiration from natural history authors such as Henry Williamson and Henry Beston, and uses her scientific expertise to ground Under the Sea Wind in scientifically accurate detail on each animal's appearance, diet and behavior. Carson's stated goal of using poetic prose and personifying sea life was "to make the sea and its life as vivid a reality for those who may read the book as it has become for me during the past decade." This writing style brought scientific observations to a larger audience, and as stated by fellow marine environmentalist author Joel Hedgpeth in a review of the book, allowed for "turning the subject
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"page_id": 13240212,
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of the sea to a respectable reading matter for the clientele of the New Yorker and Reader's Digest sets, and inspiring a fashion in literature about the sea, its ways, and creatures." The style of Carson's writing makes the book suitable for children as well as adults, and the appeal is enhanced with illustrations, originally by Howard Frech. These were eventually replaced in 1991 with illustrations by Robert W. Hines. Though Under the Sea Wind is a story of struggle and chance survival, the style that Carson presents is in stark contrast to her later work, Silent Spring, which is much more dire and analytical. == References == == External links == Under the Sea-wind at Faded Page (Canada)
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"title": "Under the Sea Wind"
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Virtual screening (VS) is a computational technique used in drug discovery to search libraries of small molecules in order to identify those structures which are most likely to bind to a drug target, typically a protein receptor or enzyme. Virtual screening has been defined as "automatically evaluating very large libraries of compounds" using computer programs. As this definition suggests, VS has largely been a numbers game focusing on how the enormous chemical space of over 1060 conceivable compounds can be filtered to a manageable number that can be synthesized, purchased, and tested. Although searching the entire chemical universe may be a theoretically interesting problem, more practical VS scenarios focus on designing and optimizing targeted combinatorial libraries and enriching libraries of available compounds from in-house compound repositories or vendor offerings. As the accuracy of the method has increased, virtual screening has become an integral part of the drug discovery process. Virtual Screening can be used to select in house database compounds for screening, choose compounds that can be purchased externally, and to choose which compound should be synthesized next. == Methods == There are two broad categories of screening techniques: ligand-based and structure-based. The remainder of this page will reflect Figure 1, the flow chart of virtual screening. === Ligand-based methods === Given a set of structurally diverse ligands that binds to a receptor, a model of the receptor can be built by exploiting the collective information contained in such set of ligands. Different computational techniques explore the structural, electronic, molecular shape, and physicochemical similarities of different ligands that could imply their mode of action against a specific molecular receptor or cell lines. A candidate ligand can then be compared to the pharmacophore model to determine whether it is compatible with it and therefore likely to bind. Different 2D chemical similarity
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analysis methods have been used to scan a databases to find active ligands. Another popular approach used in ligand-based virtual screening consist on searching molecules with shape similar to that of known actives, as such molecules will fit the target's binding site and hence will be likely to bind the target. There are a number of prospective applications of this class of techniques in the literature. Pharmacophoric extensions of these 3D methods are also freely-available as webservers. Also shape based virtual screening has gained significant popularity. === Structure-based methods === Structure-based virtual screening approach includes different computational techniques that consider the structure of the receptor that is the molecular target of the investigated active ligands. Some of these techniques include molecular docking, structure-based pharmacophore prediction, and molecular dynamics simulations. Molecular docking is the most used structure-based technique, and it applies a scoring function to estimate the fitness of each ligand against the binding site of the macromolecular receptor, helping to choose the ligands with the most high affinity. Currently, there are some webservers oriented to prospective virtual screening. === Hybrid methods === Hybrid methods that rely on structural and ligand similarity were also developed to overcome the limitations of traditional VLS approaches. This methodologies utilizes evolution‐based ligand‐binding information to predict small-molecule binders and can employ both global structural similarity and pocket similarity. A global structural similarity based approach employs both an experimental structure or a predicted protein model to find structural similarity with proteins in the PDB holo‐template library. Upon detecting significant structural similarity, 2D fingerprint based Tanimoto coefficient metric is applied to screen for small-molecules that are similar to ligands extracted from selected holo PDB templates. The predictions from this method have been experimentally assessed and shows good enrichment in identifying active small molecules. The above specified method depends
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on global structural similarity and is not capable of a priori selecting a particular ligand‐binding site in the protein of interest. Further, since the methods rely on 2D similarity assessment for ligands, they are not capable of recognizing stereochemical similarity of small-molecules that are substantially different but demonstrate geometric shape similarity. To address these concerns, a new pocket centric approach, PoLi, capable of targeting specific binding pockets in holo‐protein templates, was developed and experimentally assessed. == Computing infrastructure == The computation of pair-wise interactions between atoms, which is a prerequisite for the operation of many virtual screening programs, scales by O ( N 2 ) {\displaystyle O(N^{2})} , N is the number of atoms in the system. Due to the quadratic scaling, the computational costs increase quickly. === Ligand-based approach === Ligand-based methods typically require a fraction of a second for a single structure comparison operation. Sometimes a single CPU is enough to perform a large screening within hours. However, several comparisons can be made in parallel in order to expedite the processing of a large database of compounds. === Structure-based approach === The size of the task requires a parallel computing infrastructure, such as a cluster of Linux systems, running a batch queue processor to handle the work, such as Sun Grid Engine or Torque PBS. A means of handling the input from large compound libraries is needed. This requires a form of compound database that can be queried by the parallel cluster, delivering compounds in parallel to the various compute nodes. Commercial database engines may be too ponderous, and a high speed indexing engine, such as Berkeley DB, may be a better choice. Furthermore, it may not be efficient to run one comparison per job, because the ramp up time of the cluster nodes could easily outstrip the
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amount of useful work. To work around this, it is necessary to process batches of compounds in each cluster job, aggregating the results into some kind of log file. A secondary process, to mine the log files and extract high scoring candidates, can then be run after the whole experiment has been run. == Accuracy == The aim of virtual screening is to identify molecules of novel chemical structure that bind to the macromolecular target of interest. Thus, success of a virtual screen is defined in terms of finding interesting new scaffolds rather than the total number of hits. Interpretations of virtual screening accuracy should, therefore, be considered with caution. Low hit rates of interesting scaffolds are clearly preferable over high hit rates of already known scaffolds. Most tests of virtual screening studies in the literature are retrospective. In these studies, the performance of a VS technique is measured by its ability to retrieve a small set of previously known molecules with affinity to the target of interest (active molecules or just actives) from a library containing a much higher proportion of assumed inactives or decoys. There are several distinct ways to select decoys by matching the properties of the corresponding active molecule and more recently decoys are also selected in a property-unmatched manner. The actual impact of decoy selection, either for training or testing purposes, has also been discussed. By contrast, in prospective applications of virtual screening, the resulting hits are subjected to experimental confirmation (e.g., IC50 measurements). There is consensus that retrospective benchmarks are not good predictors of prospective performance and consequently only prospective studies constitute conclusive proof of the suitability of a technique for a particular target. == Application to drug discovery == Virtual screening is a very useful application when it comes to identifying hit molecules
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as a beginning for medicinal chemistry. As the virtual screening approach begins to become a more vital and substantial technique within the medicinal chemistry industry the approach has had an expeditious increase. == Ligand-based methods == While not knowing the structure trying to predict how the ligands will bind to the receptor. With the use of pharmacophore features each ligand identified donor, and acceptors. Equating features are overlaid, however given it is unlikely there is a single correct solution. === Pharmacophore models === This technique is used when merging the results of searches by using unlike reference compounds, same descriptors and coefficient, but different active compounds. This technique is beneficial because it is more efficient than just using a single reference structure along with the most accurate performance when it comes to diverse actives. Pharmacophore is an ensemble of steric and electronic features that are needed to have an optimal supramolecular interaction or interactions with a biological target structure in order to precipitate its biological response. Choose a representative as a set of actives, most methods will look for similar bindings. It is preferred to have multiple rigid molecules and the ligands should be diversified, in other words ensure to have different features that don't occur during the binding phase. === Shape-based virtual screening === Shape-based molecular similarity approaches have been established as important and popular virtual screening techniques. At present, the highly optimized screening platform ROCS (Rapid Overlay of Chemical Structures) is considered the de facto industry standard for shape-based, ligand-centric virtual screening. It uses a Gaussian function to define molecular volumes of small organic molecules. The selection of the query conformation is less important, rendering shape-based screening ideal for ligand-based modeling: As the availability of a bioactive conformation for the query is not the limiting factor for screening
|
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— it is more the selection of query compound(s) that is decisive for screening performance. Other shape-based molecular similarity methods such as Autodock-SS have also been developed. === Field-based virtual screening === As an improvement to shape-based similarity methods, field-based methods try to take into account all the fields that influence a ligand-receptor interaction while being agnostic of the chemical structure used as a query. Various other fields are used in these methods, such as electrostatic or hydrophobic fields. == Quantitative-structure activity relationship == Quantitative-structure activity relationship (QSAR) models consist of predictive models based on information extracted from a set of known active and known inactive compounds. SAR's (structure activity relationship) where data is treated qualitatively and can be used with structural classes and more than one binding mode. Models prioritize compounds for lead discovery. == Machine learning algorithms == Machine learning algorithms have been widely used in virtual screening approaches. Supervised learning techniques use a training and test datasets composed of known active and known inactive compounds. Different ML algorithms have been applied with success in virtual screening strategies, such as recursive partitioning, support vector machines, random forest, k-nearest neighbors and neural networks. These models find the probability that a compound is active and then ranking each compound based on its probability. === Substructural analysis in machine learning === The first machine learning model used on large datasets is the substructure analysis that was created in 1973. Each fragment substructure make a continuous contribution an activity of specific type. Substructure is a method that overcomes the difficulty of massive dimensionality when it comes to analyzing structures in drug design. An efficient substructure analysis is used for structures that have similarities to a multi-level building or tower. Geometry is used for numbering boundary joints for a given structure in the
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onset and towards the climax. When the method of special static condensation and substitutions routines are developed this method is proved to be more productive than the previous substructure analysis models. === Recursive partitioning === Recursively partitioning is method that creates a decision tree using qualitative data. Understanding the way rules break classes up with a low error of misclassification while repeating each step until no sensible splits can be found. However, recursive partitioning can have poor prediction ability potentially creating fine models at the same rate. == Structure-based methods known protein ligand docking == Ligand can bind into an active site within a protein by using a docking search algorithm, and scoring function in order to identify the most likely cause for an individual ligand while assigning a priority order. == See also == Grid computing High-throughput screening Docking (molecular) Retro screening Scoring functions ZINC database == References == == Further reading == == External links == VLS3D – list of over 2000 databases, online and standalone in silico tools
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The second law of thermodynamics is a physical law based on universal empirical observation concerning heat and energy interconversions. A simple statement of the law is that heat always flows spontaneously from hotter to colder regions of matter (or 'downhill' in terms of the temperature gradient). Another statement is: "Not all heat can be converted into work in a cyclic process." The second law of thermodynamics establishes the concept of entropy as a physical property of a thermodynamic system. It predicts whether processes are forbidden despite obeying the requirement of conservation of energy as expressed in the first law of thermodynamics and provides necessary criteria for spontaneous processes. For example, the first law allows the process of a cup falling off a table and breaking on the floor, as well as allowing the reverse process of the cup fragments coming back together and 'jumping' back onto the table, while the second law allows the former and denies the latter. The second law may be formulated by the observation that the entropy of isolated systems left to spontaneous evolution cannot decrease, as they always tend toward a state of thermodynamic equilibrium where the entropy is highest at the given internal energy. An increase in the combined entropy of system and surroundings accounts for the irreversibility of natural processes, often referred to in the concept of the arrow of time. Historically, the second law was an empirical finding that was accepted as an axiom of thermodynamic theory. Statistical mechanics provides a microscopic explanation of the law in terms of probability distributions of the states of large assemblies of atoms or molecules. The second law has been expressed in many ways. Its first formulation, which preceded the proper definition of entropy and was based on caloric theory, is Carnot's theorem, formulated by the
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French scientist Sadi Carnot, who in 1824 showed that the efficiency of conversion of heat to work in a heat engine has an upper limit. The first rigorous definition of the second law based on the concept of entropy came from German scientist Rudolf Clausius in the 1850s and included his statement that heat can never pass from a colder to a warmer body without some other change, connected therewith, occurring at the same time. The second law of thermodynamics allows the definition of the concept of thermodynamic temperature, but this has been formally delegated to the zeroth law of thermodynamics. == Introduction == The first law of thermodynamics provides the definition of the internal energy of a thermodynamic system, and expresses its change for a closed system in terms of work and heat. It can be linked to the law of conservation of energy. Conceptually, the first law describes the fundamental principle that systems do not consume or 'use up' energy, that energy is neither created nor destroyed, but is simply converted from one form to another. The second law is concerned with the direction of natural processes. It asserts that a natural process runs only in one sense, and is not reversible. That is, the state of a natural system itself can be reversed, but not without increasing the entropy of the system's surroundings, that is, both the state of the system plus the state of its surroundings cannot be together, fully reversed, without implying the destruction of entropy. For example, when a path for conduction or radiation is made available, heat always flows spontaneously from a hotter to a colder body. Such phenomena are accounted for in terms of entropy change. A heat pump can reverse this heat flow, but the reversal process and the original process,
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both cause entropy production, thereby increasing the entropy of the system's surroundings. If an isolated system containing distinct subsystems is held initially in internal thermodynamic equilibrium by internal partitioning by impermeable walls between the subsystems, and then some operation makes the walls more permeable, then the system spontaneously evolves to reach a final new internal thermodynamic equilibrium, and its total entropy, S {\displaystyle S} , increases. In a reversible or quasi-static, idealized process of transfer of energy as heat to a closed thermodynamic system of interest, (which allows the entry or exit of energy – but not transfer of matter), from an auxiliary thermodynamic system, an infinitesimal increment ( d S {\displaystyle \mathrm {d} S} ) in the entropy of the system of interest is defined to result from an infinitesimal transfer of heat ( δ Q {\displaystyle \delta Q} ) to the system of interest, divided by the common thermodynamic temperature ( T ) {\displaystyle (T)} of the system of interest and the auxiliary thermodynamic system: d S = δ Q T (closed system; idealized, reversible process) . {\displaystyle \mathrm {d} S={\frac {\delta Q}{T}}\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,{\text{(closed system; idealized, reversible process)}}.} Different notations are used for an infinitesimal amount of heat ( δ ) {\displaystyle (\delta )} and infinitesimal change of entropy ( d ) {\displaystyle (\mathrm {d} )} because entropy is a function of state, while heat, like work, is not. For an actually possible infinitesimal process without exchange of mass with the surroundings, the second law requires that the increment in system entropy fulfills the inequality d S > δ Q T surr (closed system; actually possible, irreversible process). {\displaystyle \mathrm {d} S>{\frac {\delta Q}{T_{\text{surr}}}}\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,{\text{(closed system; actually possible, irreversible process).}}} This is because a general process for this case (no mass exchange between the system and its surroundings) may include
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work being done on the system by its surroundings, which can have frictional or viscous effects inside the system, because a chemical reaction may be in progress, or because heat transfer actually occurs only irreversibly, driven by a finite difference between the system temperature (T) and the temperature of the surroundings (Tsurr). The equality still applies for pure heat flow (only heat flow, no change in chemical composition and mass), d S = δ Q T (actually possible quasistatic irreversible process without composition change). {\displaystyle \mathrm {d} S={\frac {\delta Q}{T}}\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,{\text{(actually possible quasistatic irreversible process without composition change).}}} which is the basis of the accurate determination of the absolute entropy of pure substances from measured heat capacity curves and entropy changes at phase transitions, i.e. by calorimetry. The zeroth law of thermodynamics in its usual short statement allows recognition that two bodies in a relation of thermal equilibrium have the same temperature, especially that a test body has the same temperature as a reference thermometric body. For a body in thermal equilibrium with another, there are indefinitely many empirical temperature scales, in general respectively depending on the properties of a particular reference thermometric body. The second law allows a distinguished temperature scale, which defines an absolute, thermodynamic temperature, independent of the properties of any particular reference thermometric body. == Various statements of the law == The second law of thermodynamics may be expressed in many specific ways, the most prominent classical statements being the statement by Rudolf Clausius (1854), the statement by Lord Kelvin (1851), and the statement in axiomatic thermodynamics by Constantin Carathéodory (1909). These statements cast the law in general physical terms citing the impossibility of certain processes. The Clausius and the Kelvin statements have been shown to be equivalent. === Carnot's principle === The historical origin of the
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second law of thermodynamics was in Sadi Carnot's theoretical analysis of the flow of heat in steam engines (1824). The centerpiece of that analysis, now known as a Carnot engine, is an ideal heat engine fictively operated in the limiting mode of extreme slowness known as quasi-static, so that the heat and work transfers are between subsystems that are always in their own internal states of thermodynamic equilibrium. It represents the theoretical maximum efficiency of a heat engine operating between any two given thermal or heat reservoirs at different temperatures. Carnot's principle was recognized by Carnot at a time when the caloric theory represented the dominant understanding of the nature of heat, before the recognition of the first law of thermodynamics, and before the mathematical expression of the concept of entropy. Interpreted in the light of the first law, Carnot's analysis is physically equivalent to the second law of thermodynamics, and remains valid today. Some samples from his book are: ...wherever there exists a difference of temperature, motive power can be produced. The production of motive power is then due in steam engines not to an actual consumption of caloric, but to its transportation from a warm body to a cold body ... The motive power of heat is independent of the agents employed to realize it; its quantity is fixed solely by the temperatures of the bodies between which is effected, finally, the transfer of caloric. In modern terms, Carnot's principle may be stated more precisely: The efficiency of a quasi-static or reversible Carnot cycle depends only on the temperatures of the two heat reservoirs, and is the same, whatever the working substance. A Carnot engine operated in this way is the most efficient possible heat engine using those two temperatures. === Clausius statement === The German scientist Rudolf
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Clausius laid the foundation for the second law of thermodynamics in 1850 by examining the relation between heat transfer and work. His formulation of the second law, which was published in German in 1854, is known as the Clausius statement: Heat can never pass from a colder to a warmer body without some other change, connected therewith, occurring at the same time. The statement by Clausius uses the concept of 'passage of heat'. As is usual in thermodynamic discussions, this means 'net transfer of energy as heat', and does not refer to contributory transfers one way and the other. Heat cannot spontaneously flow from cold regions to hot regions without external work being performed on the system, which is evident from ordinary experience of refrigeration, for example. In a refrigerator, heat is transferred from cold to hot, but only when forced by an external agent, the refrigeration system. === Kelvin statements === Lord Kelvin expressed the second law in several wordings. It is impossible for a self-acting machine, unaided by any external agency, to convey heat from one body to another at a higher temperature. It is impossible, by means of inanimate material agency, to derive mechanical effect from any portion of matter by cooling it below the temperature of the coldest of the surrounding objects. === Equivalence of the Clausius and the Kelvin statements === Suppose there is an engine violating the Kelvin statement: i.e., one that drains heat and converts it completely into work (the drained heat is fully converted to work) in a cyclic fashion without any other result. Now pair it with a reversed Carnot engine as shown by the right figure. The efficiency of a normal heat engine is η and so the efficiency of the reversed heat engine is 1/η. The net and sole
|
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effect of the combined pair of engines is to transfer heat Δ Q = Q ( 1 η − 1 ) {\textstyle \Delta Q=Q\left({\frac {1}{\eta }}-1\right)} from the cooler reservoir to the hotter one, which violates the Clausius statement. This is a consequence of the first law of thermodynamics, as for the total system's energy to remain the same; Input + Output = 0 ⟹ ( Q + Q c ) − Q η = 0 {\textstyle {\text{Input}}+{\text{Output}}=0\implies (Q+Q_{c})-{\frac {Q}{\eta }}=0} , so therefore Q c = Q ( 1 η − 1 ) {\textstyle Q_{c}=Q\left({\frac {1}{\eta }}-1\right)} , where (1) the sign convention of heat is used in which heat entering into (leaving from) an engine is positive (negative) and (2) Q η {\displaystyle {\frac {Q}{\eta }}} is obtained by the definition of efficiency of the engine when the engine operation is not reversed. Thus a violation of the Kelvin statement implies a violation of the Clausius statement, i.e. the Clausius statement implies the Kelvin statement. We can prove in a similar manner that the Kelvin statement implies the Clausius statement, and hence the two are equivalent. === Planck's proposition === Planck offered the following proposition as derived directly from experience. This is sometimes regarded as his statement of the second law, but he regarded it as a starting point for the derivation of the second law. It is impossible to construct an engine which will work in a complete cycle, and produce no effect except the production of work and cooling of a heat reservoir. === Relation between Kelvin's statement and Planck's proposition === It is almost customary in textbooks to speak of the "Kelvin–Planck statement" of the law, as for example in the text by ter Haar and Wergeland. This version, also known as the heat engine
|
{
"page_id": 133017,
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statement, of the second law states that It is impossible to devise a cyclically operating device, the sole effect of which is to absorb energy in the form of heat from a single thermal reservoir and to deliver an equivalent amount of work. === Planck's statement === Max Planck stated the second law as follows. Every process occurring in nature proceeds in the sense in which the sum of the entropies of all bodies taking part in the process is increased. In the limit, i.e. for reversible processes, the sum of the entropies remains unchanged. Rather like Planck's statement is that of George Uhlenbeck and G. W. Ford for irreversible phenomena. ... in an irreversible or spontaneous change from one equilibrium state to another (as for example the equalization of temperature of two bodies A and B, when brought in contact) the entropy always increases. === Principle of Carathéodory === Constantin Carathéodory formulated thermodynamics on a purely mathematical axiomatic foundation. His statement of the second law is known as the Principle of Carathéodory, which may be formulated as follows: In every neighborhood of any state S of an adiabatically enclosed system there are states inaccessible from S. With this formulation, he described the concept of adiabatic accessibility for the first time and provided the foundation for a new subfield of classical thermodynamics, often called geometrical thermodynamics. It follows from Carathéodory's principle that quantity of energy quasi-statically transferred as heat is a holonomic process function, in other words, δ Q = T d S {\displaystyle \delta Q=TdS} . Though it is almost customary in textbooks to say that Carathéodory's principle expresses the second law and to treat it as equivalent to the Clausius or to the Kelvin-Planck statements, such is not the case. To get all the content of the second
|
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}
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law, Carathéodory's principle needs to be supplemented by Planck's principle, that isochoric work always increases the internal energy of a closed system that was initially in its own internal thermodynamic equilibrium. === Planck's principle === In 1926, Max Planck wrote an important paper on the basics of thermodynamics. He indicated the principle The internal energy of a closed system is increased by an adiabatic process, throughout the duration of which, the volume of the system remains constant. This formulation does not mention heat and does not mention temperature, nor even entropy, and does not necessarily implicitly rely on those concepts, but it implies the content of the second law. A closely related statement is that "Frictional pressure never does positive work." Planck wrote: "The production of heat by friction is irreversible." Not mentioning entropy, this principle of Planck is stated in physical terms. It is very closely related to the Kelvin statement given just above. It is relevant that for a system at constant volume and mole numbers, the entropy is a monotonic function of the internal energy. Nevertheless, this principle of Planck is not actually Planck's preferred statement of the second law, which is quoted above, in a previous sub-section of the present section of this present article, and relies on the concept of entropy. A statement that in a sense is complementary to Planck's principle is made by Claus Borgnakke and Richard E. Sonntag. They do not offer it as a full statement of the second law: ... there is only one way in which the entropy of a [closed] system can be decreased, and that is to transfer heat from the system. Differing from Planck's just foregoing principle, this one is explicitly in terms of entropy change. Removal of matter from a system can also decrease its
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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entropy. === Relating the second law to the definition of temperature === The second law has been shown to be equivalent to the internal energy U defined as a convex function of the other extensive properties of the system. That is, when a system is described by stating its internal energy U, an extensive variable, as a function of its entropy S, volume V, and mol number N, i.e. U = U (S, V, N), then the temperature is equal to the partial derivative of the internal energy with respect to the entropy (essentially equivalent to the first TdS equation for V and N held constant): T = ( ∂ U ∂ S ) V , N {\displaystyle T=\left({\frac {\partial U}{\partial S}}\right)_{V,N}} === Second law statements, such as the Clausius inequality, involving radiative fluxes === The Clausius inequality, as well as some other statements of the second law, must be re-stated to have general applicability for all forms of heat transfer, i.e. scenarios involving radiative fluxes. For example, the integrand (đQ/T) of the Clausius expression applies to heat conduction and convection, and the case of ideal infinitesimal blackbody radiation (BR) transfer, but does not apply to most radiative transfer scenarios and in some cases has no physical meaning whatsoever. Consequently, the Clausius inequality was re-stated so that it is applicable to cycles with processes involving any form of heat transfer. The entropy transfer with radiative fluxes ( δ S NetRad \delta S_{\text{NetRad}} ) is taken separately from that due to heat transfer by conduction and convection ( δ Q C C \delta Q_{CC} ), where the temperature is evaluated at the system boundary where the heat transfer occurs. The modified Clausius inequality, for all heat transfer scenarios, can then be expressed as, ∫ cycle ( δ Q C C T
|
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"page_id": 133017,
"source": null,
"title": "Second law of thermodynamics"
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b + δ S NetRad ) ≤ 0 {\displaystyle \int _{\text{cycle}}({\frac {\delta Q_{CC}}{T_{b}}}+\delta S_{\text{NetRad}})\leq 0} In a nutshell, the Clausius inequality is saying that when a cycle is completed, the change in the state property S will be zero, so the entropy that was produced during the cycle must have transferred out of the system by heat transfer. The δ \delta (or đ) indicates a path dependent integration. Due to the inherent emission of radiation from all matter, most entropy flux calculations involve incident, reflected and emitted radiative fluxes. The energy and entropy of unpolarized blackbody thermal radiation, is calculated using the spectral energy and entropy radiance expressions derived by Max Planck using equilibrium statistical mechanics, K ν = 2 h c 2 ν 3 exp ( h ν k T ) − 1 , {\displaystyle K_{\nu }={\frac {2h}{c^{2}}}{\frac {\nu ^{3}}{\exp \left({\frac {h\nu }{kT}}\right)-1}},} L ν = 2 k ν 2 c 2 ( ( 1 + c 2 K ν 2 h ν 3 ) ln ( 1 + c 2 K ν 2 h ν 3 ) − ( c 2 K ν 2 h ν 3 ) ln ( c 2 K ν 2 h ν 3 ) ) {\displaystyle L_{\nu }={\frac {2k\nu ^{2}}{c^{2}}}((1+{\frac {c^{2}K_{\nu }}{2h\nu ^{3}}})\ln(1+{\frac {c^{2}K_{\nu }}{2h\nu ^{3}}})-({\frac {c^{2}K_{\nu }}{2h\nu ^{3}}})\ln({\frac {c^{2}K_{\nu }}{2h\nu ^{3}}}))} where c is the speed of light, k is the Boltzmann constant, h is the Planck constant, ν is frequency, and the quantities Kv and Lv are the energy and entropy fluxes per unit frequency, area, and solid angle. In deriving this blackbody spectral entropy radiance, with the goal of deriving the blackbody energy formula, Planck postulated that the energy of a photon was quantized (partly to simplify the mathematics), thereby starting quantum theory. A non-equilibrium statistical mechanics
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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approach has also been used to obtain the same result as Planck, indicating it has wider significance and represents a non-equilibrium entropy. A plot of Kv versus frequency (v) for various values of temperature (T) gives a family of blackbody radiation energy spectra, and likewise for the entropy spectra. For non-blackbody radiation (NBR) emission fluxes, the spectral entropy radiance Lv is found by substituting Kv spectral energy radiance data into the Lv expression (noting that emitted and reflected entropy fluxes are, in general, not independent). For the emission of NBR, including graybody radiation (GR), the resultant emitted entropy flux, or radiance L, has a higher ratio of entropy-to-energy (L/K), than that of BR. That is, the entropy flux of NBR emission is farther removed from the conduction and convection q/T result, than that for BR emission. This observation is consistent with Max Planck's blackbody radiation energy and entropy formulas and is consistent with the fact that blackbody radiation emission represents the maximum emission of entropy for all materials with the same temperature, as well as the maximum entropy emission for all radiation with the same energy radiance. === Generalized conceptual statement of the second law principle === Second law analysis is valuable in scientific and engineering analysis in that it provides a number of benefits over energy analysis alone, including the basis for determining energy quality (exergy content), understanding fundamental physical phenomena, and improving performance evaluation and optimization. As a result, a conceptual statement of the principle is very useful in engineering analysis. Thermodynamic systems can be categorized by the four combinations of either entropy (S) up or down, and uniformity (Y) – between system and its environment – up or down. This 'special' category of processes, category IV, is characterized by movement in the direction of low disorder and
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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low uniformity, counteracting the second law tendency towards uniformity and disorder. The second law can be conceptually stated as follows: Matter and energy have the tendency to reach a state of uniformity or internal and external equilibrium, a state of maximum disorder (entropy). Real non-equilibrium processes always produce entropy, causing increased disorder in the universe, while idealized reversible processes produce no entropy and no process is known to exist that destroys entropy. The tendency of a system to approach uniformity may be counteracted, and the system may become more ordered or complex, by the combination of two things, a work or exergy source and some form of instruction or intelligence. Where 'exergy' is the thermal, mechanical, electric or chemical work potential of an energy source or flow, and 'instruction or intelligence', although subjective, is in the context of the set of category IV processes. Consider a category IV example of robotic manufacturing and assembly of vehicles in a factory. The robotic machinery requires electrical work input and instructions, but when completed, the manufactured products have less uniformity with their surroundings, or more complexity (higher order) relative to the raw materials they were made from. Thus, system entropy or disorder decreases while the tendency towards uniformity between the system and its environment is counteracted. In this example, the instructions, as well as the source of work may be internal or external to the system, and they may or may not cross the system boundary. To illustrate, the instructions may be pre-coded and the electrical work may be stored in an energy storage system on-site. Alternatively, the control of the machinery may be by remote operation over a communications network, while the electric work is supplied to the factory from the local electric grid. In addition, humans may directly play, in whole
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"page_id": 133017,
"source": null,
"title": "Second law of thermodynamics"
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or in part, the role that the robotic machinery plays in manufacturing. In this case, instructions may be involved, but intelligence is either directly responsible, or indirectly responsible, for the direction or application of work in such a way as to counteract the tendency towards disorder and uniformity. There are also situations where the entropy spontaneously decreases by means of energy and entropy transfer. When thermodynamic constraints are not present, spontaneously energy or mass, as well as accompanying entropy, may be transferred out of a system in a progress to reach external equilibrium or uniformity in intensive properties of the system with its surroundings. This occurs spontaneously because the energy or mass transferred from the system to its surroundings results in a higher entropy in the surroundings, that is, it results in higher overall entropy of the system plus its surroundings. Note that this transfer of entropy requires dis-equilibrium in properties, such as a temperature difference. One example of this is the cooling crystallization of water that can occur when the system's surroundings are below freezing temperatures. Unconstrained heat transfer can spontaneously occur, leading to water molecules freezing into a crystallized structure of reduced disorder (sticking together in a certain order due to molecular attraction). The entropy of the system decreases, but the system approaches uniformity with its surroundings (category III). On the other hand, consider the refrigeration of water in a warm environment. Due to refrigeration, as heat is extracted from the water, the temperature and entropy of the water decreases, as the system moves further away from uniformity with its warm surroundings or environment (category IV). The main point, take-away, is that refrigeration not only requires a source of work, it requires designed equipment, as well as pre-coded or direct operational intelligence or instructions to achieve the desired
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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refrigeration effect. == Corollaries == === Perpetual motion of the second kind === Before the establishment of the second law, many people who were interested in inventing a perpetual motion machine had tried to circumvent the restrictions of first law of thermodynamics by extracting the massive internal energy of the environment as the power of the machine. Such a machine is called a "perpetual motion machine of the second kind". The second law declared the impossibility of such machines. === Carnot's theorem === Carnot's theorem (1824) is a principle that limits the maximum efficiency for any possible engine. The efficiency solely depends on the temperature difference between the hot and cold thermal reservoirs. Carnot's theorem states: All irreversible heat engines between two heat reservoirs are less efficient than a Carnot engine operating between the same reservoirs. All reversible heat engines between two heat reservoirs are equally efficient with a Carnot engine operating between the same reservoirs. In his ideal model, the heat of caloric converted into work could be reinstated by reversing the motion of the cycle, a concept subsequently known as thermodynamic reversibility. Carnot, however, further postulated that some caloric is lost, not being converted to mechanical work. Hence, no real heat engine could realize the Carnot cycle's reversibility and was condemned to be less efficient. Though formulated in terms of caloric (see the obsolete caloric theory), rather than entropy, this was an early insight into the second law. === Clausius inequality === The Clausius theorem (1854) states that in a cyclic process ∮ δ Q T surr ≤ 0. {\displaystyle \oint {\frac {\delta Q}{T_{\text{surr}}}}\leq 0.} The equality holds in the reversible case and the strict inequality holds in the irreversible case, with Tsurr as the temperature of the heat bath (surroundings) here. The reversible case is used to
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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introduce the state function entropy. This is because in cyclic processes the variation of a state function is zero from state functionality. === Thermodynamic temperature === For an arbitrary heat engine, the efficiency is: where Wn is the net work done by the engine per cycle, qH > 0 is the heat added to the engine from a hot reservoir, and qC = −|qC| < 0 is waste heat given off to a cold reservoir from the engine. Thus the efficiency depends only on the ratio |qC| / |qH|. Carnot's theorem states that all reversible engines operating between the same heat reservoirs are equally efficient. Thus, any reversible heat engine operating between temperatures TH and TC must have the same efficiency, that is to say, the efficiency is a function of temperatures only: In addition, a reversible heat engine operating between temperatures T1 and T3 must have the same efficiency as one consisting of two cycles, one between T1 and another (intermediate) temperature T2, and the second between T2 and T3, where T1 > T2 > T3. This is because, if a part of the two cycle engine is hidden such that it is recognized as an engine between the reservoirs at the temperatures T1 and T3, then the efficiency of this engine must be same to the other engine at the same reservoirs. If we choose engines such that work done by the one cycle engine and the two cycle engine are same, then the efficiency of each heat engine is written as the below. η 1 = 1 − | q 3 | | q 1 | = 1 − f ( T 1 , T 3 ) {\displaystyle \eta _{1}=1-{\frac {|q_{3}|}{|q_{1}|}}=1-f(T_{1},T_{3})} , η 2 = 1 − | q 2 | | q 1 | = 1
|
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"page_id": 133017,
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− f ( T 1 , T 2 ) {\displaystyle \eta _{2}=1-{\frac {|q_{2}|}{|q_{1}|}}=1-f(T_{1},T_{2})} , η 3 = 1 − | q 3 | | q 2 | = 1 − f ( T 2 , T 3 ) {\displaystyle \eta _{3}=1-{\frac {|q_{3}|}{|q_{2}|}}=1-f(T_{2},T_{3})} . Here, the engine 1 is the one cycle engine, and the engines 2 and 3 make the two cycle engine where there is the intermediate reservoir at T2. We also have used the fact that the heat q 2 {\displaystyle q_{2}} passes through the intermediate thermal reservoir at T 2 {\displaystyle T_{2}} without losing its energy. (I.e., q 2 {\displaystyle q_{2}} is not lost during its passage through the reservoir at T 2 {\displaystyle T_{2}} .) This fact can be proved by the following. η 2 = 1 − | q 2 | | q 1 | → | w 2 | = | q 1 | − | q 2 | , η 3 = 1 − | q 3 | | q 2 ∗ | → | w 3 | = | q 2 ∗ | − | q 3 | , | w 2 | + | w 3 | = ( | q 1 | − | q 2 | ) + ( | q 2 ∗ | − | q 3 | ) , η 1 = 1 − | q 3 | | q 1 | = ( | w 2 | + | w 3 | ) | q 1 | = ( | q 1 | − | q 2 | ) + ( | q 2 ∗ | − | q 3 | ) | q 1 | . {\displaystyle {\begin{aligned}&{{\eta }_{2}}=1-{\frac {|{{q}_{2}}|}{|{{q}_{1}}|}}\to |{{w}_{2}}|=|{{q}_{1}}|-|{{q}_{2}}|,\\&{{\eta }_{3}}=1-{\frac {|{{q}_{3}}|}{|{{q}_{2}}^{*}|}}\to |{{w}_{3}}|=|{{q}_{2}}^{*}|-|{{q}_{3}}|,\\&|{{w}_{2}}|+|{{w}_{3}}|=(|{{q}_{1}}|-|{{q}_{2}}|)+(|{{q}_{2}}^{*}|-|{{q}_{3}}|),\\&{{\eta }_{1}}=1-{\frac {|{{q}_{3}}|}{|{{q}_{1}}|}}={\frac {(|{{w}_{2}}|+|{{w}_{3}}|)}{|{{q}_{1}}|}}={\frac {(|{{q}_{1}}|-|{{q}_{2}}|)+(|{{q}_{2}}^{*}|-|{{q}_{3}}|)}{|{{q}_{1}}|}}.\\\end{aligned}}} In order to have the consistency in
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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the last equation, the heat q 2 {\displaystyle q_{2}} flown from the engine 2 to the intermediate reservoir must be equal to the heat q 2 ∗ {\displaystyle q_{2}^{*}} flown out from the reservoir to the engine 3. Then f ( T 1 , T 3 ) = | q 3 | | q 1 | = | q 2 | | q 3 | | q 1 | | q 2 | = f ( T 1 , T 2 ) f ( T 2 , T 3 ) . {\displaystyle f(T_{1},T_{3})={\frac {|q_{3}|}{|q_{1}|}}={\frac {|q_{2}||q_{3}|}{|q_{1}||q_{2}|}}=f(T_{1},T_{2})f(T_{2},T_{3}).} Now consider the case where T 1 {\displaystyle T_{1}} is a fixed reference temperature: the temperature of the triple point of water as 273.16 K; T 1 = 273.16 K {\displaystyle T_{1}=\mathrm {273.16~K} } . Then for any T2 and T3, f ( T 2 , T 3 ) = f ( T 1 , T 3 ) f ( T 1 , T 2 ) = 273.16 K ⋅ f ( T 1 , T 3 ) 273.16 K ⋅ f ( T 1 , T 2 ) . {\displaystyle f(T_{2},T_{3})={\frac {f(T_{1},T_{3})}{f(T_{1},T_{2})}}={\frac {273.16{\text{ K}}\cdot f(T_{1},T_{3})}{273.16{\text{ K}}\cdot f(T_{1},T_{2})}}.} Therefore, if thermodynamic temperature T* is defined by T ∗ = 273.16 K ⋅ f ( T 1 , T ) {\displaystyle T^{*}=273.16{\text{ K}}\cdot f(T_{1},T)} then the function f, viewed as a function of thermodynamic temperatures, is simply f ( T 2 , T 3 ) = f ( T 2 ∗ , T 3 ∗ ) = T 3 ∗ T 2 ∗ , {\displaystyle f(T_{2},T_{3})=f(T_{2}^{*},T_{3}^{*})={\frac {T_{3}^{*}}{T_{2}^{*}}},} and the reference temperature T1* = 273.16 K × f(T1,T1) = 273.16 K. (Any reference temperature and any positive numerical value could be used – the choice here corresponds to the Kelvin scale.) === Entropy === According to the
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"page_id": 133017,
"source": null,
"title": "Second law of thermodynamics"
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Clausius equality, for a reversible process ∮ δ Q T = 0 {\displaystyle \oint {\frac {\delta Q}{T}}=0} That means the line integral ∫ L δ Q T {\displaystyle \int _{L}{\frac {\delta Q}{T}}} is path independent for reversible processes. So we can define a state function S called entropy, which for a reversible process or for pure heat transfer satisfies d S = δ Q T {\displaystyle dS={\frac {\delta Q}{T}}} With this we can only obtain the difference of entropy by integrating the above formula. To obtain the absolute value, we need the third law of thermodynamics, which states that S = 0 at absolute zero for perfect crystals. For any irreversible process, since entropy is a state function, we can always connect the initial and terminal states with an imaginary reversible process and integrating on that path to calculate the difference in entropy. Now reverse the reversible process and combine it with the said irreversible process. Applying the Clausius inequality on this loop, with Tsurr as the temperature of the surroundings, − Δ S + ∫ δ Q T surr = ∮ δ Q T surr ≤ 0 {\displaystyle -\Delta S+\int {\frac {\delta Q}{T_{\text{surr}}}}=\oint {\frac {\delta Q}{T_{\text{surr}}}}\leq 0} Thus, Δ S ≥ ∫ δ Q T surr {\displaystyle \Delta S\geq \int {\frac {\delta Q}{T_{\text{surr}}}}} where the equality holds if the transformation is reversible. If the process is an adiabatic process, then δ Q = 0 {\displaystyle \delta Q=0} , so Δ S ≥ 0 {\displaystyle \Delta S\geq 0} . === Energy, available useful work === An important and revealing idealized special case is to consider applying the second law to the scenario of an isolated system (called the total system or universe), made up of two parts: a sub-system of interest, and the sub-system's surroundings. These surroundings are imagined to
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{
"page_id": 133017,
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be so large that they can be considered as an unlimited heat reservoir at temperature TR and pressure PR – so that no matter how much heat is transferred to (or from) the sub-system, the temperature of the surroundings will remain TR; and no matter how much the volume of the sub-system expands (or contracts), the pressure of the surroundings will remain PR. Whatever changes to dS and dSR occur in the entropies of the sub-system and the surroundings individually, the entropy Stot of the isolated total system must not decrease according to the second law of thermodynamics: d S t o t = d S + d S R ≥ 0 {\displaystyle dS_{\mathrm {tot} }=dS+dS_{\text{R}}\geq 0} According to the first law of thermodynamics, the change dU in the internal energy of the sub-system is the sum of the heat δq added to the sub-system, minus any work δw done by the sub-system, plus any net chemical energy entering the sub-system d ΣμiRNi, so that: d U = δ q − δ w + d ( ∑ μ i R N i ) {\displaystyle dU=\delta q-\delta w+d\left(\sum \mu _{iR}N_{i}\right)} where μiR are the chemical potentials of chemical species in the external surroundings. Now the heat leaving the reservoir and entering the sub-system is δ q = T R ( − d S R ) ≤ T R d S {\displaystyle \delta q=T_{\text{R}}(-dS_{\text{R}})\leq T_{\text{R}}dS} where we have first used the definition of entropy in classical thermodynamics (alternatively, in statistical thermodynamics, the relation between entropy change, temperature and absorbed heat can be derived); and then the second law inequality from above. It therefore follows that any net work δw done by the sub-system must obey δ w ≤ − d U + T R d S + ∑ μ i R d
|
{
"page_id": 133017,
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N i {\displaystyle \delta w\leq -dU+T_{\text{R}}dS+\sum \mu _{iR}dN_{i}} It is useful to separate the work δw done by the subsystem into the useful work δwu that can be done by the sub-system, over and beyond the work pR dV done merely by the sub-system expanding against the surrounding external pressure, giving the following relation for the useful work (exergy) that can be done: δ w u ≤ − d ( U − T R S + p R V − ∑ μ i R N i ) {\displaystyle \delta w_{u}\leq -d\left(U-T_{\text{R}}S+p_{\text{R}}V-\sum \mu _{iR}N_{i}\right)} It is convenient to define the right-hand-side as the exact derivative of a thermodynamic potential, called the availability or exergy E of the subsystem, E = U − T R S + p R V − ∑ μ i R N i {\displaystyle E=U-T_{\text{R}}S+p_{\text{R}}V-\sum \mu _{iR}N_{i}} The second law therefore implies that for any process which can be considered as divided simply into a subsystem, and an unlimited temperature and pressure reservoir with which it is in contact, d E + δ w u ≤ 0 {\displaystyle dE+\delta w_{u}\leq 0} i.e. the change in the subsystem's exergy plus the useful work done by the subsystem (or, the change in the subsystem's exergy less any work, additional to that done by the pressure reservoir, done on the system) must be less than or equal to zero. In sum, if a proper infinite-reservoir-like reference state is chosen as the system surroundings in the real world, then the second law predicts a decrease in E for an irreversible process and no change for a reversible process. d S tot ≥ 0 {\displaystyle dS_{\text{tot}}\geq 0} is equivalent to d E + δ w u ≤ 0 {\displaystyle dE+\delta w_{u}\leq 0} This expression together with the associated reference state permits a design
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"page_id": 133017,
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engineer working at the macroscopic scale (above the thermodynamic limit) to utilize the second law without directly measuring or considering entropy change in a total isolated system (see also Process engineer). Those changes have already been considered by the assumption that the system under consideration can reach equilibrium with the reference state without altering the reference state. An efficiency for a process or collection of processes that compares it to the reversible ideal may also be found (see Exergy efficiency). This approach to the second law is widely utilized in engineering practice, environmental accounting, systems ecology, and other disciplines. == Direction of spontaneous processes == The second law determines whether a proposed physical or chemical process is forbidden or may occur spontaneously. For isolated systems, no energy is provided by the surroundings and the second law requires that the entropy of the system alone cannot decrease: ΔS ≥ 0. Examples of spontaneous physical processes in isolated systems include the following: 1) Heat can be transferred from a region of higher temperature to a lower temperature (but not the reverse). 2) Mechanical energy can be converted to thermal energy (but not the reverse). 3) A solute can move from a region of higher concentration to a region of lower concentration (but not the reverse). However, for some non-isolated systems which can exchange energy with their surroundings, the surroundings exchange enough heat with the system, or do sufficient work on the system, so that the processes occur in the opposite direction. In such a case, the reverse process can occur because it is coupled to a simultaneous process that increases the entropy of the surroundings. The coupled process will go forward provided that the total entropy change of the system and surroundings combined is nonnegative as required by the second law: ΔStot
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"page_id": 133017,
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= ΔS + ΔSR ≥ 0. For the three examples given above: 1) Heat can be transferred from a region of lower temperature to a higher temperature by a refrigerator or heat pump, provided that the device delivers sufficient mechanical work to the system and converts it to thermal energy inside the system. 2) Thermal energy can be converted by a heat engine to mechanical work within a system at a single temperature, provided that the heat engine transfers a sufficient amount of heat from the system to a lower-temperature region in the surroundings. 3) A solute can travel from a region of lower concentration to a region of higher concentration in the biochemical process of active transport, if sufficient work is provided by a concentration gradient of a chemical such as ATP or by an electrochemical gradient. === Second law in chemical thermodynamics === For a spontaneous chemical process in a closed system at constant temperature and pressure without non-PV work, the Clausius inequality ΔS > Q/Tsurr transforms into a condition for the change in Gibbs free energy Δ G < 0 {\displaystyle \Delta G<0} or dG < 0. For a similar process at constant temperature and volume, the change in Helmholtz free energy must be negative, Δ A < 0 {\displaystyle \Delta A<0} . Thus, a negative value of the change in free energy (G or A) is a necessary condition for a process to be spontaneous. This is the most useful form of the second law of thermodynamics in chemistry, where free-energy changes can be calculated from tabulated enthalpies of formation and standard molar entropies of reactants and products. The chemical equilibrium condition at constant T and p without electrical work is dG = 0. == History == The first theory of the conversion of heat into
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{
"page_id": 133017,
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"title": "Second law of thermodynamics"
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mechanical work is due to Nicolas Léonard Sadi Carnot in 1824. He was the first to realize correctly that the efficiency of this conversion depends on the difference of temperature between an engine and its surroundings. Recognizing the significance of James Prescott Joule's work on the conservation of energy, Rudolf Clausius was the first to formulate the second law during 1850, in this form: heat does not flow spontaneously from cold to hot bodies. While common knowledge now, this was contrary to the caloric theory of heat popular at the time, which considered heat as a fluid. From there he was able to infer the principle of Sadi Carnot and the definition of entropy (1865). Established during the 19th century, the Kelvin-Planck statement of the second law says, "It is impossible for any device that operates on a cycle to receive heat from a single reservoir and produce a net amount of work." This statement was shown to be equivalent to the statement of Clausius. The ergodic hypothesis is also important for the Boltzmann approach. It says that, over long periods of time, the time spent in some region of the phase space of microstates with the same energy is proportional to the volume of this region, i.e. that all accessible microstates are equally probable over a long period of time. Equivalently, it says that time average and average over the statistical ensemble are the same. There is a traditional doctrine, starting with Clausius, that entropy can be understood in terms of molecular 'disorder' within a macroscopic system. This doctrine is obsolescent. === Account given by Clausius === In 1865, the German physicist Rudolf Clausius stated what he called the "second fundamental theorem in the mechanical theory of heat" in the following form: ∫ δ Q T = − N
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{
"page_id": 133017,
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"title": "Second law of thermodynamics"
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{\displaystyle \int {\frac {\delta Q}{T}}=-N} where Q is heat, T is temperature and N is the "equivalence-value" of all uncompensated transformations involved in a cyclical process. Later, in 1865, Clausius would come to define "equivalence-value" as entropy. On the heels of this definition, that same year, the most famous version of the second law was read in a presentation at the Philosophical Society of Zurich on April 24, in which, in the end of his presentation, Clausius concludes: The entropy of the universe tends to a maximum. This statement is the best-known phrasing of the second law. Because of the looseness of its language, e.g. universe, as well as lack of specific conditions, e.g. open, closed, or isolated, many people take this simple statement to mean that the second law of thermodynamics applies virtually to every subject imaginable. This is not true; this statement is only a simplified version of a more extended and precise description. In terms of time variation, the mathematical statement of the second law for an isolated system undergoing an arbitrary transformation is: d S d t ≥ 0 {\displaystyle {\frac {dS}{dt}}\geq 0} where S is the entropy of the system and t is time. The equality sign applies after equilibration. An alternative way of formulating of the second law for isolated systems is: d S d t = S ˙ i {\displaystyle {\frac {dS}{dt}}={\dot {S}}_{\text{i}}} with S ˙ i ≥ 0 {\displaystyle {\dot {S}}_{\text{i}}\geq 0} with S ˙ i {\displaystyle {\dot {S}}_{\text{i}}} the sum of the rate of entropy production by all processes inside the system. The advantage of this formulation is that it shows the effect of the entropy production. The rate of entropy production is a very important concept since it determines (limits) the efficiency of thermal machines. Multiplied with ambient temperature T
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{
"page_id": 133017,
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"title": "Second law of thermodynamics"
}
|
a {\displaystyle T_{\text{a}}} it gives the so-called dissipated energy P diss = T a S ˙ i {\displaystyle P_{\text{diss}}=T_{\text{a}}{\dot {S}}_{\text{i}}} . The expression of the second law for closed systems (so, allowing heat exchange and moving boundaries, but not exchange of matter) is: d S d t = Q ˙ T + S ˙ i {\displaystyle {\frac {dS}{dt}}={\frac {\dot {Q}}{T}}+{\dot {S}}_{\text{i}}} with S ˙ i ≥ 0 {\displaystyle {\dot {S}}_{\text{i}}\geq 0} Here, Q ˙ {\displaystyle {\dot {Q}}} is the heat flow into the system T {\displaystyle T} is the temperature at the point where the heat enters the system. The equality sign holds in the case that only reversible processes take place inside the system. If irreversible processes take place (which is the case in real systems in operation) the >-sign holds. If heat is supplied to the system at several places we have to take the algebraic sum of the corresponding terms. For open systems (also allowing exchange of matter): d S d t = Q ˙ T + S ˙ + S ˙ i {\displaystyle {\frac {dS}{dt}}={\frac {\dot {Q}}{T}}+{\dot {S}}+{\dot {S}}_{\text{i}}} with S ˙ i ≥ 0 {\displaystyle {\dot {S}}_{\text{i}}\geq 0} Here, S ˙ {\displaystyle {\dot {S}}} is the flow of entropy into the system associated with the flow of matter entering the system. It should not be confused with the time derivative of the entropy. If matter is supplied at several places we have to take the algebraic sum of these contributions. == Statistical mechanics == Statistical mechanics gives an explanation for the second law by postulating that a material is composed of atoms and molecules which are in constant motion. A particular set of positions and velocities for each particle in the system is called a microstate of the system and because of the constant motion,
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the system is constantly changing its microstate. Statistical mechanics postulates that, in equilibrium, each microstate that the system might be in is equally likely to occur, and when this assumption is made, it leads directly to the conclusion that the second law must hold in a statistical sense. That is, the second law will hold on average, with a statistical variation on the order of 1/√N where N is the number of particles in the system. For everyday (macroscopic) situations, the probability that the second law will be violated is practically zero. However, for systems with a small number of particles, thermodynamic parameters, including the entropy, may show significant statistical deviations from that predicted by the second law. Classical thermodynamic theory does not deal with these statistical variations. == Derivation from statistical mechanics == The first mechanical argument of the Kinetic theory of gases that molecular collisions entail an equalization of temperatures and hence a tendency towards equilibrium was due to James Clerk Maxwell in 1860; Ludwig Boltzmann with his H-theorem of 1872 also argued that due to collisions gases should over time tend toward the Maxwell–Boltzmann distribution. Due to Loschmidt's paradox, derivations of the second law have to make an assumption regarding the past, namely that the system is uncorrelated at some time in the past; this allows for simple probabilistic treatment. This assumption is usually thought as a boundary condition, and thus the second law is ultimately a consequence of the initial conditions somewhere in the past, probably at the beginning of the universe (the Big Bang), though other scenarios have also been suggested. Given these assumptions, in statistical mechanics, the second law is not a postulate, rather it is a consequence of the fundamental postulate, also known as the equal prior probability postulate, so long as one
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"page_id": 133017,
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is clear that simple probability arguments are applied only to the future, while for the past there are auxiliary sources of information which tell us that it was low entropy. The first part of the second law, which states that the entropy of a thermally isolated system can only increase, is a trivial consequence of the equal prior probability postulate, if we restrict the notion of the entropy to systems in thermal equilibrium. The entropy of an isolated system in thermal equilibrium containing an amount of energy of E {\displaystyle E} is: S = k B ln [ Ω ( E ) ] {\displaystyle S=k_{\mathrm {B} }\ln \left[\Omega \left(E\right)\right]} where Ω ( E ) {\displaystyle \Omega \left(E\right)} is the number of quantum states in a small interval between E {\displaystyle E} and E + δ E {\displaystyle E+\delta E} . Here δ E {\displaystyle \delta E} is a macroscopically small energy interval that is kept fixed. Strictly speaking this means that the entropy depends on the choice of δ E {\displaystyle \delta E} . However, in the thermodynamic limit (i.e. in the limit of infinitely large system size), the specific entropy (entropy per unit volume or per unit mass) does not depend on δ E {\displaystyle \delta E} . Suppose we have an isolated system whose macroscopic state is specified by a number of variables. These macroscopic variables can, e.g., refer to the total volume, the positions of pistons in the system, etc. Then Ω {\displaystyle \Omega } will depend on the values of these variables. If a variable is not fixed, (e.g. we do not clamp a piston in a certain position), then because all the accessible states are equally likely in equilibrium, the free variable in equilibrium will be such that Ω {\displaystyle \Omega } is maximized
|
{
"page_id": 133017,
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at the given energy of the isolated system as that is the most probable situation in equilibrium. If the variable was initially fixed to some value then upon release and when the new equilibrium has been reached, the fact the variable will adjust itself so that Ω {\displaystyle \Omega } is maximized, implies that the entropy will have increased or it will have stayed the same (if the value at which the variable was fixed happened to be the equilibrium value). Suppose we start from an equilibrium situation and we suddenly remove a constraint on a variable. Then right after we do this, there are a number Ω {\displaystyle \Omega } of accessible microstates, but equilibrium has not yet been reached, so the actual probabilities of the system being in some accessible state are not yet equal to the prior probability of 1 / Ω {\displaystyle 1/\Omega } . We have already seen that in the final equilibrium state, the entropy will have increased or have stayed the same relative to the previous equilibrium state. Boltzmann's H-theorem, however, proves that the quantity H increases monotonically as a function of time during the intermediate out of equilibrium state. === Derivation of the entropy change for reversible processes === The second part of the second law states that the entropy change of a system undergoing a reversible process is given by: d S = δ Q T {\displaystyle dS={\frac {\delta Q}{T}}} where the temperature is defined as: 1 k B T ≡ β ≡ d ln [ Ω ( E ) ] d E {\displaystyle {\frac {1}{k_{\mathrm {B} }T}}\equiv \beta \equiv {\frac {d\ln \left[\Omega \left(E\right)\right]}{dE}}} See Microcanonical ensemble for the justification for this definition. Suppose that the system has some external parameter, x, that can be changed. In general, the energy
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{
"page_id": 133017,
"source": null,
"title": "Second law of thermodynamics"
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eigenstates of the system will depend on x. According to the adiabatic theorem of quantum mechanics, in the limit of an infinitely slow change of the system's Hamiltonian, the system will stay in the same energy eigenstate and thus change its energy according to the change in energy of the energy eigenstate it is in. The generalized force, X, corresponding to the external variable x is defined such that X d x {\displaystyle Xdx} is the work performed by the system if x is increased by an amount dx. For example, if x is the volume, then X is the pressure. The generalized force for a system known to be in energy eigenstate E r {\displaystyle E_{r}} is given by: X = − d E r d x {\displaystyle X=-{\frac {dE_{r}}{dx}}} Since the system can be in any energy eigenstate within an interval of δ E {\displaystyle \delta E} , we define the generalized force for the system as the expectation value of the above expression: X = − ⟨ d E r d x ⟩ {\displaystyle X=-\left\langle {\frac {dE_{r}}{dx}}\right\rangle \,} To evaluate the average, we partition the Ω ( E ) {\displaystyle \Omega \left(E\right)} energy eigenstates by counting how many of them have a value for d E r d x {\displaystyle {\frac {dE_{r}}{dx}}} within a range between Y {\displaystyle Y} and Y + δ Y {\displaystyle Y+\delta Y} . Calling this number Ω Y ( E ) {\displaystyle \Omega _{Y}\left(E\right)} , we have: Ω ( E ) = ∑ Y Ω Y ( E ) {\displaystyle \Omega \left(E\right)=\sum _{Y}\Omega _{Y}\left(E\right)\,} The average defining the generalized force can now be written: X = − 1 Ω ( E ) ∑ Y Y Ω Y ( E ) {\displaystyle X=-{\frac {1}{\Omega \left(E\right)}}\sum _{Y}Y\Omega _{Y}\left(E\right)\,} We can relate this to the
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{
"page_id": 133017,
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"title": "Second law of thermodynamics"
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derivative of the entropy with respect to x at constant energy E as follows. Suppose we change x to x + dx. Then Ω ( E ) {\displaystyle \Omega \left(E\right)} will change because the energy eigenstates depend on x, causing energy eigenstates to move into or out of the range between E {\displaystyle E} and E + δ E {\displaystyle E+\delta E} . Let's focus again on the energy eigenstates for which d E r d x {\textstyle {\frac {dE_{r}}{dx}}} lies within the range between Y {\displaystyle Y} and Y + δ Y {\displaystyle Y+\delta Y} . Since these energy eigenstates increase in energy by Y dx, all such energy eigenstates that are in the interval ranging from E – Y dx to E move from below E to above E. There are N Y ( E ) = Ω Y ( E ) δ E Y d x {\displaystyle N_{Y}\left(E\right)={\frac {\Omega _{Y}\left(E\right)}{\delta E}}Ydx\,} such energy eigenstates. If Y d x ≤ δ E {\displaystyle Ydx\leq \delta E} , all these energy eigenstates will move into the range between E {\displaystyle E} and E + δ E {\displaystyle E+\delta E} and contribute to an increase in Ω {\displaystyle \Omega } . The number of energy eigenstates that move from below E + δ E {\displaystyle E+\delta E} to above E + δ E {\displaystyle E+\delta E} is given by N Y ( E + δ E ) {\displaystyle N_{Y}\left(E+\delta E\right)} . The difference N Y ( E ) − N Y ( E + δ E ) {\displaystyle N_{Y}\left(E\right)-N_{Y}\left(E+\delta E\right)\,} is thus the net contribution to the increase in Ω {\displaystyle \Omega } . If Y dx is larger than δ E {\displaystyle \delta E} there will be the energy eigenstates that move from below E to above E +
|
{
"page_id": 133017,
"source": null,
"title": "Second law of thermodynamics"
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δ E {\displaystyle E+\delta E} . They are counted in both N Y ( E ) {\displaystyle N_{Y}\left(E\right)} and N Y ( E + δ E ) {\displaystyle N_{Y}\left(E+\delta E\right)} , therefore the above expression is also valid in that case. Expressing the above expression as a derivative with respect to E and summing over Y yields the expression: ( ∂ Ω ∂ x ) E = − ∑ Y Y ( ∂ Ω Y ∂ E ) x = ( ∂ ( Ω X ) ∂ E ) x {\displaystyle \left({\frac {\partial \Omega }{\partial x}}\right)_{E}=-\sum _{Y}Y\left({\frac {\partial \Omega _{Y}}{\partial E}}\right)_{x}=\left({\frac {\partial \left(\Omega X\right)}{\partial E}}\right)_{x}\,} The logarithmic derivative of Ω {\displaystyle \Omega } with respect to x is thus given by: ( ∂ ln ( Ω ) ∂ x ) E = β X + ( ∂ X ∂ E ) x {\displaystyle \left({\frac {\partial \ln \left(\Omega \right)}{\partial x}}\right)_{E}=\beta X+\left({\frac {\partial X}{\partial E}}\right)_{x}\,} The first term is intensive, i.e. it does not scale with system size. In contrast, the last term scales as the inverse system size and will thus vanish in the thermodynamic limit. We have thus found that: ( ∂ S ∂ x ) E = X T {\displaystyle \left({\frac {\partial S}{\partial x}}\right)_{E}={\frac {X}{T}}\,} Combining this with ( ∂ S ∂ E ) x = 1 T {\displaystyle \left({\frac {\partial S}{\partial E}}\right)_{x}={\frac {1}{T}}\,} gives: d S = ( ∂ S ∂ E ) x d E + ( ∂ S ∂ x ) E d x = d E T + X T d x = δ Q T {\displaystyle dS=\left({\frac {\partial S}{\partial E}}\right)_{x}dE+\left({\frac {\partial S}{\partial x}}\right)_{E}dx={\frac {dE}{T}}+{\frac {X}{T}}dx={\frac {\delta Q}{T}}\,} === Derivation for systems described by the canonical ensemble === If a system is in thermal contact with a heat bath at some temperature T then,
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"page_id": 133017,
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"title": "Second law of thermodynamics"
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in equilibrium, the probability distribution over the energy eigenvalues are given by the canonical ensemble: P j = exp ( − E j k B T ) Z {\displaystyle P_{j}={\frac {\exp \left(-{\frac {E_{j}}{k_{\mathrm {B} }T}}\right)}{Z}}} Here Z is a factor that normalizes the sum of all the probabilities to 1, this function is known as the partition function. We now consider an infinitesimal reversible change in the temperature and in the external parameters on which the energy levels depend. It follows from the general formula for the entropy: S = − k B ∑ j P j ln ( P j ) {\displaystyle S=-k_{\mathrm {B} }\sum _{j}P_{j}\ln \left(P_{j}\right)} that d S = − k B ∑ j ln ( P j ) d P j {\displaystyle dS=-k_{\mathrm {B} }\sum _{j}\ln \left(P_{j}\right)dP_{j}} Inserting the formula for P j {\displaystyle P_{j}} for the canonical ensemble in here gives: d S = 1 T ∑ j E j d P j = 1 T ∑ j d ( E j P j ) − 1 T ∑ j P j d E j = d E + δ W T = δ Q T {\displaystyle dS={\frac {1}{T}}\sum _{j}E_{j}dP_{j}={\frac {1}{T}}\sum _{j}d\left(E_{j}P_{j}\right)-{\frac {1}{T}}\sum _{j}P_{j}dE_{j}={\frac {dE+\delta W}{T}}={\frac {\delta Q}{T}}} === Initial conditions at the Big Bang === As elaborated above, it is thought that the second law of thermodynamics is a result of the very low-entropy initial conditions at the Big Bang. From a statistical point of view, these were very special conditions. On the other hand, they were quite simple, as the universe - or at least the part thereof from which the observable universe developed - seems to have been extremely uniform. This may seem somewhat paradoxical, since in many physical systems uniform conditions (e.g. mixed rather than separated gases) have
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{
"page_id": 133017,
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"title": "Second law of thermodynamics"
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high entropy. The paradox is solved once realizing that gravitational systems have negative heat capacity, so that when gravity is important, uniform conditions (e.g. gas of uniform density) in fact have lower entropy compared to non-uniform ones (e.g. black holes in empty space). Yet another approach is that the universe had high (or even maximal) entropy given its size, but as the universe grew it rapidly came out of thermodynamic equilibrium, its entropy only slightly increased compared to the increase in maximal possible entropy, and thus it has arrived at a very low entropy when compared to the much larger possible maximum given its later size. As for the reason why initial conditions were such, one suggestion is that cosmological inflation was enough to wipe off non-smoothness, while another is that the universe was created spontaneously where the mechanism of creation implies low-entropy initial conditions. == Living organisms == There are two principal ways of formulating thermodynamics, (a) through passages from one state of thermodynamic equilibrium to another, and (b) through cyclic processes, by which the system is left unchanged, while the total entropy of the surroundings is increased. These two ways help to understand the processes of life. The thermodynamics of living organisms has been considered by many authors, including Erwin Schrödinger (in his book What is Life?) and Léon Brillouin. To a fair approximation, living organisms may be considered as examples of (b). Approximately, an animal's physical state cycles by the day, leaving the animal nearly unchanged. Animals take in food, water, and oxygen, and, as a result of metabolism, give out breakdown products and heat. Plants take in radiative energy from the sun, which may be regarded as heat, and carbon dioxide and water. They give out oxygen. In this way they grow. Eventually they die, and
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"page_id": 133017,
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their remains rot away, turning mostly back into carbon dioxide and water. This can be regarded as a cyclic process. Overall, the sunlight is from a high temperature source, the sun, and its energy is passed to a lower temperature sink, i.e. radiated into space. This is an increase of entropy of the surroundings of the plant. Thus animals and plants obey the second law of thermodynamics, considered in terms of cyclic processes. Furthermore, the ability of living organisms to grow and increase in complexity, as well as to form correlations with their environment in the form of adaption and memory, is not opposed to the second law – rather, it is akin to general results following from it: Under some definitions, an increase in entropy also results in an increase in complexity, and for a finite system interacting with finite reservoirs, an increase in entropy is equivalent to an increase in correlations between the system and the reservoirs. Living organisms may be considered as open systems, because matter passes into and out from them. Thermodynamics of open systems is currently often considered in terms of passages from one state of thermodynamic equilibrium to another, or in terms of flows in the approximation of local thermodynamic equilibrium. The problem for living organisms may be further simplified by the approximation of assuming a steady state with unchanging flows. General principles of entropy production for such approximations are a subject of ongoing research. == Gravitational systems == Commonly, systems for which gravity is not important have a positive heat capacity, meaning that their temperature rises with their internal energy. Therefore, when energy flows from a high-temperature object to a low-temperature object, the source temperature decreases while the sink temperature is increased; hence temperature differences tend to diminish over time. This is not
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"page_id": 133017,
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always the case for systems in which the gravitational force is important: systems that are bound by their own gravity, such as stars, can have negative heat capacities. As they contract, both their total energy and their entropy decrease but their internal temperature may increase. This can be significant for protostars and even gas giant planets such as Jupiter. When the entropy of the black-body radiation emitted by the bodies is included, however, the total entropy of the system can be shown to increase even as the entropy of the planet or star decreases. == Non-equilibrium states == The theory of classical or equilibrium thermodynamics is idealized. A main postulate or assumption, often not even explicitly stated, is the existence of systems in their own internal states of thermodynamic equilibrium. In general, a region of space containing a physical system at a given time, that may be found in nature, is not in thermodynamic equilibrium, read in the most stringent terms. In looser terms, nothing in the entire universe is or has ever been truly in exact thermodynamic equilibrium. For purposes of physical analysis, it is often enough convenient to make an assumption of thermodynamic equilibrium. Such an assumption may rely on trial and error for its justification. If the assumption is justified, it can often be very valuable and useful because it makes available the theory of thermodynamics. Elements of the equilibrium assumption are that a system is observed to be unchanging over an indefinitely long time, and that there are so many particles in a system, that its particulate nature can be entirely ignored. Under such an equilibrium assumption, in general, there are no macroscopically detectable fluctuations. There is an exception, the case of critical states, which exhibit to the naked eye the phenomenon of critical opalescence. For
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"page_id": 133017,
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laboratory studies of critical states, exceptionally long observation times are needed. In all cases, the assumption of thermodynamic equilibrium, once made, implies as a consequence that no putative candidate "fluctuation" alters the entropy of the system. It can easily happen that a physical system exhibits internal macroscopic changes that are fast enough to invalidate the assumption of the constancy of the entropy. Or that a physical system has so few particles that the particulate nature is manifest in observable fluctuations. Then the assumption of thermodynamic equilibrium is to be abandoned. There is no unqualified general definition of entropy for non-equilibrium states. There are intermediate cases, in which the assumption of local thermodynamic equilibrium is a very good approximation, but strictly speaking it is still an approximation, not theoretically ideal. For non-equilibrium situations in general, it may be useful to consider statistical mechanical definitions of other quantities that may be conveniently called 'entropy', but they should not be confused or conflated with thermodynamic entropy properly defined for the second law. These other quantities indeed belong to statistical mechanics, not to thermodynamics, the primary realm of the second law. The physics of macroscopically observable fluctuations is beyond the scope of this article. == Arrow of time == The second law of thermodynamics is a physical law that is not symmetric to reversal of the time direction. This does not conflict with symmetries observed in the fundamental laws of physics (particularly CPT symmetry) since the second law applies statistically on time-asymmetric boundary conditions. The second law has been related to the difference between moving forwards and backwards in time, or to the principle that cause precedes effect (the causal arrow of time, or causality). == Irreversibility == Irreversibility in thermodynamic processes is a consequence of the asymmetric character of thermodynamic operations, and not
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"page_id": 133017,
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of any internally irreversible microscopic properties of the bodies. Thermodynamic operations are macroscopic external interventions imposed on the participating bodies, not derived from their internal properties. There are reputed "paradoxes" that arise from failure to recognize this. === Loschmidt's paradox === Loschmidt's paradox, also known as the reversibility paradox, is the objection that it should not be possible to deduce an irreversible process from the time-symmetric dynamics that describe the microscopic evolution of a macroscopic system. In the opinion of Schrödinger, "It is now quite obvious in what manner you have to reformulate the law of entropy – or for that matter, all other irreversible statements – so that they be capable of being derived from reversible models. You must not speak of one isolated system but at least of two, which you may for the moment consider isolated from the rest of the world, but not always from each other." The two systems are isolated from each other by the wall, until it is removed by the thermodynamic operation, as envisaged by the law. The thermodynamic operation is externally imposed, not subject to the reversible microscopic dynamical laws that govern the constituents of the systems. It is the cause of the irreversibility. The statement of the law in this present article complies with Schrödinger's advice. The cause–effect relation is logically prior to the second law, not derived from it. This reaffirms Albert Einstein's postulates that cornerstone Special and General Relativity - that the flow of time is irreversible, however it is relative. Cause must precede effect, but only within the constraints as defined explicitly within General Relativity (or Special Relativity, depending on the local spacetime conditions). Good examples of this are the Ladder Paradox, time dilation and length contraction exhibited by objects approaching the velocity of light or within
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"page_id": 133017,
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proximity of a super-dense region of mass/energy - e.g. black holes, neutron stars, magnetars and quasars. === Poincaré recurrence theorem === The Poincaré recurrence theorem considers a theoretical microscopic description of an isolated physical system. This may be considered as a model of a thermodynamic system after a thermodynamic operation has removed an internal wall. The system will, after a sufficiently long time, return to a microscopically defined state very close to the initial one. The Poincaré recurrence time is the length of time elapsed until the return. It is exceedingly long, likely longer than the life of the universe, and depends sensitively on the geometry of the wall that was removed by the thermodynamic operation. The recurrence theorem may be perceived as apparently contradicting the second law of thermodynamics. More obviously, however, it is simply a microscopic model of thermodynamic equilibrium in an isolated system formed by removal of a wall between two systems. For a typical thermodynamical system, the recurrence time is so large (many many times longer than the lifetime of the universe) that, for all practical purposes, one cannot observe the recurrence. One might wish, nevertheless, to imagine that one could wait for the Poincaré recurrence, and then re-insert the wall that was removed by the thermodynamic operation. It is then evident that the appearance of irreversibility is due to the utter unpredictability of the Poincaré recurrence given only that the initial state was one of thermodynamic equilibrium, as is the case in macroscopic thermodynamics. Even if one could wait for it, one has no practical possibility of picking the right instant at which to re-insert the wall. The Poincaré recurrence theorem provides a solution to Loschmidt's paradox. If an isolated thermodynamic system could be monitored over increasingly many multiples of the average Poincaré recurrence time,
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the thermodynamic behavior of the system would become invariant under time reversal. === Maxwell's demon === James Clerk Maxwell imagined one container divided into two parts, A and B. Both parts are filled with the same gas at equal temperatures and placed next to each other, separated by a wall. Observing the molecules on both sides, an imaginary demon guards a microscopic trapdoor in the wall. When a faster-than-average molecule from A flies towards the trapdoor, the demon opens it, and the molecule will fly from A to B. The average speed of the molecules in B will have increased while in A they will have slowed down on average. Since average molecular speed corresponds to temperature, the temperature decreases in A and increases in B, contrary to the second law of thermodynamics. One response to this question was suggested in 1929 by Leó Szilárd and later by Léon Brillouin. Szilárd pointed out that a real-life Maxwell's demon would need to have some means of measuring molecular speed, and that the act of acquiring information would require an expenditure of energy. Likewise, Brillouin demonstrated that the decrease in entropy caused by the demon would be less than the entropy produced by choosing molecules based on their speed. Maxwell's 'demon' repeatedly alters the permeability of the wall between A and B. It is therefore performing thermodynamic operations on a microscopic scale, not just observing ordinary spontaneous or natural macroscopic thermodynamic processes. == Quotations == The law that entropy always increases holds, I think, the supreme position among the laws of Nature. If someone points out to you that your pet theory of the universe is in disagreement with Maxwell's equations – then so much the worse for Maxwell's equations. If it is found to be contradicted by observation – well, these
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experimentalists do bungle things sometimes. But if your theory is found to be against the second law of thermodynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation. There have been nearly as many formulations of the second law as there have been discussions of it. Clausius is the author of the sibyllic utterance, "The energy of the universe is constant; the entropy of the universe tends to a maximum." The objectives of continuum thermomechanics stop far short of explaining the "universe", but within that theory we may easily derive an explicit statement in some ways reminiscent of Clausius, but referring only to a modest object: an isolated body of finite size. == See also == == References == === Sources === == Further reading == Goldstein, Martin, and Inge F., 1993. The Refrigerator and the Universe. Harvard Univ. Press. Chpts. 4–9 contain an introduction to the second law, one a bit less technical than this entry. ISBN 978-0-674-75324-2 Leff, Harvey S., and Rex, Andrew F. (eds.) 2003. Maxwell's Demon 2 : Entropy, classical and quantum information, computing. Bristol UK; Philadelphia PA: Institute of Physics. ISBN 978-0-585-49237-7 Halliwell, J.J. (1994). Physical Origins of Time Asymmetry. Cambridge. ISBN 978-0-521-56837-1.(technical). Carnot, Sadi (1890). Thurston, Robert Henry (ed.). Reflections on the Motive Power of Heat and on Machines Fitted to Develop That Power. New York: J. Wiley & Sons. (full text of 1897 ed.) (html Archived 2007-08-18 at the Wayback Machine) Stephen Jay Kline (1999). The Low-Down on Entropy and Interpretive Thermodynamics, La Cañada, CA: DCW Industries. ISBN 1-928729-01-0. Kostic, M (2011). Revisiting The Second Law of Energy Degradation and Entropy Generation: From Sadi Carnot's Ingenious Reasoning to Holistic Generalization. AIP Conference Proceedings. Vol. 1411. pp. 327–350. Bibcode:2011AIPC.1411..327K. CiteSeerX 10.1.1.405.1945. doi:10.1063/1.3665247. ISBN 978-0-7354-0985-9. {{cite book}}:
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|journal= ignored (help) also at [1]. == External links == Stanford Encyclopedia of Philosophy: "Philosophy of Statistical Mechanics" – by Lawrence Sklar. Second law of thermodynamics in the MIT Course Unified Thermodynamics and Propulsion from Prof. Z. S. Spakovszky E.T. Jaynes, 1988, "The evolution of Carnot's principle," in G. J. Erickson and C. R. Smith (eds.)Maximum-Entropy and Bayesian Methods in Science and Engineering, Vol,.1: p. 267. Caratheodory, C., "Examination of the foundations of thermodynamics," trans. by D. H. Delphenich The second law of Thermodynamics, BBC Radio 4 discussion with John Gribbin, Peter Atkins & Monica Grady (In Our Time, December 16, 2004) The Journal of the International Society for the History of Philosophy of Science, 2012
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Molecule mining is the process of data mining, or extracting and discovering patterns, as applied to molecules. Since molecules may be represented by molecular graphs, this is strongly related to graph mining and structured data mining. The main problem is how to represent molecules while discriminating the data instances. One way to do this is chemical similarity metrics, which has a long tradition in the field of cheminformatics. Typical approaches to calculate chemical similarities use chemical fingerprints, but this loses the underlying information about the molecule topology. Mining the molecular graphs directly avoids this problem. So does the inverse QSAR problem which is preferable for vectorial mappings. == Coding(Moleculei,Moleculej≠i) == === Kernel methods === Marginalized graph kernel Optimal assignment kernel Pharmacophore kernel C++ (and R) implementation combining the marginalized graph kernel between labeled graphs extensions of the marginalized kernel Tanimoto kernels graph kernels based on tree patterns kernels based on pharmacophores for 3D structure of molecules === Maximum common graph methods === MCS-HSCS (Highest Scoring Common Substructure (HSCS) ranking strategy for single MCS) Small Molecule Subgraph Detector (SMSD)- is a Java-based software library for calculating Maximum Common Subgraph (MCS) between small molecules. This will help us to find similarity/distance between two molecules. MCS is also used for screening drug like compounds by hitting molecules, which share common subgraph (substructure). == Coding(Moleculei) == === Molecular query methods === Warmr AGM PolyFARM FSG MolFea MoFa/MoSS Gaston LAZAR ParMol (contains MoFa, FFSM, gSpan, and Gaston) optimized gSpan SMIREP DMax SAm/AIm/RHC AFGen gRed G-Hash === Methods based on special architectures of neural networks === BPZ ChemNet CCS MolNet Graph machines == See also == Molecular Query Language Chemical graph theory Chemical space QSAR ADME partition coefficient == References == === Further reading === Schölkopf, B., K. Tsuda and J. P. Vert: Kernel Methods in
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"page_id": 4851611,
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}
|
Computational Biology, MIT Press, Cambridge, MA, 2004. R.O. Duda, P.E. Hart, D.G. Stork, Pattern Classification, John Wiley & Sons, 2001. ISBN 0-471-05669-3 Gusfield, D., Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, Cambridge University Press, 1997. ISBN 0-521-58519-8 R. Todeschini, V. Consonni, Handbook of Molecular Descriptors, Wiley-VCH, 2000. ISBN 3-527-29913-0 == External links == Small Molecule Subgraph Detector (SMSD) - is a Java-based software library for calculating Maximum Common Subgraph (MCS) between small molecules. 5th International Workshop on Mining and Learning with Graphs, 2007 Overview for 2006 Molecule mining (basic chemical expert systems) ParMol and master thesis documentation - Java - Open source - Distributed mining - Benchmark algorithm library TU München - Kramer group Molecule mining (advanced chemical expert systems) DMax Chemistry Assistant - commercial software AFGen - Software for generating fragment-based descriptors
|
{
"page_id": 4851611,
"source": null,
"title": "Molecule mining"
}
|
Information causality is a physical principle suggested in 2009. Information causality states that the information gain a receiver (Bob) can reach about data, previously unknown to him, from a sender (Alice), by using all his local resources and n {\displaystyle n} classical bits communicated by the sender, is at most n {\displaystyle n} bits; and that this limitation should hold even in the case where Alice and Bob pre-share a physical non-signaling resource, such as an entangled quantum state. The principle assumes classical communication: if quantum bits were allowed to be transmitted, the information gain could be higher (for example if Alice and Bob pre-share some entangled qubits) as demonstrated in the quantum superdense coding protocol. The principle is respected by all correlations accessible with quantum physics, while it excludes all correlations which violate the quantum Tsirelson bound for the CHSH inequality. However, it does not exclude beyond-quantum correlations in multipartite situations. The principle has also been related to a principle called thermodynamic sufficiency. == See also == Tsirelson's bound Quantum nonlocality == References ==
|
{
"page_id": 43714458,
"source": null,
"title": "Information causality"
}
|
Pregnancy vegetarianism is the practice of adhering to a vegetarian diet during pregnancy. Vegetarianism is "the principle or practice of excluding all meat and fish, and sometimes, in the case of vegans, all animal products (such as eggs, milk, cheese, etc) from one's diet." Although some people frown upon pregnant women practicing vegetarianism, there is no evidence that vegetarianism—practiced properly—is unhealthful during pregnancy. There are millions of healthy babies born each year from vegetarian households. == Protein consumption == Most opponents of pregnancy vegetarianism are concerned about the pregnant woman's protein intake because vegetarians do not eat chicken, fish, or beef. It is recommended, for example, that a pregnant woman should aim to have something from the four main food groups every day. These include fruit and vegetables, carbohydrates, protein-rich foods and dairy foods. There are several vegetarian sources of protein: soy, cooked dried beans or peas, tofu, nuts or seeds, peanut butter, and eggs. Vegetarians focus on foods that are normally left out of most non-meat pregnancy diets such as include beans, fresh dark green vegetables, and whole grains which are good sources of protein. The risks associated with vegetarianism, that is to say the problems vegetarians face, can generally be lessened by a careful diet. These problems that many associate with vegetarianism, such as anaemia, are in fact not due to the vegetarian diet alone, but more so to the fact that the subject in question has failed to supplement their body with the nutrition they require. When cutting out meats, some vegetarians fail to intake any other kinds of protein. To intake protein is very important during pregnancy as one of the cause of the anaemia is iron deficiency and it varies by region. The iron-deficiency anaemia increases the risk of low weight in birth and transmits
|
{
"page_id": 42665887,
"source": null,
"title": "Pregnancy vegetarianism"
}
|
the iron-deficiency to infants. == Effect on weight gain == One benefit of adopting pregnancy vegetarianism, is the possibility of minimizing pregnancy weight gain. Because being a vegetarian is a choice less often chosen, many have described this control of weight as due to them being more conscious of their diet. A 2009 study showed that over 52 percent of pregnant women gain more weight than the recommended, 23-35 pounds. During the second and third trimester, the average diet needs only to be increased by 300 calories, and it may be argued that pregnancy vegetarianism may be a way of monitoring diet and calorie intake. == Nutrients needed == According to dietitian Sarah Schenker, being a vegetarian during pregnancy is perfectly safe so long as a strict diet is being followed. By this she means that one must know exactly what their body needs and make sure that they are taking in these nutrients. A healthy diet is very important when pregnant as a vegetarian. Seeing a dietitian could be beneficial to one as they could provide guidelines which should be followed for a healthy lifestyle. Pregnant woman should get enough omega-3s, vitamin B12, and calcium. All these elements could be found in vegetarian meals and products. Omega-3s are found in dark leafy green vegetables, flax seed, walnuts, kidney and pinto beans, broccoli and squash. Calcium is found in cottage cheese and fortified plant-based drinks. Moreover, pregnant woman should get enough zinc, protein, and iron. These elements are found in peas and beans. Vegetables and fruits should be eaten every day more than five times in order to get enough vitamins. However, as vegetarians have a greater exposure to phytoestrogens than omnivores, there are studies which support the possibility of negative effect on the developing male reproductive system and can
|
{
"page_id": 42665887,
"source": null,
"title": "Pregnancy vegetarianism"
}
|
increase the risk of the baby developing birth defects such as hypospadias. == References ==
|
{
"page_id": 42665887,
"source": null,
"title": "Pregnancy vegetarianism"
}
|
In electrochemistry, a valve metal is a metal which passes current in only one direction. Usually, in an electrolytic cell, it can function generally as a cathode, but not generally as an anode because a (highly resistive) oxide of the metal forms under anodic conditions. Valve metals include commonly aluminium, titanium, tantalum, and niobium. Other metals may also be considered as valve metals, such as tungsten, chromium, zirconium, hafnium, zinc, vanadium, bismuth or antimony. == References ==
|
{
"page_id": 67635106,
"source": null,
"title": "Valve metals"
}
|
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Scikit-learn is a NumFOCUS fiscally sponsored project. == Overview == The scikit-learn project started as scikits.learn, a Google Summer of Code project by French data scientist David Cournapeau. The name of the project derives from its role as a "scientific toolkit for machine learning", originally developed and distributed as a third-party extension to SciPy. The original codebase was later rewritten by other developers. In 2010, contributors Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort and Vincent Michel, from the French Institute for Research in Computer Science and Automation in Saclay, France, took leadership of the project and released the first public version of the library on February 1, 2010. In November 2012, scikit-learn as well as scikit-image were described as two of the "well-maintained and popular" scikits libraries. In 2019, it was noted that scikit-learn is one of the most popular machine learning libraries on GitHub. == Features == Large catalogue of well-established machine learning algorithms and data pre-processing methods (i.e. feature engineering) Utility methods for common data-science tasks, such as splitting data into train and test sets, cross-validation and grid search Consistent way of running machine learning models (estimator.fit() and estimator.predict()), which libraries can implement Declarative way of structuring a data science process (the Pipeline), including data pre-processing and model fitting == Examples == Fitting a random forest classifier: == Implementation == scikit-learn is largely written in Python, and uses NumPy extensively for high-performance linear algebra and array operations. Furthermore, some core algorithms are written in Cython
|
{
"page_id": 33490859,
"source": null,
"title": "Scikit-learn"
}
|
to improve performance. Support vector machines are implemented by a Cython wrapper around LIBSVM; logistic regression and linear support vector machines by a similar wrapper around LIBLINEAR. In such cases, extending these methods with Python may not be possible. scikit-learn integrates well with many other Python libraries, such as Matplotlib and plotly for plotting, NumPy for array vectorization, Pandas dataframes, SciPy, and many more. == Version history == scikit-learn was initially developed by David Cournapeau as a Google Summer of Code project in 2007. Later that year, Matthieu Brucher joined the project and started to use it as a part of his thesis work. In 2010, INRIA, the French Institute for Research in Computer Science and Automation, got involved and the first public release (v0.1 beta) was published in late January 2010. August 2013. scikit-learn 0.14 July 2014. scikit-learn 0.15.0 March 2015. scikit-learn 0.16.0 November 2015. scikit-learn 0.17.0 September 2016. scikit-learn 0.18.0 July 2017. scikit-learn 0.19.0 September 2018. scikit-learn 0.20.0 May 2019. scikit-learn 0.21.0 December 2019. scikit-learn 0.22 May 2020. scikit-learn 0.23.0 Jan 2021. scikit-learn 0.24 September 2021. scikit-learn 1.0.0 October 2021. scikit-learn 1.0.1 December 2021. scikit-learn 1.0.2 May 2022. scikit-learn 1.1.0 May 2022. scikit-learn 1.1.1 August 2022. scikit-learn 1.1.2 October 2022. scikit-learn 1.1.3 December 2022. scikit-learn 1.2.0 January 2023. scikit-learn 1.2.1 March 2023. scikit-learn 1.2.2 == Awards == 2019 Inria-French Academy of Sciences-Dassault Systèmes Innovation Prize 2022 Open Science Award for Open Source Research Software == scikit-learn alternatives == mlpy SpaCy NLTK Orange PyTorch TensorFlow JAX Infer.NET List of numerical analysis software == References == == External links == Official website scikit-learn on GitHub
|
{
"page_id": 33490859,
"source": null,
"title": "Scikit-learn"
}
|
Cell physiology is the biological study of the activities that take place in a cell to keep it alive. The term physiology refers to normal functions in a living organism. Animal cells, plant cells and microorganism cells show similarities in their functions even though they vary in structure. == General characteristics == There are two types of cells: prokaryotes and eukaryotes. Prokaryotes were the first of the two to develop and do not have a self-contained nucleus. Their mechanisms are simpler than later-evolved eukaryotes, which contain a nucleus that envelops the cell's DNA and some organelles. === Prokaryotes === Prokaryotes have DNA located in an area called the nucleoid, which is not separated from other parts of the cell by a membrane. There are two domains of prokaryotes: bacteria and archaea. Prokaryotes have fewer organelles than eukaryotes. Both have plasma membranes and ribosomes (structures that synthesize proteins and float free in cytoplasm). Two unique characteristics of prokaryotes are fimbriae (finger-like projections on the surface of a cell) and flagella (threadlike structures that aid movement). === Eukaryotes === Eukaryotes have a nucleus where DNA is contained. They are usually larger than prokaryotes and contain many more organelles. The nucleus, the feature of a eukaryote that distinguishes it from a prokaryote, contains a nuclear envelope, nucleolus and chromatin. In cytoplasm, endoplasmic reticulum (ER) synthesizes membranes and performs other metabolic activities. There are two types, rough ER (containing ribosomes) and smooth ER (lacking ribosomes). The Golgi apparatus consists of multiple membranous sacs, responsible for manufacturing and shipping out materials such as proteins. Lysosomes are structures that use enzymes to break down substances through phagocytosis, a process that comprises endocytosis and exocytosis. In the mitochondria, metabolic processes such as cellular respiration occur. The cytoskeleton is made of fibers that support the structure of the
|
{
"page_id": 6227883,
"source": null,
"title": "Cell physiology"
}
|
cell and help the cell move. == Physiological processes == There are different ways through which cells can transport substances across the cell membrane. The two main pathways are passive transport and active transport. Passive transport is more direct and does not require the use of the cell's energy. It relies on an area that maintains a high-to-low concentration gradient. Active transport uses adenosine triphosphate (ATP) to transport a substance that moves against its concentration gradient. === Movement of proteins === The pathway for proteins to move in cells starts at the ER. Lipids and proteins are synthesized in the ER, and carbohydrates are added to make glycoproteins. Glycoproteins undergo further synthesis in the Golgi apparatus, becoming glycolipids. Both glycoproteins and glycolipids are transported into vesicles to the plasma membrane. The cell releases secretory proteins known as exocytosis. === Transport of ions === Ions travel across cell membranes through channels, pumps or transporters. In channels, they move down an electrochemical gradient to produce electrical signals. Pumps maintain electrochemical gradients. The main type of pump is the Na/K pump. It moves 3 sodium ions out of a cell and 2 potassium ions into a cell. The process converts one ATP molecule to adenosine diphosphate (ADP) and Phosphate. In a transporter, ions use more than one gradient to produce electrical signals. === Endocytosis in animal cells === Endocytosis is a form of active transport where a cell takes in molecules, using the plasma membrane, and packages them into vesicles.: 139–140 === Phagocytosis === In phagocytosis, a cell surrounds particles including food particles through an extension of the pseudopods, which are located on the plasma membrane. The pseudopods then package the particles in a food vacuole. The lysosome, which contains hydrolytic enzymes, then fuses with the food vacuole. Hydrolytic enzymes, also known as
|
{
"page_id": 6227883,
"source": null,
"title": "Cell physiology"
}
|
digestive enzymes, then digest the particles within the food vacuole.: 139–140 === Pinocytosis === In pinocytosis, a cell takes in ("gulps") extracellular fluid into vesicles, which are formed when plasma membrane surrounds the fluid. The cell can take in any molecule or solute through this process.: 139–140 === Receptor-mediated endocytosis === Receptor-mediated endocytosis is a form of pinocytosis where a cell takes in specific molecules or solutes. Proteins with receptor sites are located on the plasma membrane, binding to specific solutes. The receptor proteins that are attached to the specific solutes go inside coated pits, forming a vesicle. The vesicles then surround the receptors that are attached to the specific solutes, releasing their molecules. Receptor proteins are recycled back to the plasma membrane by the same vesicle.: 139–140 == References == == External links == Overview at Medical College of Georgia (archived) Cell Physiological Phenomena at the U.S. National Library of Medicine Medical Subject Headings (MeSH) Electrophysiology at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
|
{
"page_id": 6227883,
"source": null,
"title": "Cell physiology"
}
|
Restriction sites, or restriction recognition sites, are located on a DNA molecule containing specific (4-8 base pairs in length) sequences of nucleotides, which are recognized by restriction enzymes. These are generally palindromic sequences (because restriction enzymes usually bind as homodimers), and a particular restriction enzyme may cut the sequence between two nucleotides within its recognition site, or somewhere nearby. == Function == For example, the common restriction enzyme EcoRI recognizes the palindromic sequence GAATTC and cuts between the G and the A on both the top and bottom strands. This leaves an overhang (an end-portion of a DNA strand with no attached complement) known as a sticky end on each end of AATT. The overhang can then be used to ligate in (see DNA ligase) a piece of DNA with a complementary overhang (another EcoRI-cut piece, for example). Some restriction enzymes cut DNA at a restriction site in a manner which leaves no overhang, called a blunt end. Blunt ends are much less likely to be ligated by a DNA ligase because the blunt end doesn't have the overhanging base pair that the enzyme can recognize and match with a complementary pair. Sticky ends of DNA however are more likely to successfully bind with the help of a DNA ligase because of the exposed and unpaired nucleotides. For example, a sticky end trailing with AATTG is more likely to bind with a ligase than a blunt end where both the 5' and 3' DNA strands are paired. In the case of the example the AATTG would have a complementary pair of TTAAC which would reduce the functionality of the DNA ligase enzyme. == Applications == Restriction sites can be used for multiple applications in molecular biology such as identifying restriction fragment length polymorphisms (RFLPs). Restriction sites are also important consideration
|
{
"page_id": 2492332,
"source": null,
"title": "Restriction site"
}
|
to be aware of when designing plasmids. == Databases == Several databases exist for restriction sites and enzymes, of which the largest noncommercial database is REBASE. Recently, it has been shown that statistically significant nullomers (i.e. short absent motifs which are highly expected to exist) in virus genomes are restriction sites indicating that viruses have probably got rid of these motifs to facilitate invasion of bacterial hosts. Nullomers Database contains a comprehensive catalogue of minimal absent motifs many of which might potentially be not-yet-known restriction motifs. == See also == List of restriction enzyme cutting sites == References ==
|
{
"page_id": 2492332,
"source": null,
"title": "Restriction site"
}
|
Ants are simple animals and their behavioural repertory is limited to somewhere between ten and forty elementary behaviours. This is an attempt to explain the different patterns of self-organization in ants. == Ants as complex systems == Ant colonies are self-organized systems: complex collective behaviors arise as the product of interactions between many individuals each following a simple set of rules, not via top-down instruction from elite individuals or the queen. No one worker has universal knowledge of the colony's needs; individual workers react only to their local environment. Because of this, ants are a popular source of inspiration for design in software engineering, robotics, industrial design, and other fields involving many simple parts working together to perform complex tasks. The most popular current model of self-organization in ants and other social insects is the response threshold model. A threshold for a particular task is the amount of stimulus, such as a pheromone or interactions with other workers, necessary to cause the worker to perform the associated task. A higher threshold requires a stronger stimulus, and thus translates into less preference for performing a specific task. Different workers have different thresholds for different tasks, allowing certain workers to function as specialists that preferentially perform one or more tasks. Threshold levels can be affected by several factors: worker age, since workers frequently switch from within-nest work to outside-nest work with age; size, since larger workers often perform different tasks, such as defense or seed processing; caste; health, since injuries can encourage young workers to switch to outside-nest work earlier; or be randomly distributed. As demand for a task increases, so does the proportion of workers whose thresholds are met; as demand decreases, fewer workers' thresholds are met and fewer workers are allocated to that task. In this way, simple individual rules
|
{
"page_id": 17303474,
"source": null,
"title": "Patterns of self-organization in ants"
}
|
allow for the regulation of work on a large scale in diverse settings. This system can also evolve in response to different environments and life history strategies, leading to the immense variation observed in ants. == Bifurcation == This is an instant transition of the whole system to a new stable pattern when a threshold is reached. Bifurcation is also known as multi-stability in which many stable states are possible. Examples of pattern types: Transition between disordered and ordered pattern Transition from an even use of many food sources to one source. Formation of branched nest galleries. Group preference of one exit by escaping ants. Chain formation of mutual leg grasping. == Synchronization == Oscillating patterns of activity in which individuals at different activity levels stimulate one another emerging from mutual activation. Examples of pattern types: Short scale rhythms arising from mechanical activation from physical contact. Long scale rhythms in which temporal changes in food needs and larvae stimulate changes in the reproductive cycle. == Self-organized waves == Traveling waves of chemical concentration or mechanical deformation. Examples of pattern types: Alarm waves propagated by physical contact. Rotating trails from spatial changes in food resources acting on trail laying activity. == Self-organized criticality == Self-organized criticality is an abrupt disturbance in a system resulting from a buildup of events without external stimuli. Examples of pattern types: Abrupt changes in feeding activity. Mechanical grasping of legs forming ant droplets. == References ==
|
{
"page_id": 17303474,
"source": null,
"title": "Patterns of self-organization in ants"
}
|
The Non-Proliferation Trust (NPT) is a U.S. nonprofit organization that, at the beginning of the 21st century, advocated storing 10,000 tons of U.S. nuclear waste in Russia for a fee of $15 billion paid to the Russian government and $250 million paid to a fund for Russian orphans. The group was headed by Admiral Daniel Murphy. This proposal was endorsed by the Russian atomic energy ministry, MinAtom, which estimated that the proposal could eventually generate $150 billion in revenue for Russia. == See also == Halter Marine Federal Agency on Atomic Energy (Russia) == References ==
|
{
"page_id": 198579,
"source": null,
"title": "Non-Proliferation Trust"
}
|
Bjørg Cyvin (born 1932 - died 2015 at age 82) is a Norwegian chemist and researcher. == Early life == Bjorg Cvyvin (born Nygaard) was born February 8, 1932, in Alesund, Norway. Her father, Johannes Nygaard and her mother Ovidia Nygaard were married at Ålesund parish. She had an older brother named Harald Nygaard who was born in 1928 == Education and work == Bjørg Nygaard earned her diploma as a civil engineer in 1956 at the Department of Industrial Chemistry at the Norwegian Institute of Technology (NTH) in Trondheim. The following year, she was employed as a researcher at the institute's Department of Industrial Chemistry. There she collaborated with, among others, the institute's founder and head, Olav Notevarp, on research into the connection between fatty acids in the diet and occurrences of arteriosclerosis and cardiovascular diseases. Among other things, they determined the importance of a diet rich in polyunsaturated fat. In 1958 or 1959, she married the chemist Sven Josef Cyvin (1931–2013), and took his surname. They had one child, Helge Lie (1955-2015). The married couple were also research colleagues. Together with her husband and fellow researcher, she received the Fridtjof Nansen Prize for Outstanding Research in 1995. She has been widely published, often in collaboration with her husband. Some of her published work includes a book on Coronoid Hydrocarbons which she wrote with her husband Sven Josef Cyvin and another researcher named Jon Brunvoll. She has 222 research publications while she was associated with Xiamen University and other places. Many were in collaboration with her husband and other researchers. == References ==
|
{
"page_id": 74909622,
"source": null,
"title": "Bjørg Cyvin"
}
|
An electron-withdrawing group (EWG) is a group or atom that has the ability to draw electron density toward itself and away from other adjacent atoms. This electron density transfer is often achieved by resonance or inductive effects. Electron-withdrawing groups have significant impacts on fundamental chemical processes such as acid-base reactions, redox potentials, and substitution reactions. == Consequences of EWGs == === Effects on Brønsted–Lowry acidity === Electron-withdrawing groups exert an "inductive" or "electron-pulling" effect on covalent bonds. The strength of the electron-withdrawing group is inversely proportional to the pKa of the carboxylic acid. The inductive effect is cumulative: trichloroacetic acid is 1000× stronger than chloroacetic acid. The impact of the EWG on pKa decreases with distances from the carboxylic group. For benzoic acids, the effect is quantified by the Hammett equation: log K K 0 = σ ρ {\displaystyle \log {\frac {K}{K_{0}}}=\sigma \rho } where K 0 {\displaystyle {K}_{0}} = Reference constant σ {\displaystyle \sigma } = Substituent constant ρ {\displaystyle \rho } = Reaction rate constant === Effect on Lewis acidity === Electron-withdrawing groups tend to lower Lewis basicity. EWGs enhance the Lewis acidity, making compounds more reactive as Lewis acids. For example, fluorine is a stronger electron-withdrawing substituent than methyl, resulting in an increased Lewis acidity of boron trifluoride relative to trimethylborane. This effect of EWG has been quantified in many of ways. The Tolman electronic parameter is determined by the frequency of a C-O vibrational mode (ν(CO)) of the coordination complexes [LNi(CO)3] (L = Lewis base). === Effect on a aromatic substitution reactions === Electrophilic aromatic substitution is famously affected by EWGs. The effect is transmitted by inductive and resonance effects. Benzene with an EWG typically undergoes electrophilic substitution at meta positions. Overall the rates are diminished. thus EWGs are called deactivating. When it comes to
|
{
"page_id": 4458422,
"source": null,
"title": "Electron-withdrawing group"
}
|
nucleophilic substitution reactions, electron-withdrawing groups are more prone to nucleophilic substitution. For example, chlorodinitrobenzene is far more susceptible to reactions displacing chloride compared to chlorobenzene. === Effects on redox potential === In the context of electron transfer, these groups enhance the oxidizing power tendency of the attached species. For example, Tetracyanoethylene serves as an oxidant due to its four cyano substituents, which are electron-withdrawing. Oxidants with EWGs are stronger than the parent compound. Acetylferrocenium is 300 mV more oxidizing than ferrocene. == Comparison with electron-donating groups == Electron-withdrawing groups are the opposite effect of electron-donating groups (EDGs). Both describe functional groups, however, electron-withdrawing groups pull electron density away from a molecule, whereas EDGs push electron density onto a substituent. == See also == Electron-donating group == References ==
|
{
"page_id": 4458422,
"source": null,
"title": "Electron-withdrawing group"
}
|
Malcolm Bruce Smith (29 February 1924 – 27 July 2000) was an Australian chemist who studied the egg protein ovalbumin. He described the formation of S-ovalbumin from the native form (R-ovalbumin) as the pH of eggs rises over time. Smith was raised and attended schools in Angaston and Nuriootpa in South Australia. He won Country Scholarship to study Industrial Chemistry at the South Australian School of Mines in Adelaide. His studies were interrupted by World War II, when he was recruited to a laboratory position by the Munitions Department. After some years working for a public analyst in Adelaide, C.A.Smythe & Co, he was engaged by the Australian Council for Scientific and Industrial Research (later renamed the C.S.I.R.O) as a Technical Officer at the Division of Food Preservation and Transport in Sydney. Smith remained in this employment until retiring on 29 February 1984 from the position of Principal Research Scientist at the then named Division of Food Research. Smith was co-author of a history of his Division, published in 1979. He was awarded degrees of BSc and MSc at the University of New South Wales in 1956 and 1959, and was awarded the degree of Doctor of Science by that University in 1980. His discourse discussed his published research into 'Physico-Chemical Studies on Proteins, with Particular Reference to the Structure and Stability of Egg Proteins.' Smith married Josephine Lucy in Adelaide in 1945, and had two daughters and two sons. He died from diffuse lewy body disease in 2000. == References ==
|
{
"page_id": 15140792,
"source": null,
"title": "Malcolm Bruce Smith"
}
|
N-acetylglutamate synthetase may refer to: Amino-acid N-acetyltransferase Glutamate N-acetyltransferase Urea cycle == See also == N-Acetylglutamate synthase
|
{
"page_id": 985017,
"source": null,
"title": "N-acetylglutamate synthetase"
}
|
Moscovium is a synthetic chemical element; it has symbol Mc and atomic number 115. It was first synthesized in 2003 by a joint team of Russian and American scientists at the Joint Institute for Nuclear Research (JINR) in Dubna, Russia. In December 2015, it was recognized as one of four new elements by the Joint Working Party of international scientific bodies IUPAC and IUPAP. On 28 November 2016, it was officially named after the Moscow Oblast, in which the JINR is situated. Moscovium is an extremely radioactive element: its most stable known isotope, moscovium-290, has a half-life of only 0.65 seconds. In the periodic table, it is a p-block transactinide element. It is a member of the 7th period and is placed in group 15 as the heaviest pnictogen. Moscovium is calculated to have some properties similar to its lighter homologues, nitrogen, phosphorus, arsenic, antimony, and bismuth, and to be a post-transition metal, although it should also show several major differences from them. In particular, moscovium should also have significant similarities to thallium, as both have one rather loosely bound electron outside a quasi-closed shell. Chemical experimentation on single atoms has confirmed theoretical expectations that moscovium is less reactive than its lighter homologue bismuth. Over a hundred atoms of moscovium have been observed to date, all of which have been shown to have mass numbers from 286 to 290. == Introduction == == History == === Discovery === The first successful synthesis of moscovium was by a joint team of Russian and American scientists in August 2003 at the Joint Institute for Nuclear Research (JINR) in Dubna, Russia. Headed by Russian nuclear physicist Yuri Oganessian, the team included American scientists of the Lawrence Livermore National Laboratory. The researchers on February 2, 2004, stated in Physical Review C that they bombarded
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
americium-243 with calcium-48 ions to produce four atoms of moscovium. These atoms decayed by emission of alpha-particles to nihonium in about 100 milliseconds. The Dubna–Livermore collaboration strengthened their claim to the discoveries of moscovium and nihonium by conducting chemical experiments on the final decay product 268Db. None of the nuclides in this decay chain were previously known, so existing experimental data was not available to support their claim. In June 2004 and December 2005, the presence of a dubnium isotope was confirmed by extracting the final decay products, measuring spontaneous fission (SF) activities and using chemical identification techniques to confirm that they behave like a group 5 element (as dubnium is known to be in group 5 of the periodic table). Both the half-life and the decay mode were confirmed for the proposed 268Db, lending support to the assignment of the parent nucleus to moscovium. However, in 2011, the IUPAC/IUPAP Joint Working Party (JWP) did not recognize the two elements as having been discovered, because current theory could not distinguish the chemical properties of group 4 and group 5 elements with sufficient confidence. Furthermore, the decay properties of all the nuclei in the decay chain of moscovium had not been previously characterized before the Dubna experiments, a situation which the JWP generally considers "troublesome, but not necessarily exclusive". === Road to confirmation === Two heavier isotopes of moscovium, 289Mc and 290Mc, were discovered in 2009–2010 as daughters of the tennessine isotopes 293Ts and 294Ts; the isotope 289Mc was later also synthesized directly and confirmed to have the same properties as found in the tennessine experiments. In 2011, the Joint Working Party of international scientific bodies International Union of Pure and Applied Chemistry (IUPAC) and International Union of Pure and Applied Physics (IUPAP) evaluated the 2004 and 2007 Dubna experiments, and
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
concluded that they did not meet the criteria for discovery. Another evaluation of more recent experiments took place within the next few years, and a claim to the discovery of moscovium was again put forward by Dubna. In August 2013, a team of researchers at Lund University and at the Gesellschaft für Schwerionenforschung (GSI) in Darmstadt, Germany announced they had repeated the 2004 experiment, confirming Dubna's findings. Simultaneously, the 2004 experiment had been repeated at Dubna, now additionally also creating the isotope 289Mc that could serve as a cross-bombardment for confirming the discovery of the tennessine isotope 293Ts in 2010. Further confirmation was published by the team at the Lawrence Berkeley National Laboratory in 2015. In December 2015, the IUPAC/IUPAP Joint Working Party recognized the element's discovery and assigned the priority to the Dubna-Livermore collaboration of 2009–2010, giving them the right to suggest a permanent name for it. While they did not recognise the experiments synthesising 287Mc and 288Mc as persuasive due to the lack of a convincing identification of atomic number via cross-reactions, they recognised the 293Ts experiments as persuasive because its daughter 289Mc had been produced independently and found to exhibit the same properties. In May 2016, Lund University (Lund, Scania, Sweden) and GSI cast some doubt on the syntheses of moscovium and tennessine. The decay chains assigned to 289Mc, the isotope instrumental in the confirmation of the syntheses of moscovium and tennessine, were found based on a new statistical method to be too different to belong to the same nuclide with a reasonably high probability. The reported 293Ts decay chains approved as such by the JWP were found to require splitting into individual data sets assigned to different tennessine isotopes. It was also found that the claimed link between the decay chains reported as from 293Ts and
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
289Mc probably did not exist. (On the other hand, the chains from the non-approved isotope 294Ts were found to be congruent.) The multiplicity of states found when nuclides that are not even–even undergo alpha decay is not unexpected and contributes to the lack of clarity in the cross-reactions. This study criticized the JWP report for overlooking subtleties associated with this issue, and considered it "problematic" that the only argument for the acceptance of the discoveries of moscovium and tennessine was a link they considered to be doubtful. On June 8, 2017, two members of the Dubna team published a journal article answering these criticisms, analysing their data on the nuclides 293Ts and 289Mc with widely accepted statistical methods, noted that the 2016 studies indicating non-congruence produced problematic results when applied to radioactive decay: they excluded from the 90% confidence interval both average and extreme decay times, and the decay chains that would be excluded from the 90% confidence interval they chose were more probable to be observed than those that would be included. The 2017 reanalysis concluded that the observed decay chains of 293Ts and 289Mc were consistent with the assumption that only one nuclide was present at each step of the chain, although it would be desirable to be able to directly measure the mass number of the originating nucleus of each chain as well as the excitation function of the 243Am+48Ca reaction. === Naming === Using Mendeleev's nomenclature for unnamed and undiscovered elements, moscovium is sometimes known as eka-bismuth. In 1979, IUPAC recommended that the placeholder systematic element name ununpentium (with the corresponding symbol of Uup) be used until the discovery of the element is confirmed and a permanent name is decided. Although widely used in the chemical community on all levels, from chemistry classrooms to advanced textbooks,
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
the recommendations were mostly ignored among scientists in the field, who called it "element 115", with the symbol of E115, (115) or even simply 115. On 30 December 2015, discovery of the element was recognized by the International Union of Pure and Applied Chemistry (IUPAC). According to IUPAC recommendations, the discoverer(s) of a new element has the right to suggest a name. A suggested name was langevinium, after Paul Langevin. Later, the Dubna team mentioned the name moscovium several times as one among many possibilities, referring to the Moscow Oblast where Dubna is located. In June 2016, IUPAC endorsed the latter proposal to be formally accepted by the end of the year, which it was on 28 November 2016. The naming ceremony for moscovium, tennessine, and oganesson was held on 2 March 2017 at the Russian Academy of Sciences in Moscow. === Other routes of synthesis === In 2024, the team at JINR reported the observation of one decay chain of 289Mc while studying the reaction between 242Pu and 50Ti, aimed at producing more neutron-deficient livermorium isotopes in preparation for synthesis attempts of elements 119 and 120. This was the first successful report of a charged-particle exit channel – the evaporation of a proton and two neutrons, rather than only neutrons, as the compound nucleus de-excites to the ground state – in a hot fusion reaction between an actinide target and a projectile with atomic number greater than or equal to 20. Such reactions have been proposed as a novel synthesis route for yet-undiscovered isotopes of superheavy elements with several neutrons more than the known ones, which may be closer to the theorized island of stability and have longer half-lives. In particular, the isotopes 291Mc–293Mc may be reachable in these types of reactions within current detection limits. == Predicted properties
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
== Other than nuclear properties, no properties of moscovium or its compounds have been measured; this is due to its extremely limited and expensive production and the fact that it decays very quickly. Properties of moscovium remain unknown and only predictions are available. === Nuclear stability and isotopes === Moscovium is expected to be within an island of stability centered on copernicium (element 112) and flerovium (element 114). Due to the expected high fission barriers, any nucleus within this island of stability exclusively decays by alpha decay and perhaps some electron capture and beta decay. Although the known isotopes of moscovium do not actually have enough neutrons to be on the island of stability, they can be seen to approach the island as in general, the heavier isotopes are the longer-lived ones. The hypothetical isotope 291Mc is an especially interesting case as it has only one neutron more than the heaviest known moscovium isotope, 290Mc. It could plausibly be synthesized as the daughter of 295Ts, which in turn could be made from the reaction 249Bk(48Ca,2n)295Ts. Calculations show that it may have a significant electron capture or positron emission decay mode in addition to alpha decay and also have a relatively long half-life of several seconds. This would produce 291Fl, 291Nh, and finally 291Cn which is expected to be in the middle of the island of stability and have a half-life of about 1200 years, affording the most likely hope of reaching the middle of the island using current technology. Possible drawbacks are that the cross section of the production reaction of 295Ts is expected to be low and the decay properties of superheavy nuclei this close to the line of beta stability are largely unexplored. The heavy isotopes from 291Mc to 294Mc might also be produced using charged-particle evaporation, in
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
the 245Cm(48Ca,pxn) and 248Cm(48Ca,pxn) reactions. The light isotopes 284Mc, 285Mc, and 286Mc could be made from the 241Am+48Ca reaction. They would undergo a chain of alpha decays, ending at transactinide isotopes too light to be made by hot fusion and too heavy to be made by cold fusion. The isotope 286Mc was found in 2021 at Dubna, in the 243Am(48Ca,5n)286Mc reaction: it decays into the already-known 282Nh and its daughters. The yet lighter 282Mc and 283Mc could be made from 243Am+44Ca, but the cross-section would likely be lower. Other possibilities to synthesize nuclei on the island of stability include quasifission (partial fusion followed by fission) of a massive nucleus. Such nuclei tend to fission, expelling doubly magic or nearly doubly magic fragments such as calcium-40, tin-132, lead-208, or bismuth-209. It has been shown that the multi-nucleon transfer reactions in collisions of actinide nuclei (such as uranium and curium) might be used to synthesize the neutron-rich superheavy nuclei located at the island of stability, although formation of the lighter elements nobelium or seaborgium is more favored. One last possibility to synthesize isotopes near the island is to use controlled nuclear explosions to create a neutron flux high enough to bypass the gaps of instability at 258–260Fm and at mass number 275 (atomic numbers 104 to 108), mimicking the r-process in which the actinides were first produced in nature and the gap of instability around radon bypassed. Some such isotopes (especially 291Cn and 293Cn) may even have been synthesized in nature, but would have decayed away far too quickly (with half-lives of only thousands of years) and be produced in far too small quantities (about 10−12 the abundance of lead) to be detectable as primordial nuclides today outside cosmic rays. === Physical and atomic === In the periodic table, moscovium is a
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
member of group 15, the pnictogens. It appears below nitrogen, phosphorus, arsenic, antimony, and bismuth. Every previous pnictogen has five electrons in its valence shell, forming a valence electron configuration of ns2np3. In moscovium's case, the trend should be continued and the valence electron configuration is predicted to be 7s27p3; therefore, moscovium will behave similarly to its lighter congeners in many respects. However, notable differences are likely to arise; a largely contributing effect is the spin–orbit (SO) interaction—the mutual interaction between the electrons' motion and spin. It is especially strong for the superheavy elements, because their electrons move much faster than in lighter atoms, at velocities comparable to the speed of light. In relation to moscovium atoms, it lowers the 7s and the 7p electron energy levels (stabilizing the corresponding electrons), but two of the 7p electron energy levels are stabilized more than the other four. The stabilization of the 7s electrons is called the inert-pair effect, and the effect "tearing" the 7p subshell into the more stabilized and the less stabilized parts is called subshell splitting. Computation chemists see the split as a change of the second (azimuthal) quantum number l from 1 to 1⁄2 and 3⁄2 for the more stabilized and less stabilized parts of the 7p subshell, respectively. For many theoretical purposes, the valence electron configuration may be represented to reflect the 7p subshell split as 7s27p21/27p13/2. These effects cause moscovium's chemistry to be somewhat different from that of its lighter congeners. The valence electrons of moscovium fall into three subshells: 7s (two electrons), 7p1/2 (two electrons), and 7p3/2 (one electron). The first two of these are relativistically stabilized and hence behave as inert pairs, while the last is relativistically destabilized and can easily participate in chemistry. (The 6d electrons are not destabilized enough to participate chemically.)
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
Thus, the +1 oxidation state should be favored, like Tl+, and consistent with this the first ionization potential of moscovium should be around 5.58 eV, continuing the trend towards lower ionization potentials down the pnictogens. Moscovium and nihonium both have one electron outside a quasi-closed shell configuration that can be delocalized in the metallic state: thus they should have similar melting and boiling points (both melting around 400 °C and boiling around 1100 °C) due to the strength of their metallic bonds being similar. Additionally, the predicted ionization potential, ionic radius (1.5 Å for Mc+; 1.0 Å for Mc3+), and polarizability of Mc+ are expected to be more similar to Tl+ than its true congener Bi3+. Moscovium should be a dense metal due to its high atomic weight, with a density around 13.5 g/cm3. The electron of the hydrogen-like moscovium atom (oxidized so that it only has one electron, Mc114+) is expected to move so fast that it has a mass 1.82 times that of a stationary electron, due to relativistic effects. For comparison, the figures for hydrogen-like bismuth and antimony are expected to be 1.25 and 1.077 respectively. === Chemical === Moscovium is predicted to be the third member of the 7p series of chemical elements and the heaviest member of group 15 in the periodic table, below bismuth. Unlike the two previous 7p elements, moscovium is expected to be a good homologue of its lighter congener, in this case bismuth. In this group, each member is known to portray the group oxidation state of +5 but with differing stability. For nitrogen, the +5 state is mostly a formal explanation of molecules like N2O5: it is very difficult to have five covalent bonds to nitrogen due to the inability of the small nitrogen atom to accommodate five ligands. The
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
+5 state is well represented for the essentially non-relativistic typical pnictogens phosphorus, arsenic, and antimony. However, for bismuth it becomes rare due to the relativistic stabilization of the 6s orbitals known as the inert-pair effect, so that the 6s electrons are reluctant to bond chemically. It is expected that moscovium will have an inert-pair effect for both the 7s and the 7p1/2 electrons, as the binding energy of the lone 7p3/2 electron is noticeably lower than that of the 7p1/2 electrons. Nitrogen(I) and bismuth(I) are known but rare and moscovium(I) is likely to show some unique properties, probably behaving more like thallium(I) than bismuth(I). Because of spin-orbit coupling, flerovium may display closed-shell or noble gas-like properties; if this is the case, moscovium will likely be typically monovalent as a result, since the cation Mc+ will have the same electron configuration as flerovium, perhaps giving moscovium some alkali metal character. Calculations predict that moscovium(I) fluoride and chloride would be ionic compounds, with an ionic radius of about 109–114 pm for Mc+, although the 7p1/2 lone pair on the Mc+ ion should be highly polarisable. The Mc3+ cation should behave like its true lighter homolog Bi3+. The 7s electrons are too stabilized to be able to contribute chemically and hence the +5 state should be impossible and moscovium may be considered to have only three valence electrons. Moscovium would be quite a reactive metal, with a standard reduction potential of −1.5 V for the Mc+/Mc couple. The chemistry of moscovium in aqueous solution should essentially be that of the Mc+ and Mc3+ ions. The former should be easily hydrolyzed and not be easily complexed with halides, cyanide, and ammonia. Moscovium(I) hydroxide (McOH), carbonate (Mc2CO3), oxalate (Mc2C2O4), and fluoride (McF) should be soluble in water; the sulfide (Mc2S) should be insoluble; and the
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
chloride (McCl), bromide (McBr), iodide (McI), and thiocyanate (McSCN) should be only slightly soluble, so that adding excess hydrochloric acid would not noticeably affect the solubility of moscovium(I) chloride. Mc3+ should be about as stable as Tl3+ and hence should also be an important part of moscovium chemistry, although its closest homolog among the elements should be its lighter congener Bi3+. Moscovium(III) fluoride (McF3) and thiozonide (McS3) should be insoluble in water, similar to the corresponding bismuth compounds, while moscovium(III) chloride (McCl3), bromide (McBr3), and iodide (McI3) should be readily soluble and easily hydrolyzed to form oxyhalides such as McOCl and McOBr, again analogous to bismuth. Both moscovium(I) and moscovium(III) should be common oxidation states and their relative stability should depend greatly on what they are complexed with and the likelihood of hydrolysis. Like its lighter homologues ammonia, phosphine, arsine, stibine, and bismuthine, moscovine (McH3) is expected to have a trigonal pyramidal molecular geometry, with an Mc–H bond length of 195.4 pm and a H–Mc–H bond angle of 91.8° (bismuthine has bond length 181.7 pm and bond angle 91.9°; stibine has bond length 172.3 pm and bond angle 92.0°). In the predicted aromatic pentagonal planar Mc−5 cluster, analogous to pentazolate (N−5), the Mc–Mc bond length is expected to be expanded from the extrapolated value of 312–316 pm to 329 pm due to spin–orbit coupling effects. == Experimental chemistry == The isotopes 288Mc, 289Mc, and 290Mc have half-lives long enough for chemical investigation. A 2024 experiment at the GSI, producing 288Mc via the 243Am+48Ca reaction, studied the adsorption of nihonium and moscovium on SiO2 and gold surfaces. The adsorption enthalpy of moscovium on SiO2 was determined experimentally as −ΔHSiO2ads(Mc) = 54+11−5 kJ/mol (68% confidence interval). Moscovium was determined to be less reactive with the SiO2 surface than its lighter congener bismuth,
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
}
|
but more reactive than closed-shell copernicium and flerovium. This arises because of the relativistic stabilisation of the 7p1/2 shell. == See also == Materials science in science fiction § Moscovium == Notes == == References == == Bibliography == Audi, G.; Kondev, F. G.; Wang, M.; et al. (2017). "The NUBASE2016 evaluation of nuclear properties". Chinese Physics C. 41 (3): 030001. Bibcode:2017ChPhC..41c0001A. doi:10.1088/1674-1137/41/3/030001. Beiser, A. (2003). Concepts of modern physics (6th ed.). McGraw-Hill. ISBN 978-0-07-244848-1. OCLC 48965418. Hoffman, D. C.; Ghiorso, A.; Seaborg, G. T. (2000). The Transuranium People: The Inside Story. World Scientific. ISBN 978-1-78-326244-1. Kragh, H. (2018). From Transuranic to Superheavy Elements: A Story of Dispute and Creation. Springer. ISBN 978-3-319-75813-8. == External links == Uut and Uup Add Their Atomic Mass to Periodic Table Archived 2006-09-07 at the Wayback Machine Superheavy elements History and etymology Moscovium at The Periodic Table of Videos (University of Nottingham)
|
{
"page_id": 67514,
"source": null,
"title": "Moscovium"
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|
The molecular formula C3H6O2 may refer to: == Acids and esters == === Acid === Propanoic acid === Esters === Methyl acetate Ethyl formate == Aldehydes and ketones == Lactaldehyde (2-hydroxypropanal) (S)-Lactaldehyde (R)-Lactaldehyde Reuterin (3-hydroxypropanal) Methoxyacetaldehyde Hydroxyacetone == Alkenes == === Diols === 1-Propene-1,1-diol 1-Propene-1,2-diol (E)-1-Propene-1,2-diol (Z)-1-Propene-1,2-diol 1-Propene-1,3-diol (E)-Propene-1,3-diol (Z)-Propene-1,3-diol 2-Propene-1,1-diol 2-Propene-1,2-diol === Oxyethenol === 1-Methoxyethenol == Cyclic == === Three atoms in ring === ==== No oxygen in ring ==== 1,1-Cyclopropandiol Cyclopropan-1,2-diol (E)-Cyclopropan-1,2-diol (Z)-Cyclopropan-1,2-diol ==== One oxygen in ring ==== Glycidol (oxiran-2-ylmethanol) (R)-Glycidol (S)-Glycidol 2-Methyloxiranol (R)-2-Methyloxiranol (S)-2-Methyloxiranol 3-Methyloxiranol (R,R)-3-Methyloxiranol (R,S)-3-Methyloxiranol (S,R)-3-Methyloxiranol (S,S)-3-Methyloxiranol === Two oxygens in ring === Dimethyldioxirane === Four atoms in ring === ==== One oxygen in ring ==== Oxetan-3-ol Oxetan-2-ol (R)-Oxetan-2-ol (S)-Oxetan-2-ol ==== Two oxygens in ring ==== 3-Methyl-1,2-dioxetane (R)-3-Methyl-1,2-dioxetane (S)-3-Methyl-1,2-dioxetane 2-Methyl-1,3-dioxetane === Five atoms in ring === 1,2-Dioxolane 1,3-Dioxolane
|
{
"page_id": 12126139,
"source": null,
"title": "C3H6O2"
}
|
A systematic element name is the temporary name assigned to an unknown or recently synthesized chemical element. A systematic symbol is also derived from this name. In chemistry, a transuranic element receives a permanent name and symbol only after its synthesis has been confirmed. In some cases, such as the Transfermium Wars, controversies over the formal name and symbol have been protracted and highly political. In order to discuss such elements without ambiguity, the International Union of Pure and Applied Chemistry (IUPAC) uses a set of rules, adopted in 1978, to assign a temporary systematic name and symbol to each such element. This approach to naming originated in the successful development of regular rules for the naming of organic compounds. == IUPAC rules == The temporary names derive systematically from the element's atomic number, and apply only to 101 ≤ Z ≤ 999. Each digit is translated into a "numerical root" according to the table. The roots are concatenated, and the name is completed by the suffix -ium. Some of the roots are Latin and others are Greek, to avoid two digits starting with the same letter (for example, the Greek-derived pent is used instead of the Latin-derived quint to avoid confusion with quad for 4). There are two elision rules designed to prevent odd-looking names. Traditionally the suffix -ium was used only for metals (or at least elements that were expected to be metallic), and other elements used different suffixes: halogens used -ine and noble gases used -on instead. However, the systematic names use -ium for all elements regardless of group. Thus, elements 117 and 118 were ununseptium and ununoctium, not ununseptine and ununocton. This does not apply to the trivial names these elements receive once confirmed; thus, elements 117 and 118 are now tennessine and oganesson, respectively. For
|
{
"page_id": 67513,
"source": null,
"title": "Systematic element name"
}
|
these trivial names, all elements receive the suffix -ium except those in group 17, which receive -ine (like the halogens), and those in group 18, which receive -on (like the noble gases). (That being said, tennessine and oganesson are expected to behave quite differently from their lighter congeners.) The systematic symbol is formed by taking the first letter of each root, converting the first to uppercase. This results in three-letter symbols instead of the one- or two-letter symbols used for named elements. The rationale is that any scheme producing two-letter symbols will have to deviate from full systematicity to avoid collisions with the symbols of the permanently named elements. The Recommendations for the Naming of Elements of Atomic Numbers Greater than 100 can be found here. As of 2019, all 118 discovered elements have received individual permanent names and symbols. Therefore, systematic names and symbols are now used only for the undiscovered elements beyond element 118, oganesson. When such an element is discovered, it will keep its systematic name and symbol until its discovery meets the criteria of and is accepted by the IUPAC/IUPAP Joint Working Party, upon which the discoverers are invited to propose a permanent name and symbol. Once this name and symbol is proposed, there is still a comment period before they become official and replace the systematic name and symbol. At the time the systematic names were recommended (1978), names had already been officially given to all elements up to atomic number 103, lawrencium. While systematic names were given for elements 101 (mendelevium), 102 (nobelium), and 103 (lawrencium), these were only as "minor alternatives to the trivial names already approved by IUPAC". The following elements for some time only had systematic names as approved names, until their final replacement with trivial names after their discoveries were
|
{
"page_id": 67513,
"source": null,
"title": "Systematic element name"
}
|
accepted. == See also == Mendeleev's predicted elements – a much earlier (1869) system of naming undiscovered elements == References == == External links == IUPAC Provisional Recommendations: IR-3: Elements and Groups of Elements (PDF) (Report). IUPAC. March 2004.
|
{
"page_id": 67513,
"source": null,
"title": "Systematic element name"
}
|
Guan ware or Kuan ware (Chinese: 官窯; pinyin: guān yáo; Wade–Giles: kuan-yao) is one of the Five Famous Kilns of Song dynasty China, making high-status stonewares, whose surface decoration relied heavily on crackled glaze, randomly crazed by a network of crack lines in the glaze. Guan means "official" in Chinese and Guan ware was, most unusually for Chinese ceramics of the period, the result of an imperial initiative resulting from the loss of access to northern kilns such as those making Ru ware and Jun ware after the invasion of the north and the flight of a Song prince to establish the Southern Song at a new capital at Hangzhou, Zhejiang province. It is usually assumed that potters from the northern imperial kilns followed the court south to man the new kilns. In some Asian sources "Guan ware" may be used in the literally translated sense to cover any "official" wares ordered by the Imperial court. In April 2015, Liu Yiqian paid US$14.7 million for a Guan ware vase from the Southern Song. == Dating and kiln sites == The new Southern Song court was established in Hangzhou in 1127, but some time probably elapsed before the kiln was established; this may not have been until after hostilities with the invaders were concluded in 1141. According to Chinese historical sources, the first kiln was actually within or beside the palace precinct, described as in the "back park", and was called or was at "Xiuneisi". Various places around the city have been explored, and ceramic remains found, but perhaps because of subsequent building on the site, the location of this kiln remained uncertain, and it is now thought that the name might refer to the controlling office rather than the actual kiln site. Following excavations in starting in 1996 it is
|
{
"page_id": 41224120,
"source": null,
"title": "Guan ware"
}
|
now thought that the site has been found, as the Laohudong or Tiger Cave Kiln [老虎洞窑] on the outskirts of the city. An old Yue ware dragon kiln had been revived, but the official wares were made in a northern-style mantou kiln, rare this far south. A second kiln was established later at Jiaotanxia ("Altar of Heaven" or "Suburban Altar"), on the outskirts of the new capital; this has been identified and excavated. In Chinese contemporary sources these wares were regarded as rather inferior to those from the first kiln, and the excavated sherds are very similar to those of the nearby Longquan celadon kilns. Indeed, Longquan may have helped out when the Guan kilns could not fulfill orders by themselves. The end date of Guan ware is uncertain, but it probably persisted until 1400 or later, as the Ge Gu Yao Lun, a fourteenth century Ming dynasty manual on ceramics by Cao Zhao, seems to treat it as being still produced. == Characteristics == Guan ware is not difficult to distinguish from the Ru ware which it perhaps tries to imitate, but wares from the second site can be very similar indeed to Longquan ware, and it has been suggested that some was made there. Crackled glaze is usual, but perhaps was not at this time a desired effect, as it certainly became in imitations centuries later. Alternatively it was originally produced accidentally, but within the Guan period became deliberate. In surviving examples the effect is probably often more striking than it would have been originally, either because collectors have chemically enhanced them, through gradual oxidation over time, or from staining in use. Three qualities of the ware are recorded in old sources, and can be identified in surviving examples. The best had a grey-blue glaze on a thin
|
{
"page_id": 41224120,
"source": null,
"title": "Guan ware"
}
|
body, with wide crackle, followed by a greener glaze with a denser crackle, then finally "almost a pale grey brown" with a "very dark close crackle on a dark grey body" that was rather thicker; all are illustrated here, with the types indicated by 1–3 (which is not a standard terminology). The crackle arises during cooling, when the coefficient of expansion differs between the glaze and the body. There are several layers of glaze, and the glaze is often thicker than the clay body, as can be seen in sherds. The crackle does not occur through all layers. Most shapes were wheel thrown, but moulds and slab-building were also used. Less usual shapes include those derived from ancient ritual bronzes and jade congs. Bowls and dishes often have "lobed or indented rims". == Imitations == Guan ware is "the most frequently copied of all Chinese wares", and the imitations began immediately, at the many southern kilns producing Longquan celadon and other wares. Imitations in Jingdezhen porcelain seem to have begun under the Yuan dynasty and continue to the present day; these are often hard to date. == Notes == == References == Gompertz, G.St.G.M., Chinese Celadon Wares, 1980 (2nd edn.), Faber & Faber, ISBN 0571180035 Kerr, Rose, Needham, Joseph, Wood, Nigel, Science and Civilisation in China: Volume 5, Chemistry and Chemical Technology, Part 12, Ceramic Technology, 2004, Cambridge University Press, ISBN 0521838339, 9780521838337 Koh, NK, Koh Antiques, Singapore, "Guan wares" (covering official wares) Krahl, Regina, Oxford Art Online, "Guan and Ge wares", section in "China, §VIII, 3: Ceramics: Historical development" Medley, Margaret, The Chinese Potter: A Practical History of Chinese Ceramics, 3rd edition, 1989, Phaidon, ISBN 071482593X Vainker, S.J., Chinese Pottery and Porcelain, 1991, British Museum Press, 9780714114705 Valenstein, S. (1998). A handbook of Chinese ceramics, Metropolitan Museum of Art,
|
{
"page_id": 41224120,
"source": null,
"title": "Guan ware"
}
|
New York. ISBN 9780870995149 (fully online)
|
{
"page_id": 41224120,
"source": null,
"title": "Guan ware"
}
|
A discharge ionization detector (DID) is a type of detector used in gas chromatography. == Principle == A DID is an ion detector which uses a high-voltage electric discharge to produce ions. The detector uses an electrical discharge in helium to generate high energy UV photons and metastable helium which ionizes all compounds except helium. The ions produce an electric current, which is the signal output of the detector. The greater the concentration of the component, the more ions are produced, and the greater the current. == Application == DIDs are sensitive to a broad range of components. In air separation plants, they are used to detect the components CO; CH2; C+; N2; O2 in argon product in ppm range. DIDs are non-destructive detectors. They do not destroy or consume the components they detect. Therefore, they can be used before other detectors in multiple-detector configurations. DIDs are an improvement over helium ionization detectors in that they contain no radioactive source. == References ==
|
{
"page_id": 4917179,
"source": null,
"title": "Discharge ionization detector"
}
|
Pydlpoly is a molecular dynamics simulation package which is a modified version of DL-POLY with a Python language interface. Pydlpoly is written by Rochus Schmid in Ruhr University Bochum, Germany.
|
{
"page_id": 39913402,
"source": null,
"title": "Pydlpoly"
}
|
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