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1-s2_0-S0304386X21000529-main | chunk_1 | Hydrometallurgy 202 (2021) 105603 Contents lists available at ScienceDirect HYDRO Hydrometallurgy MET ELSEVIER evier.com/locate/hydromet Electrochemical investigation of microbially and galvanically leached chalcopyrite C. Tanne, A. Schippers Federal Institute forGeosciences and NaturalResources (BGR),ResourceGeochemis... |
1-s2_0-S0304386X21000529-main | chunk_2 | The galvanic behavior of mixed mineral systems and their role dur- Table 1 ing oxidative bioleaching have been thoroughly studied (Donati and Sand, 2007; Tanne and Schippers, 2019a), and the occurrence of Element Content [%] galvanic interactions between different minerals and their influence Chalcopyrite BG Chalcopyri... |
1-s2_0-S0304386X21000529-main | chunk_3 | Rest potential measurements were performed in the absence of microorganisms by the measurement of the the microbial growth medium were used as electrolyte during electro- open circuit potential until the steady state signal remained stable over chemical measurements which were performed under aerobic condi- hours. The ... |
1-s2_0-S0304386X21000529-main | chunk_4 | The minerals chalcopyrite or pyrite were each con- mineral if galvanic assisted bioleaching is intentionally applied. A nected to an electrode made of the same or the other mineral. A selection higher potential difference leads to higher corrosion currents which of detected coupling currents is shown in Fig. 3 as a fun... |
1-s2_0-S0304386X21000529-main | chunk_5 | Thus, abrasivenes due to shear forces A typical electrochemical corrosion test is the determination of the may favor the corrosion of chalcopyrite in case of quartz addition, or corrosion potential and the corrosion current using potentiodynamic silica may have a catalytic effect on abiotic chalcopyrite dissolution. Th... |
1-s2_0-S0304386X21000529-main | chunk_6 | This and their properties related to electrochemistry are on demand. The may explain why for bioleaching residues (Fig. 8e) a very low oxidation option of running electro-bioreactors and galvanic support in combi- current was measured. In contrast, chemically leached copper concen- nation should also be examined to a l... |
1-s2_0-S0304386X21000529-main | chunk_7 | Microbiol. 53, 1536-1540. for the dissolution kinetics and passivation mechanism. J. Colloid Interface Sci. 584, Mehta, A.P., Murr, L.E., 1982. Kinetic study of sulfide leaching by galvanic interaction 103-113. https://doi.org/10.1016/jcis.2020.09.115. between chalcopyrite, pyrite,and sphalerite in the presence of T. f... |
1-s2_0-S0048969723068377-main | chunk_1 | Science of the Total Environment 908 (2024) 168210 Contents lists available at ScienceDirect Science Science of the Total Environment ELSEVIER Review Biomining for sustainable recovery of rare earth elements from mining waste: A comprehensive review Phong H.N. Vo a*, Soroosh Danaee b, Ho Truong Nam Hai , Lai Nguyen Huy... |
1-s2_0-S0048969723068377-main | chunk_2 | Therefore, the current mining residue/waste recycling rate ligand complexes in mining waste is low pH (<3), along with the atomic is still very modest compared to its vast potential. number of associated REEs, as REEs presence decreases with increasing Existing methods for REEs recovery such as hydro-, thermal- and ato... |
1-s2_0-S0048969723068377-main | chunk_3 | It was reported that leaching efficiency of 91 %, whereas when sucrose was used, A. niger and disrupting a single gene within the phosphate signalling control of Y lipolytica reached a leaching efficiency of 66 %, and 34 % respectively biolixiviant production, increased bioleaching by 18 %; however, dis- (Shen et al., ... |
1-s2_0-S0048969723068377-main | chunk_4 | While ion-exchange is responsible for binding negatively popular for other elements (e.g., Fe, P, Si), research into REEs recovery is charged groups to metal cations, electrostatic interactions or hydrogen still limited (Chikkanna et al., 2021). binding forces are responsible for the adsorption of anions. Additionally,... |
1-s2_0-S0048969723068377-main | chunk_5 | Inactive biomass for biosorption fastest, at a rate of up to 92 %. In this case, REEs were primarily localized Besides active biomass, inactive biomass is another biosorbent with in the outer fraction, and bonded to the sulfated polysaccharide of Ulva potential for REEs recovery. The inactive biomass can be either the ... |
1-s2_0-S0048969723068377-main | chunk_6 | Macroalgae Spiked solution La, Nd, Dy 171 mg La/g Langmuir isotherm [5] 187 mg Nd/g 189 mg Dy/g Pseudo-second order Magnetospirillum magneticum Bacteria Spiked solution La 6.0 mg/g Langmuir isotherm [6] Bacillus licheniformis Bacteria Spiked solution Ce 38.93 mg/g Freundlich model [7] Pseudo-second order Acutodesi nina... |
1-s2_0-S0048969723068377-main | chunk_7 | Furthermore, there are some limitations in the Further, bioprecipitation derived biogenic sulfides are more effective upscaling process that are mostly related to the direct usage of micro- than chemically derived sulfides in precipitating metals, with up to organisms in flotation. The application of biosurfactants can... |
1-s2_0-S0048969723068377-main | chunk_8 | In contrast, chemical reactions increase with a way to introduce air into bioreactors which are influenced by their type temperature rise; thus, it positively affects REEs extraction (Rasoulnia and configuration, should also be considered. For example, baffles are et al., 2021). As a result, gas solubility and chemical... |
1-s2_0-S0048969723068377-main | chunk_9 | Considered Considered criteria Strengths Weaknesses Opportunities Threats aspects Technical Overall treatment High extraction efficiency Slow reaction times Optimal reaction time High cell densities required aspects performance (>80 %). High temperature required. identified via optimal for leachate. High selectivity fo... |
1-s2_0-S0048969723068377-main | chunk_10 | Given the success in REEs recovery from published biomining There are some critical points that must be addressed: studies, conducting more in-depth research and technology transfer is necessary to further optimize biomining technologies. It is recom- · The abundance and concentration of REEs in mining waste vary mende... |
1-s2_0-S0048969723068377-main | chunk_11 | Engelbrektson, A.L., Cheng, Y., Hubbard, C.G., Jin, Y.T., Arora, B., Tom, L.M., Hu, P., Moropeng, L., Yahaya, A., Mamudu, O.A., 2020. A review on the impact of mining Grauel, A.-L., Conrad, M.E., Andersen, G.L., Ajo-Franklin, J.B., Coates, J.D., 2018. operation: monitoring, assessment and management. Results Eng. 8, 10... |
1-s2_0-S0048969723068377-main | chunk_12 | In: Wong, J.W.C., Tyagi, R.D. (Eds.), Liu, C., Liu, W.-S., van der Ent, A., Morel, J.L., Zheng, H.-X., Wang, G.-B., Tang, Y.-T., Current Developments in Biotechnology and Bioengineering. Elsevier, pp. 241-265. Qiu, R.-L., 2021. Simultaneous hyperaccumulation of rare earth elements, Guezennec, A-G., Joulian, C., Jacob, ... |
1-s2_0-S0048969723068377-main | chunk_13 | Geochemical Mwewa, B., Tadie, M., Ndlovu, S., Simate, G.S., Matinde, E., 2022. Recovery of rare earth characteristics of coal mine discharge vis-a-vis behavior of rare earth elements at elements from acid mine drainage: a review of the extraction methods. J. Environ. Jaintia Hills coalfield, northeastern India. J. Geoc... |
1-s2_0-S0048969723068377-main | chunk_14 | Sun, Q., Liu, X., Wang, S., Lian, B., 2020. Effects of mineral substrate on ectomycorrhizal Environ. Sci. Technol. 51 (4), 378-427. fungal colonization and bacterial community structure. Sci. Total Environ. 721, Reynier, N., Gagne-Turcotte, R., Coudert, L., Costis, S., Cameron, R., Blais, J.-F., 2021. 137663. Bioleachi... |
1-s2_0-S2589014X22000494-main | chunk_1 | Bioresource Technology Reports 17 (2022) 100992 Contents lists available at ScienceDirect BEORESOLURCE REPORTS Bioresource Technology Reports ELSEVIER -technology-reports Orotic acid production from crude glycerol by engineered Ashbya gossypii Rui Silva, Tatiana Q. Aguiar, Lucilia Domingues CEB - Centre of Biological E... |
1-s2_0-S2589014X22000494-main | chunk_2 | Acro- fungus through metabolic engineering and culture conditions optimi- nyms near the gene names represent the corresponding enzyme: mtDHOD, zation; i) understanding the genetic factors for orotic acid accumulation mitochondrial dihydroorotate dehydrogenase; cytDHOD, cytosolic dihydroor- and excretion in fungi, which... |
1-s2_0-S2589014X22000494-main | chunk_3 | This sequence was amplified by PCR using specific primers (Section 1 of and the suspension was filtrated through qualitative filter paper Supplementary data), containing recombinogenic flanks for the ScURA3 (Advantec) to remove suspended debris. Then, the pH of the filtrate was locus, from gDNA of the strain A. gossypi... |
1-s2_0-S2589014X22000494-main | chunk_4 | Unless indicated otherwise, statistical significance was established mitochondrial DHOD would turn S. cerevisiae into an orotic acid pro- at p < 0.05 for the comparisons. ducer and thus demonstrate that, beyond the pyrimidine auxotrophy, the presence of this enzyme is determinant for orotic acid accumulation 3. Results... |
1-s2_0-S2589014X22000494-main | chunk_5 | Interestingly, both overexpressing strains presented The resulting strains, in particular the strain overexpressing the native similar improvements in response to the hyperosmotic conditions AFL067W, presented enhanced glycerol consumption and improved (Fig. 3B). Glycerol is the major osmoprotectant used by A. gossypi ... |
1-s2_0-S2589014X22000494-main | chunk_6 | Two new strains were constructed: strain uGU2, comprising the promising raw materials for A. gossypii cultivations, namely CG and genetic modifications of strain uG plus the overexpression of AgURA2; yeast extract. Therefore, these two media components were used to test and strain uGU2.9, comprising the genetic modific... |
1-s2_0-S2589014X22000494-main | chunk_7 | Consid- valorize CG in a circular economy context for orotic acid production. ering the many variables associated with the disposal, valorization and Given the need to improve the economic and environmental sus- bioconversion of crude glycerol to orotic acid, a comprehensive techno- tainability of the biodiesel industr... |
1-s2_0-S2589014X22000494-main | chunk_8 | Declaration of competing interest Gojkovic, Z., Knecht, W., Zameitat, E, Warneboldt, J., Coutelis, J.B., Pynyaha, Y., Neuveglise, C., Moller, K, Loffler, M., Piskur, J., 2004. Horizontal gene transfe promoted evolution of the ability to propagateunder anaerobic conditions in yeasts. The authors declare that they have n... |
1-s2_0-S2589014X22000494-main | chunk_9 | Nutritional requirements Wishart, D.S., Feunang, Y.D., Marcu, A., Guo, A.C., Liang, K., Vazquez-Fresno, R., and strain heterogeneity in Ashbya gossypi. J. Basic Microbiol. 52, 582-589. Sajed, T, Johnson, D., Li, C., Karu, N., Sayeeda, Z., Lo, E., Assempour, N., https://doi.org/10.1002/jobm.201100383. Berjanski, M, Sing... |
1-s2_0-S136759312100051X-main | chunk_1 | Available online at www.sciencedirect.com Chemical Biology ScienceDirect ELSEVIER Protein sequence design with deep generative models Kevin K. Yang promises to leverage the information obtained from wet Abstract lab experiments using data-driven models to more effi- Protein engineering seeks to identify protein sequenc... |
1-s2_0-S136759312100051X-main | chunk_2 | Notably, mediocre but functional ones. Biasing the initial input set these representations do not always outperform simpler for functional variants further optimizes evolution [25]. representations if training with a large fraction of the total [17]. Protein sequence generation In addition to improving function predict... |
1-s2_0-S136759312100051X-main | chunk_3 | The current iteration of this work, Condi- quences. In addition, 11% of 1000 sequences generated for tioning by Adaptive Sampling, improves this approach by recreating a removed copper-binding site identified the avoiding regions too far from the training set for the oracle correct binding amino acid triad. The authors... |
1-s2_0-S136759312100051X-main | chunk_4 | This work is supported by the Camille and Henry Dreyfus Foundation (ML-20-194) and the NSF Division of Chemical, Bioengineering, Environmental, and Transport Systems Many of the examples presented required testing many (1937902). protein variants, and many of the advances in machine Current Opinion in Chemical Biology ... |
1-s2_0-S136759312100051X-main | chunk_5 | References Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Papers of particular interest, published within the period of review, have been highlighted as: Grisel O, Blondel M,Prettenhofer P,Weiss R, Dubourg V,et al.: Scikit-learn: machine learning in python. J Mach Learn Res 2011, 12:2825-2830. *+ of special... |
1-s2_0-S136759312100051X-main | chunk_6 | Alford RF,Leaver-FayA,JeliazkovJR,O'Meara MJ,DiMaioFP, directedevolutionofbiomolecules.Nature2011,472: Park H, Shapovalov MV, Renfrew PD, Muligan VK, Kappel K, 499-503, https://doi.org/10.1038/nature09929. et al.: The rosetta all-atom energy function for macromolec- 56. Morrison MS, Podracky CJ, Liu DR: The developing ... |
1-s2_0-S095965262301346X-main | chunk_1 | Journal of Cleaner Production 410 (2023) 137188 Contents lists available at ScienceDirect Journal of Cleaner Production ELSEVIER journal homepage: www.elsevier.com/locate/jclepro Application of machine learning to guide efficient metal leaching from spent lithium-ion batteries and comprehensively reveal the process par... |
1-s2_0-S095965262301346X-main | chunk_2 | It was The relative research articles about hydrometallurgy recycling spent reported that ML can be also used to predict the metal recovery from LIBs between 2005 and 2022 were referred to using the Web of Science solid waste (Daware et al., 2022; Priyadarshini et al., 2022; Mokarian and Google Scholar databases. Gener... |
1-s2_0-S095965262301346X-main | chunk_3 | For the metal leaching after pretreatment was usually a data range (e.g., 200-300 μm, or ~500 efficiency (for instance Li), four optimal ML models from the XGB, RF, μm, etc.), the maximum data was the input. The acid type (a total of 25) SVM, and AdaBoost algorithms were obtained after hyperparameter was converted into... |
1-s2_0-S095965262301346X-main | chunk_4 | Meanwhile, the other leaching parameters including acid concentration, These made the organic acids less used in the industrialized hydromet- reductant additive amount of H2O2 and other solid, leaching time, allurgical process of spent LIBs. To combine with their advantages, temperature, pulp density, rotation speed, a... |
1-s2_0-S095965262301346X-main | chunk_5 | The results all suggested that the XGB model exhibited the influence of each input feature on the target variable of Li leaching ef- best prediction. Furthermore, the XGB validation RMSE values of ficiency. The figure depicts the mean SHAP value for each input feature 10.22-15.45 suggested the reliability of the model,... |
1-s2_0-S095965262301346X-main | chunk_6 | When the pKa1 is larger than 3.75, the articles from 2005 to 2022 (collecting 17,588 data points) so far. We Li shows a sharply decreased leaching trend. Meanwhile, when the acid believe this can reveal the persuasive and comprehensive interaction concentration was above 1.5 M, the Li leaching was almost unchanged. mec... |
1-s2_0-S095965262301346X-main | chunk_7 | However, when using the mixed two-acid system, a Some reduced ranges of input features based on partial dependence analysis. larger change in Ni leaching behavior was observed when increasing the Input variables Range concentration of organic acid (2-Acid Conc). Li Co leaching Mn Ni It should be noted that the Li, Co, ... |
1-s2_0-S095965262301346X-main | chunk_8 | Journal of Cleaner Production 410 (2023)137188 features and metal leaching is fully revealed through the partial 3加1 dependence analysis of 20 input features (including raw material properties and technological parameters) and 4 output metal leaching 604 s efficiency. Based on the SVM models, a convenient GUI was devel... |
1-s2_0-S095965262301346X-main | chunk_9 | Li, Y., Lv, W., Huang, H., Yan, W., Li, X., Ning, P., Cao, H., Sun, Z., 2021. Recycling of Schratz, P., Muenchow, J., Iturritxa, E., Richter, J., Brenning, A., 2019. Hyperparameter spent lithium-ion batteries in view of green chemistry. Green Chem. 23, 6139-6171. tuning and performance assessment of statistical and mac... |
1-s2_0-S095965262301346X-main | chunk_10 | Hazard Mater. 406, 124332. material from spent lithium ion batteries by ultrasonic enhanced leaching and one- Zhao, Y., Yuan, X., Jiang, L., Wen, J., Wang, H., Guan, R., Zhang, J., Zeng, G., 2020. step regeneration. J. Environ. Manag. 277, 111426. Regeneration and reutilization of cathode materials from spent lithium-i... |
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