File size: 2,995 Bytes
b7bbbfc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9bd662d
b7bbbfc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
---
configs:
- config_name: default
  data_files: "co/*.parquet"
- config_name: info
  data_files: "ds.parquet"
- config_name: configuration_sets
  data_files: "cs/*.parquet"
- config_name: config_set_mapping
  data_files: "cs_co_map/*.parquet"
license: mit
tags:
- molecular dynamics
- mlip
- interatomic potential
pretty_name: cG-SchNet
---
### <details><summary>Cite this dataset </summary>Gebauer, N. W., Gastegger, M., Hessmann, S. S., Müller, K., and Schütt, K. T. _cG-SchNet_. ColabFit, 2023. https://doi.org/10.60732/de8af6a2</details>  
#### This dataset has been curated and formatted for the ColabFit Exchange  
#### This dataset is also available on the ColabFit Exchange:  
https://materials.colabfit.org/id/DS_xzaglubh0trq_0  
#### Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.  
https://materials.colabfit.org
<br><hr>  
# Dataset  Name  
cG-SchNet  
### Description  
Configurations from a cG-SchNet trained on a subset of the QM9dataset. Model was trained with the intention of providing molecules withspecified functional groups or motifs, relying on sampling of molecularfingerprint data. Relaxation data for the generated molecules is computedusing ORCA software. Configuration sets include raw data fromcG-SchNet-generated configurations, with models trained on several differenttypes of target data and DFT relaxation data as a separate configurationset. Includes approximately 80,000 configurations.  
### Dataset authors  
Niklas W.A. Gebauer, Michael Gastegger, Stefaan S.P. Hessmann, Klaus-Robert Müller, Kristof T. Schütt  
### Publication  
https://doi.org/10.1038/s41467-022-28526-y  
### Original data link  
https://github.com/atomistic-machine-learning/cG-SchNet/  
### License  
MIT  
### Number of unique molecular configurations  
23632  
### Number of atoms  
418729  
### Elements included  
C, F, H, N, O  
### Properties included  
energy  
<br>
<hr>  

# Usage  
- `ds.parquet` : Aggregated dataset information.  
- `co/` directory: Configuration rows each include a structure, calculated properties, and metadata.  
- `cs/` directory : Configuration sets are subsets of configurations grouped by some common characteristic. If `cs/` does not exist, no configurations sets have been defined for this dataset.  
- `cs_co_map/` directory : The mapping of configurations to configuration sets (if defined).  
<br>
#### ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:  
- [Parquet parsing: example code](https://materials.colabfit.org/docs/how_to_use_parquet)  
- [Dataset info schema](https://materials.colabfit.org/docs/dataset_schema)  
- [Configuration schema](https://materials.colabfit.org/docs/configuration_schema)  
- [Configuration set schema](https://materials.colabfit.org/docs/configuration_set_schema)  
- [Configuration set to configuration mapping schema](https://materials.colabfit.org/docs/cs_co_mapping_schema)