Dataset Open Access
Data of "Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning"
Roet, Sander;
Daub, Christopher D;
Riccardi, Enrico
This is the data and assosiated in-house code for the paper:
Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning
Sander Roet, Christopher D. Daub, and Enrico Riccardi
Journal of Chemical Theory and Computation 2021 17 (10), 6193-6202
DOI: 10.1021/acs.jctc.1c00458
Files
(12.8 GB)
| Name | Size | |
|---|---|---|
|
Chemistrees.zip
md5:037a9e5349e4c3bad3e429fd78885129 |
12.8 GB | Download |
67
7
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 67 | 67 |
| Downloads | 7 | 7 |
| Data volume | 89.5 GB | 89.5 GB |
| Unique views | 60 | 60 |
| Unique downloads | 7 | 7 |
Indexed in
- Publication date:
- September 24, 2021
- DOI:
-
- Keyword(s):
- simulation data
- Published in:
- Journal of Chemical Theory and Computation: 17 pp. 6193-6202 (10).
- Related identifiers:
- Documented by
- 10.1021/acs.jctc.1c00458 (Journal article)
- License (for files):
- Creative Commons Attribution 4.0 International