Description
The entire data supports the research publication and can be divided in 3 parts:
1. Training data (Raw PXRD and DSC data and its description of the labelling contained in the Documentation.zip);
2. Excel-files that are the input of the algorithm (Results.xlsx contains reaction outcomes/ Chem.xlsx contains all chemical descriptors for used molecules; both are in the Documentation.zip);
3. Code (Python algorithm that uses the excel-files from the previous point to generate predictive capabilities).
1. Training data (Raw PXRD and DSC data and its description of the labelling contained in the Documentation.zip);
2. Excel-files that are the input of the algorithm (Results.xlsx contains reaction outcomes/ Chem.xlsx contains all chemical descriptors for used molecules; both are in the Documentation.zip);
3. Code (Python algorithm that uses the excel-files from the previous point to generate predictive capabilities).
| Date made available | 25 Jan 2022 |
|---|---|
| Publisher | University of Bath |
Research output
- 1 Article
-
Intelligent Mechanochemical Design of Co-Amorphous Mixtures
Gröls, J. R. & Castro Dominguez, B., 4 May 2022, In: Crystal Growth and Design. 22, 5, p. 2989-2996 8 p.Research output: Contribution to journal › Article › peer-review
Open Access17 Link opens in a new tab Citations (SciVal)
Cite this
- DataSetCite