Combining electronic and structural features in machine learning models to predict organic solar cells properties
- Submitting institution
-
The University of Liverpool
- Unit of assessment
- 8 - Chemistry
- Output identifier
- 11345
- Type
- D - Journal article
- DOI
-
10.1039/c8mh01135d
- Title of journal
- MATERIALS HORIZONS
- Article number
- -
- First page
- 343
- Volume
- 6
- Issue
- 2
- ISSN
- 2051-6347
- Open access status
- Exception within 3 months of publication
- Month of publication
- -
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 40
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
