Antunes, L. M., Vikram, V., Plata, J. J., Powell, A. V., Butler, K. T. and Grau-Crespo, R.
ORCID: https://orcid.org/0000-0001-8845-1719
(2022)
Machine learning approaches for accelerating the discovery of thermoelectric materials.
In: An, Y. (ed.)
Machine Learning in Materials Informatics: Methods and Applications.
American Chemical Society, Washington, DC, pp. 1-32.
ISBN 9780841297630
doi: 10.1021/bk-2022-1416.ch001
Altmetric Badge
| Item Type | Book or Report Section |
| URI | https://centaur.reading.ac.uk/id/eprint/106582 |
| Identification Number/DOI | 10.1021/bk-2022-1416.ch001 |
| Refereed | Yes |
| Divisions | Life Sciences > School of Chemistry, Food and Pharmacy > Department of Chemistry |
| Uncontrolled Keywords | thermoelectric, machine learning, computational chemistry |
| Publisher | American Chemical Society |
| Download/View statistics | View download statistics for this item |
- Published Version
· Restricted to Repository staff only
· The Copyright of this document has not been checked yet. This may affect its availability.
Please see our End User Agreement.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.
University Staff: Request a correction | Centaur Editors: Update this record
Download
Download