Combining machine-learning models with first-principles high-throughput calculations to accelerate the search for promising thermoelectric materials
From high-throughput screening of high-power-factor materials, through first-principles calculation of transport properties, to training machine-learning models for identifying good thermoelectric materials.
Authors
- Artem R. Oganov (ORCID: https://orcid.org/0000-0001-7082-9728)
- Tao Fan (ORCID: https://orcid.org/0000-0002-9555-6604)
Institutions
- Skolkovo Institute of Science and Technology (RU)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1039/d4tc03403a
- Citations
- 12
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 1.41
Funders
- Russian Science Foundation