Bayesian optimization-driven enhancement of the thermoelectric properties of polycrystalline III-V semiconductor thin films
Abstract Studying the properties of thermoelectric materials needs substantial effort owing to the interplay of the trade-off relationships among the influential parameters. In view of this issue, artificial intelligence has recently been used to investigate and optimize thermoelectric materials. He...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-03-01
|
| Series: | NPG Asia Materials |
| Online Access: | https://doi.org/10.1038/s41427-024-00536-w |