Issue 35, 2023

Data analytics accelerates the experimental discovery of Cu1−xAgxGaTe2 based thermoelectric chalcogenides with high figure of merit

Abstract

Thermoelectric (TE) materials allow us to harvest energy practically from any heat source, including heat that would be otherwise wasted. This huge promise of energy harvesting is contingent on identifying/designing materials having higher efficiency than presently available ones. However, due to the vastness of the chemical space of materials, only a small fraction of potential candidates has been experimentally and/or computationally scanned thus far. By employing an artificial intelligence (AI) approach based on compressed-sensing symbolic regression analysis of experimental data in an active-learning framework, we have not only identified a trend in the materials composition for superior TE performance, but also predicted and experimentally synthesized several high-performing TE chalcogenides. In particular, p-type Cu0.45Ag0.55GaTe2 shows a very high experimental figure of merit (zT) ∼1.90 at 770 K using experimentally measured heat capacity (Cp). The present work demonstrates not only experimental realization of AI-predicted high-zT TE, but also the importance and potential of physically informed descriptors in material science, particularly for relatively small but well-controlled datasets typically available from experiments.

Graphical abstract: Data analytics accelerates the experimental discovery of Cu1−xAgxGaTe2 based thermoelectric chalcogenides with high figure of merit

Supplementary files

Article information

Article type
Communication
Submitted
07 Jul 2023
Accepted
18 Aug 2023
First published
21 Aug 2023

J. Mater. Chem. A, 2023,11, 18651-18659

Data analytics accelerates the experimental discovery of Cu1−xAgxGaTe2 based thermoelectric chalcogenides with high figure of merit

Y. Zhong, X. Hu, D. Sarker, X. Su, Q. Xia, L. Xu, C. Yang, X. Tang, S. V. Levchenko, Z. Han and J. Cui, J. Mater. Chem. A, 2023, 11, 18651 DOI: 10.1039/D3TA03990K

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements