Data-driven thermoelectric modeling: Current challenges and prospects-Reference-Cited by-同舟云学术

Data-driven thermoelectric modeling: Current challenges and prospects

Published:2021-11-21 Issue:19 Volume:130 Page:190902
ISSN:0021-8979
Container-title:Journal of Applied Physics
language:en
Short-container-title:Journal of Applied Physics

Author:

Mbaye Mamadou T.¹^ORCID,Pradhan Sangram K.¹^ORCID,Bahoura Messaoud¹²

Affiliation:

1. Center for Materials Research, Norfolk State University, Norfolk, Virginia 23504, USA

2. Engineering Department, Norfolk State University, Norfolk, Virginia 23504, USA

Funder

National Science Foundation

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

https://aip.scitation.org/doi/am-pdf/10.1063/5.0054532

Reference94 articles.

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3. From DFT to machine learning: recent approaches to materials science–a review

4. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

5. National Science and Technology Council (U.S.), Materials Genome Initiative for Global Competitiveness (Executive Office of the President, National Science and Technology Council, Washington, DC, 2011), see http://www.whitehouse.gov/blog/2011/06/24/materials-genome-initiative-renaissance-american-manufacturing

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