Machine learning approaches to identify and design low thermal conductivity oxides for thermoelectric applications

Abhishek Tewari, Siddharth Dixit, Niteesh Sahni, Stéphane P.A. Bordas

Open source

DOI: 10.1017/dce.2020.7
Published: 2020
Container: Data-Centric Engineering
Publisher: Cambridge University Press (CUP)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1017/dce.2020.7,
  title = {Machine learning approaches to identify and design low thermal conductivity oxides for thermoelectric applications},
  author = {Abhishek Tewari and Siddharth Dixit and Niteesh Sahni and Stéphane P.A. Bordas},
  year = {2020},
  journal = {Data-Centric Engineering},
  doi = {10.1017/dce.2020.7},
  url = {https://doi.org/10.1017/dce.2020.7}
}

RIS

TY  - JOUR
TI  - Machine learning approaches to identify and design low thermal conductivity oxides for thermoelectric applications
AU  - Abhishek Tewari
AU  - Siddharth Dixit
AU  - Niteesh Sahni
AU  - Stéphane P.A. Bordas
PY  - 2020
JO  - Data-Centric Engineering
DO  - 10.1017/dce.2020.7
UR  - https://doi.org/10.1017/dce.2020.7
ER  -

APA

Tewari, A., Dixit, S., Sahni, N., & Bordas, S. P. (2020). Machine learning approaches to identify and design low thermal conductivity oxides for thermoelectric applications. Data-Centric Engineering. https://doi.org/10.1017/dce.2020.7

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crossref · retrieved 2026-09-24T20:40:11.221Z