Hybrid Data-Driven Discovery of High-Performance Silver Selenide-Based Thermoelectric Composites.

Shang, Wenjie; Zeng, Minxiang; Tanvir, A N M; Wang, Ke; Saeidi-Javash, Mortaza; Dowling, Alexander; Luo, Tengfei; Zhang, Yanliang

Shang, Wenjie; Zeng, Minxiang; Tanvir, A N M; Wang, Ke; Saeidi-Javash, Mortaza; Dowling, Alexander; Luo, Tengfei; Zhang, Yanliang.

Afiliación

Shang W; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Zeng M; Department of Chemical Engineering, Texas Tech University, Lubbock, TX, 79409, USA.
Tanvir ANM; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Wang K; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Saeidi-Javash M; Department of Mechanical and Aerospace Engineering, California State University Long Beach, Long Beach, CA, 90840, USA.
Dowling A; Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Luo T; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
Zhang Y; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.

Adv Mater ; 35(47): e2212230, 2023 Nov.

Article en En | MEDLINE | ID: mdl-37493182

Palabras clave

Bayesian optimization; composites; machine learning; power factor; thermoelectrics

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Adv Mater Asunto de la revista: BIOFISICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania

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