MORE | Spring 2023

Thermoelectric Material Discovery Using Machine Learning

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The conventional approach of discovering thermoelectric materials from an essentially infinite universe of chemical compounds includes costly and time-consuming studies. In the current study, thermoelectric properties (labels) and descriptors (features) of a group of substances are calculated using density functional theory (DFT) simulations. With the knowledge that machine learning (ML) can extract the key characteristics from the small database and we attempt to use them to predict the behavior of any new compound.

Student researcher

Kevin Coutinho

Mechanical engineering

Hometown: Tempe, Arizona, United States

Graduation date: Spring 2023