High-Throughput Prediction of the Thermal and Electronic Transport Properties of Large Physical and Chemical Spaces Accelerated by Machine Learning: Charting the ZT of Binary Skutterudites.

ABSTRACT: Thermal and electronic transport properties are the keys to many technological applications of materials. Thermoelectric, TE, materials can be considered a singular case in which not only one but three different transport properties are combined to describe their performance through their TE figure of merit, ZT. Despite the availability of high-throughput experimental techniques, synthesizing, characterizing, and measuring the properties of samples with numerous variables affecting ZT are not a cost- or time-efficient approach to lead this strategy. The significance of computational materials science in discovering new TE materials has been running in parallel to the development of new frameworks and methodologies to compute the electron and thermal transport properties linke

SUBMITTER: Santana-Andreo J 

PROVIDER: S-EPMC10835667 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature