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    Thermoelectric semiconductor database: DFT-based discovery and experimental validation

    Yujie Xia1,*, Mingran Kong2,*, Pu Miao3,*, Xiangjun Tan4, Shaoqiu Lyu5, Muzhi Wang5, Tiejun Zhu3, Chenguang Fu3,†, and Tiantian Zhang1,‡

    • *These authors contributed equally to this work.
    • †Contact author: chenguang_fu@zju.edu.cn
    • ‡Contact author: ttzhang@itp.ac.cn

    Phys. Rev. B 113, 205203 – Published 11 May, 2026

    DOI: https://doi.org/10.1103/rvcd-66cb

    Abstract

    Thermoelectric (TE) materials enable sustainable bidirectional conversion between heat and electricity, facilitating waste heat recovery and cooling. However, optimizing their performance is challenging due to the intertwined and often competing nature of electronic and thermal transport properties. Although high-throughput screening accelerates discovery, computational costs often limit simultaneous accuracy in both electronic and thermal predictions. Here, we develop a first-principles framework that incorporates key scattering mechanisms for both electrons and phonons and solves the Boltzmann transport equation to compute electronic and lattice thermal transport properties. This approach enables efficient and accurate evaluation of 1136 semiconductors, compiled into an interactive database. Herein, we identify promising TE candidates with band gaps between 0 and 0.8 eV, allowing effective Fermi level tuning. Experimental synthesis of one candidate ScPtSb confirms excellent TE performance, validating our predictive approach. In this work, we provide a robust computational resource and guidance for accelerated development of high-performance TE materials.

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