A new funnel for thermoelectric materials discovery

IF 83.3 1区材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY

Nature Reviews Materials Pub Date : 2026-09-15 DOI:10.1038/s41578-026-00965-9

Giulia Pacchioni

引用次数: 0

Abstract

An article in npj Computational Materials presents a thermoelectric inverse design framework that combines generative artificial intelligence with hierarchical first principles screening to identify previously unknown thermoelectric candidates with promising predicted performance.

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热电材料发现的新漏斗

npj Computational Materials上的一篇文章提出了一种热电逆设计框架，该框架将生成人工智能与分层第一性原理筛选相结合，以识别以前未知的热电候选物，并具有良好的预测性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature Reviews Materials Materials Science-Biomaterials

CiteScore

119.40

自引率

0.40%

发文量

107

期刊介绍： Nature Reviews Materials is an online-only journal that is published weekly. It covers a wide range of scientific disciplines within materials science. The journal includes Reviews, Perspectives, and Comments. Nature Reviews Materials focuses on various aspects of materials science, including the making, measuring, modelling, and manufacturing of materials. It examines the entire process of materials science, from laboratory discovery to the development of functional devices.