Inverse design with deep generative models: next step in materials discovery

Authors: Shuaihua Lu, Qionghua Zhou, Xinyu Chen, Zhilong Song, Jinlan Wang

Published: 2022-06-11

DOI: 10.1093/nsr/nwac111

Source: Full article

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Abstract

Data-driven inverse design for inorganic functional materials is a rapidly emerging field, which aims to automatically design innovative materials with target properties and to enable property-to-structure material discovery.