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Nature Communications • Vol 14 • No 1
An invertible, invariant crystal representation for inverse design of solid-state materials using generative deep learning
November 2023 • Hang Xiao, Rong Li, Xiaoyang Shi, Yan Chen, Liangliang Zhu, Xi Chen, Lei Wang
Abstract The past decade has witnessed rapid progress in deep learning for molecular design, owing to the availability of invertible and invariant representations for molecules such as simplified molecular-input line-entry system (SMILES), which has powered cheminformatics since the late 1980s. However, the design of elemental components and their structural arrangement in solid-state materials to achieve certain desired properties is still a long-standing challenge in physics, chemistry and biology. This is prima…
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