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20192026
most citedGenerative adversarial networks (GAN) based efficient sampling of chemical space for inverse design of inorganic materials

294 citations · 458 across the 10 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

cond-mat.mtrl-sci2024★ 6 cited

Accelerating Discovery of Extreme Lattice Thermal Conductivity by Crystal Attention Graph Neural Network (CATGNN) Using Chemical Bonding Intuitive Descriptors

Mohammed Al-Fahdi, Riccardo Rurali, Jianjun Hu +2

Designing materials with targeted lattice thermal conductivity (LTC) demands electronic-level insight into chemical bonding. We introduce two bonding descriptors, namely normalized…

cond-mat.mtrl-sci2024★ 1 cited

Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study

Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong +2

In real-world material research, machine learning (ML) models are usually expected to predict and discover novel exceptional materials that deviate from the known materials. It is…