activity
20242026
most citedAI-driven inverse design of materials: Past, present and future

72 citations · 108 across the 8 of their papers we have counts for

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Showing cond-mat.mtrl-sciShow all

5 papers · 1 filter

cond-mat.mtrl-sci2026

PhononScore: a phonon-aware scoring function for dynamical stability

Xiao-Qi Han, Ze-Feng Gao, Zhong-Yi Lu

In recent years, crystal generation models have enabled the design of massive numbers of candidate materials. However, the lack of dynamical stability among generated structures ha…

cond-mat.mtrl-sci2026

Bridging Crystal Structure and Material Properties via Bond-Centric Descriptors

Jian-Feng Zhang, Ze-Feng Gao, Xiao-Qi Han +7

Although chemical bonding is the fundamental mechanistic bridge connecting atomic structure to macroscopic material properties, current data-driven materials science largely treats…

cond-mat.mtrl-sci2025

PhononBench:A Large-Scale Phonon-Based Benchmark for Dynamical Stability in Crystal Generation

Xiao-Qi Han, Ze-Feng Gao, Wen-Kao Li +2

In recent years, generative artificial intelligence has made significant advances in the design of crystalline materials, giving rise to approaches based on graph neural networks,…

cond-mat.mtrl-sci2025★ 17 cited

InvDesFlow-AL: active learning-based workflow for inverse design of functional materials

Xiao-Qi Han, Peng-Jie Guo, Ze-Feng Gao +2

Developing inverse design methods for functional materials with specific properties is critical to advancing fields like renewable energy, catalysis, energy storage, and carbon cap…

cond-mat.mtrl-sci2024★ 72 cited

AI-driven inverse design of materials: Past, present and future

Xiao-Qi Han, Xin-De Wang, Meng-Yuan Xu +5

The discovery of advanced materials is the cornerstone of human technological development and progress. The structures of materials and their corresponding properties are essential…