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

15 citations · 16 across the 7 of their papers we have counts for

collaborators

10 papers

cond-mat.supr-con2026

Screening phonon-mediated superconductors from static orbital Hamiltonians

Jian-Feng Zhang, Ze-Feng Gao, Xiao-Qi Han +6

The first-principles search for superconductors is severely limited by the high cost of electron-phonon coupling (EPC) calculations. Here we develop a low-cost, physically transpar…

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.str-el2026

NQS-Agent: Health-Aware Agentic Hyperparameter Optimization for Neural-Network Quantum States

Jia-Qi Wang, Xiao-Qi Han, Ze-Feng Gao +2

Neural-network quantum states (NQS) provide expressive variational representations for strongly correlated quantum many-body systems, but their practical accuracy depends sensitive…

cond-mat.mtrl-sci2026

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.supr-con20261 cited

HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction

Xiao-Qi Han, Ze-Feng Gao, Xin-De Wang +3

The discovery of high-temperature superconducting materials holds great significance for human industry and daily life. In recent years, research on predicting superconducting tran…

cond-mat.mtrl-sci202615 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…