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Qiang Zhu

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Preprint Oct 2026

EpNet-Si: Atomic Form Factors Learned from Band Structures

The empirical pseudopotential method (EPM) computes band structures with one diagonalization per $k$ point and no self-consistency, but its fixed atomic form factors do not transfer between crystal structures. To address this limitation, we introduce EpNet-Si, an EPM for silicon in which an equivariant network predicts...

Qiang Zhu · 0 citations
Preprint Oct 2026

Molecular Crystal Structure Prediction from Conditional Flow on the Unit Cells

A molecular crystal structure is jointly described by its space group symmetry, unit cell, and the molecular alignment within the asymmetric unit. Concurrently predicting all three variables is a daunting task, as it mixes discrete symmetry choices with a high-dimensional search in the continuous space. To address this...

Qiang Zhu, Yi-Han Weng · 0 citations
Preprint Aug 2026

High-throughput Discovery of Magnetic Rare Earth Transition Metal Alloys

We present an accelerated materials discovery framework that combines diffusion-based crystal structure generation with hierarchical screening to identify new rare-earth--transition-metal magnets simultaneously achieving high magnetization and thermodynamic stability. Using this workflow, we systematically explored ove...

S. Tao, Osman Goni Ridwan, Li-Qin Ke et al. · 0 citations
#machine learning Preprint Aug 2026

CrystalGRPO: Target-Aligned and Coverage-Preserving Reinforcement Learning for Flow-Based Crystal Structure Prediction

This work introduces CrystalGRPO, a CSP-aligned post-training framework that extends existing ODE-to-SDE policy constructions to the joint coordinate--lattice state and provides two operating modes: CrystalGRPO-Q, which prioritizes single-draw recovery, and CrystalGRPO-C, which combines full-trajectory reference regula...

Kaixiang Su, Hongfei Xue, Qiang Zhu · 0 citations

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