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20242026
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cond-mat.mtrl-sci2026

Boron-assisted synthesis of compositionally complex amorphous oxides via short-range-order-constrained generative design

Honglin Li, Chuhao Liu, Yongfeng Guo +19

Engineering short-range atomic order in amorphous materials offers a promising yet still underexplored route to high-performance solids. Here, we establish a boron-assisted amorphi…

cond-mat.mtrl-sci2026

High-Pressure Crystal Structure Database

Zhenyu Wang, Qingchang Wang, Junwen Duan +7

High-pressure research is a productive route to new structures and emergent properties. However, crucial high-pressure structural information remains highly fragmented across indiv…

cond-mat.mtrl-sci2025

Space Group Informed Transformer for Crystalline Materials Generation

Zhendong Cao, Xiaoshan Luo, Jian Lv +1

We introduce CrystalFormer, a transformer-based autoregressive model specifically designed for space group-controlled generation of crystalline materials. By explicitly incorporati…

cond-mat.mtrl-sci2025

CrystalFlow: A Flow-Based Generative Model for Crystalline Materials

Xiaoshan Luo, Zhenyu Wang, Qingchang Wang +4

Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approac…

cond-mat.mtrl-sci2024

Deep learning generative model for crystal structure prediction

Xiaoshan Luo, Zhenyu Wang, Pengyue Gao +4

Recent advances in deep learning generative models (GMs) have created high capabilities in accessing and assessing complex high-dimensional data, allowing superior efficiency in na…