6 papers
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…
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…
OpenCSP: A Deep Learning Framework for Crystal Structure Prediction from Ambient to High Pressure
Yinan Wang, Xiaoyang Wang, Zhenyu Wang +3
High-pressure crystal structure prediction (CSP) underpins advances in condensed matter physics, planetary science, and materials discovery. Yet, most large atomistic models are tr…
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…
Discovery of High-Temperature Superconducting Ternary Hydrides via Deep Learning
Xiaoyang Wang, Chengqian Zhang, Zhenyu Wang +5
The discovery of novel high-temperature superconductor materials holds transformative potential for a wide array of technological applications. However, the combinatorially vast ch…
Data-driven design of high-temperature superconductivity among ternary hydrides under pressure
Bowen Jiang, Xiaoshan Luo, Toshiaki Iitaka +6
Recently, ternary clathrate hydrides are promising candidates for high-temperature superconductor. However, it is a formidable challenge to effectively hunt high-temperature superc…