132 citations · 221 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…
DPA-2: a large atomic model as a multi-task learner
Duo Zhang, Xinzijian Liu, Xiangyu Zhang +40
The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demo…