5 papers
Enhancing Materials Discovery with Valence Constrained Design in Generative Modeling
Mouyang Cheng, Weiliang Luo, Hao Tang +6
Diffusion-based deep generative models have emerged as powerful tools for inverse materials design. Yet, many existing approaches overlook essential chemical constraints such as ox…
Benchmarking Universal Machine Learning Interatomic Potentials for Real-Time Analysis of Inelastic Neutron Scattering Data
Bowen Han, Yongqiang Cheng
The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based o…
A Foundation Model for Non-Destructive Defect Identification from Vibrational Spectra
Mouyang Cheng, Chu-Liang Fu, Bowen Yu +5
Defects are ubiquitous in solids and strongly influence materials' mechanical and functional properties. However, non-destructive characterization and quantification of defects, es…
AI-Driven Defect Engineering for Advanced Thermoelectric Materials
Chu-Liang Fu, Mouyang Cheng, Nguyen Tuan Hung +7
Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-off…
Real-time interpretation of neutron vibrational spectra with symmetry-equivariant Hessian matrix prediction
Bowen Han, Pei Zhang, Kshitij Mehta +3
The vibrational behavior of molecules serves as a crucial fingerprint of their structure, chemical state, and surrounding environment. Neutron vibrational spectroscopy provides com…