976 citations · 1.6k across the 10 of their papers we have counts for
10 papers
Multi-scale Investigation of Chemical Short-Range Order and Dislocation Glide in the MoNbTi and TaNbTi Refractory Multi-Principal Element Alloys
Hui Zheng, Lauren T. W. Fey, Xiang-Guo Li +6
Refractory multi-principal element alloys (RMPEAs) are promising materials for high-temperature structural applications. Here, we investigate the role of chemical short-range order…
Accelerating Materials Discovery with Bayesian Optimization and Graph Deep Learning
Yunxing Zuo, Mingde Qin, Chi Chen +4
Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equi…
Bridging the Gap Between Simulated and Experimental Ionic Conductivities in Lithium Superionic Conductors
Ji Qi, Swastika Banerjee, Yunxing Zuo +5
Lithium superionic conductors (LSCs) are of major importance as solid electrolytes for next-generation all-solid-state lithium-ion batteries. While molecular dynamics…
Learning Properties of Ordered and Disordered Materials from Multi-fidelity Data
Chi Chen, Yunxing Zuo, Weike Ye +2
Predicting the properties of a material from the arrangement of its atoms is a fundamental goal in materials science. While machine learning has emerged in recent years as a new pa…
Complex Strengthening Mechanisms in the NbMoTaW Multi-Principal Element Alloy
Xiang-Guo Li, Chi Chen, Hui Zheng +2
Refractory multi-principal element alloys (MPEAs) have exceptional mechanical properties, including high strength-to-weight ratio and fracture toughness, at high temperatures. Here…
A Performance and Cost Assessment of Machine Learning Interatomic Potentials
Yunxing Zuo, Chi Chen, Xiangguo Li +8
Machine learning of the quantitative relationship between local environment descriptors and the potential energy surface of a system of atoms has emerged as a new frontier in the d…
Grain Boundary Properties of Elemental Metals
Hui Zheng, Xiang-Guo Li, Richard Tran +5
The structure and energy of grain boundaries (GBs) are essential for predicting the properties of polycrystalline materials. In this work, we use high-throughput density functional…
Anisotropic work function of elemental crystals
Richard Tran, Xiang-Guo Li, Joseph Montoya +3
The work function is a fundamental electronic property of a solid that varies with the facets of a crystalline surface. It is a crucial parameter in spectroscopy as well as materia…
An Electrostatic Spectral Neighbor Analysis Potential (eSNAP) for Lithium Nitride
Zhi Deng, Chi Chen, Xiang-Guo Li +1
Machine-learned interatomic potentials based on local environment descriptors represent a transformative leap over traditional potentials based on rigid functional forms in terms o…
Quantum-Accurate Spectral Neighbor Analysis Potential Models for Ni-Mo Binary Alloys and FCC Metals
Xiang-Guo Li, Chongze Hu, Chi Chen +3
In recent years, efficient inter-atomic potentials approaching the accuracy of density functional theory (DFT) calculations have been developed using rigorous atomic descriptors sa…