5 papers
A New Workflow for Materials Discovery Bridging the Gap Between Experimental Databases and Graph Neural Networks
Brandon Schoener, Yuting Hu, Pasit Wanlapha +6
Incorporating Machine Learning (ML) into material property prediction has become a crucial step in accelerating materials discovery. A key challenge is the severe lack of training…
Electron Localization in Non-Compact Covalent Bonds Captured by the r2SCAN+V Approach
Yubo Zhang, Da Ke, Rohan Maniar +4
In density functional theory, the SCAN (Strongly Constrained and Appropriately Normed) and r2SCAN functionals significantly improve over generalized gradient approximation function…
Out-of-plane displacement of quantum color centers in monolayer h-BN
Zhao Tang, Fanhao Jia, Greis J. Kim-Reyes +3
Color centers exhibiting deep-level states within the wide bandgap h-BN monolayer possess substantial potential for quantum applications. Uncovering precise geometric characteristi…
Efficiently charting the space of mixed vacancy-ordered perovskites by machine-learning encoded atomic-site information
Fan Zhang, Li Fu, Weiwei Gao +2
Vacancy-ordered double perovskites (VODPs) are promising alternatives to three-dimensional lead halide perovskites for optoelectronic and photovoltaic applications. Mixing these ma…
Quasiparticle and Excitonic Structures of Few-layer and Bulk GaSe: Interlayer Coupling, Self-energy, and Electron-hole Interaction
Fanhao Jia, Zhao Tang, Greis J. Cruz +4
Metal monochalcogenide GaSe is a classic layered semiconductor that has received increasing research interest due to its highly tunable electronic and optical properties for ultrat…