2 papers
cond-mat.mtrl-sci2024
SpinMultiNet: Neural Network Potential Incorporating Spin Degrees of Freedom with Multi-Task Learning
Koki Ueno, Satoru Ohuchi, Kazuhide Ichikawa +2
Neural Network Potentials (NNPs) have attracted significant attention as a method for accelerating density functional theory (DFT) calculations. However, conventional NNP models ty…
physics.comp-ph2024
Shotgun crystal structure prediction using machine-learned formation energies
Chang Liu, Hiromasa Tamaki, Tomoyasu Yokoyama +5
Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configuration…