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Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe

, , , and . npj Computational Materials, 8 (1): 13 (Jan 25, 2022)
DOI: 10.1038/s41524-022-00696-9

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Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe, , , and . npj Computational Materials, 8 (1): 13 (Jan 25, 2022)Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe, , , and . npj computational materials, 8 (1): 13 (2022)Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution., , , , , and . Comput. Phys. Commun., (2021)Constrained DFT-based magnetic machine-learning potentials for magnetic alloys : a case study of Fe-Al, , , , , and . Scientific reports, 13 (1): 19728 (2023)Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials : A MTP/ShengBTE solution, , , , , and . Computer physics communications, (2020)Exploring phononic properties of two-dimensional materials using machine learning interatomic potentials, , , , , , and . Applied materials today, 20 (September): 100685 (2020)Fitting to magnetic forces improves the reliability of magnetic Moment Tensor Potentials, , , , , , and . Computational materials science, 245 (October): 113331 (2024)