共 50 条
- [1] Simulating complex inorganic materials for energy applications with machine-learning potentials [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 257
- [3] Strategies for the construction of machine-learning potentials for accurate and efficient atomic-scale simulations [J]. MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2021, 2 (03):
- [5] Machine-learning potentials for crystal defects [J]. MRS COMMUNICATIONS, 2022, 12 (05) : 510 - 520
- [8] Machine-learning strategies for the accurate and efficient analysis of x-ray spectroscopy [J]. MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2024, 5 (02):
- [9] Exploring diffusion behavior of superionic materials using machine-learning interatomic potentials [J]. PHYSICAL REVIEW MATERIALS, 2024, 8 (04):
- [10] Intricate short-range order in GeSn alloys revealed by atomistic simulations with highly accurate and efficient machine-learning potentials [J]. PHYSICAL REVIEW MATERIALS, 2024, 8 (04):