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Development of an atomic cluster expansion potential for iron and its oxides

铁及其氧化物原子团簇扩展势的开发

Baptiste Bienvenu,Mira Todorova,Jörg Neugebauer et al.

npj computational materials. 2025;11(1):81. DOI:10.1038/s41524-025-01574-w

Constructing multicomponent cluster expansions with machine-learning and chemical embedding

利用机器学习和化学嵌入构建多组分团展开

Yann L Müller,Anirudh Raju Natarajan

npj computational materials. 2025;11(1):60. DOI:10.1038/s41524-025-01543-3

A machine-learning framework for accelerating spin-lattice relaxation simulations

加速自旋晶格弛豫模拟的机器学习框架

Valerio Briganti,Alessandro Lunghi

npj computational materials. 2025;11(1):62. DOI:10.1038/s41524-025-01547-z

Outlier-detection for reactive machine learned potential energy surfaces

反应式机器学习势能面中的异常值检测

Luis Itza Vazquez-Salazar,Silvan Käser,Markus Meuwly

npj computational materials. 2025;11(1):33. DOI:10.1038/s41524-024-01473-6

Effect of Hubbard U-corrections on the electronic and magnetic properties of 2D materials: a high-throughput study

Hubbard U校正对二维材料电子和磁性性质的影响：一种高通量研究方法

Sahar Pakdel,Thomas Olsen,Kristian S Thygesen

npj computational materials. 2025;11(1):18. DOI:10.1038/s41524-024-01503-3

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