141 citations · 181 across the 4 of their papers we have counts for
5 papers
Atomistic prediction of magnetic behaviour across chemistry, structure and temperature
Ruosong Shi, Chengbing Chen, Bicheng Liu +15
Controlling magnetic phases and properties through composition and external conditions is central to the development of magnetic materials. Atomistic foundation models offer a rout…
A Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials
Taiping Hu, Teng Yang, Jianchuan Liu +9
Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dyna…
Deep Learning Illuminates Spin and Lattice Interaction in Magnetic Materials
Teng Yang, Zefeng Cai, Zhengtao Huang +10
Atomistic simulations hold significant value in clarifying crucial phenomena such as phase transitions and energy transport in materials science. Their success stems from the prese…
Direct observation of optically induced transient structures in graphite using ultrafast electron crystallography
Ramani K. Raman, Yoshie Murooka, Chong-Yu Ruan +3
We use ultrafast electron crystallography to study structural changes induced in graphite by a femtosecond laser pulse. At moderate fluences of ~< 21mJ/cm^2, lattice vibrations are…
Interplay between structure and magnetism in nanowires
Teng Yang, Shinya Okano, Savas Berber +1
We investigate the equilibrium geometry and electronic structure of MoSI nanowires using ab initio Density Functional calculations. The skeleton of these unusual…