The machine-learning potential molecular dynamics study of nuclear materials

2021/11-present: Ningbo Institute of Materials Technology and Engineering, CAS, Associate Professor

(1) Junying Zhong, Lei Zhang, Tao Bo*, Active learning-enhanced neuroevolution potential for predictive modeling of UO2 thermophysical properties, Phys. Chem. Chem. Phys., 2025, doi.org/10.1039/D5CP03760C.
(2) Yu-Han Lv, Guang-Ying Li, Lei Zhang, Xiao-Li Tan*, Tao Bo*, Machine Learning-Based Force Field Development and Microstructure-Property Investigation of NaF-BeF2 Molten Salt Fuel, J. Nucl. Mater., 2026, 618, 156201.
(3) Guang-Ying Li, Yu-Han Lv, Li Zhang, Kewei Jiang, Lei Zhang, Yuhui Liu, Xiao-Li Tan*, Tao Bo*, Machine Learning-Driven Exploration of Composition-and Temperature-Dependent Transport and Thermodynamic Properties in LiF-NaF-KF Molten Salts for Nuclear Applications, J. Phys. Chem. B, 2025, 129, 37, 9418-9429.
(4) Tao Bo, Ya Wang, Yingzong Liang, Xinbao Liu, Jun Ren, Hongming Weng, Miao Liu*, Sheng Meng*, High-Throughput Screening of Element-Doped Carbon Nanotubes Toward an Optimal One-Dimensional Superconductor. J. Phys. Chem. Lett., 2021, 12, 6667-6675.
(5) Tao Bo, Peng-Fei Liu, Luo Yan, and Bao-Tian Wang*, Electron-phonon coupling superconductivity in two-dimensional orthorhombic MB6 (M = Mg, Ca, Ti, Y) and hexagonal MB6 (M = Mg, Ca, Sc, Ti). Phys. Rev. Mater., 2020, 4, 114802.