我的研究方向主要是应用机器学习相关算法试图去解决金属玻璃及其形成液体的结构与性能间的关联。会编程与分子动力学模拟。
发表文章如下:
[1]Wu J Q, Sun Y T, Wang W H, et al. Application of machine learning approach in disordered materials (in Chinese). Sci Sin-Phys Mech Astron, 2020,50: 067002
[2]J. Q. Wu, H. P. Zhang and M. Z. Li, Common structural basis of short- and long-time relaxation dynamics in metallic glass-forming liquids, Comput. Mater. Sci. 203.111135 (2022).
[3]J. Q. Wu, H. P. Zhang, Y. F. He and M. Z. Li, Unsupervised machine learning study on the structure signature of glass transition in metallic glass-forming system, Acta Mater. 245.118608 (2023).
[4]H. P. Zhang, B. B. Fan, J. Q. Wu, W. H. Wang and M. Z. Li. Universal relationship of boson peak with Debye level and Debye-Waller factor, Phys. Rev. M 4. 095603 (2020).
[5]X. Qin, J. Q. Wu, and M. Z. Li. Atomic structural characteristics and dynamical properties in monatomic metallic liquids via molecular dynamics simulations. arXiv preprint arXiv:2204.01944 (2022).