我的研究方向主要是應(yīng)用機器學(xué)習(xí)相關(guān)算法試圖去解決金屬玻璃及其形成液體的結(jié)構(gòu)與性能間的關(guān)聯(lián)。會編程與分子動力學(xué)模擬。
發(fā)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).