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My major research interest is using physical insights to develop intelligent models that can learn from large data sets.
At present, I am enrolling in the research project of “Next generation solid-state batteries” funded by the Faraday Institution, and working on the application of machine learning method in battery degradation. I'm also interested in the theoretical design of functional materials, such as high temperature superconductors and inorganic electrides, with the combination of machine learning and density functional theory methods.
Jiao, Y., Wu, W. Ma, F., Yu, Z., Lu, Y., Sheng, X., Zhang, Y., Yang, S. (2019). Room Temperature Magnetism and Strong Magnetic Anisotropy in Two-Dimensional Iron Arsenides. Nanoscale, 2019, 11(35): 16508-16514
Zhang, Y., Wang, H., Wang, Y., Zhang, L., & Ma, Y. (2017). Computer-assisted inverse design of inorganic electrides. Physical Review X, 7(1), 011017
Zhang, Y., Wu, W., Wang, Y., Yang, S. A., & Ma, Y. (2017). Pressure-stabilized semiconducting electrides in alkaline-earth-metal subnitrides. Journal of the American Chemical Society, 139(39), 13798-13803
Errea, I., Calandra, M., Pickard, C.J., Nelson J. R., Needs, R. J., Li, Y., Liu, H., Zhang, Y., Ma, Y., Mauri, F. (2016). Quantum hydrogen-bond symmetrization in the superconducting hydrogen sulfide system. Nature 532, 81
Li, Y., Wang, L., Liu, H., Zhang, Y., Hao, J., Pickard, C. J., ... & Errea, I. (2016). Dissociation products and structures of solid H2S at strong compression. Physical Review B, 93(2), 020103