Dongyu Liu
- Research Fellow:HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE) / School of Electronic Engineering
- Dongyu Liu has been at HSE University since 2021.
Education and Degrees
- 2021PhD
- 2016
Bachelor's
Xi’an University 2016-2021 Ph.D., Power Engineering and Engineering Thermophysics, International Research Center for Renewable Energy (IRCRE), State Key Laboratory of Multiphase Flow in Power Engineering (MFPE), Xi'an Jiaotong University, China
2020-2021 Visiting Student, Theoretical Chemistry, Chemistry Department, Yale University, United States
2012-2016 B.E., New Energy Resource Science and Engineering, Shcool of Energy and Power Engineering, Xi'an Jiaotong University, China
20233
- Article Das A., Liu D., Wary R. R., Andrey S. Vasenko, Oleg V. Prezhdo, Nair R. G. Enhancement of Photocatalytic and Photoelectrochemical Performance of ZnO by Mg Doping: Experimental and Density Functional Theory Insights // The Journal of Physical Chemistry Letters. 2023. Vol. 14. No. 18. P. 4134-4141. doi
- Article Liu D., Wu Y., Vasenko A., Prezhdo O. Grain boundary sliding and distortion on a nanosecond timescale induce trap states in CsPbBr3: ab initio investigation with machine learning force field // Nanoscale. 2023. Vol. 15. No. 1. P. 285-293. doi
- Article Wang K., Liu D., Liu L., Li X., Wu H., Sun Z., Li M., Vasenko A., Ding S., Wang F., Xiao C. Isolated Metalloid Tellurium Atomic Cluster on Nitrogen-Doped Carbon Nanosheet for High-Capacity Rechargeable Lithium-CO2 Battery // Advanced Science. 2023. Vol. 10. No. 7. Article 2205959. doi
20224
- Article Liu D., Vasenko A., Perez C. M., Prezhdo O. Ag–Bi Charge Redistribution Creates Deep Traps in Defective Cs2AgBiBr6: Machine Learning Analysis of Density Functional Theory // The Journal of Physical Chemistry Letters. 2022. Vol. 13. No. 16. P. 3645-3651. doi
- Article Wang Z., Zhou Y., Liu D., Qi R., Xia C., Li M., You B., Xia B. Y. Carbon-Confined Indium Oxides for Efficient Carbon Dioxide Reduction in a Solid-State Electrolyte Flow Cell // Angewandte Chemie - International Edition. 2022. Vol. 61. No. 21. Article 202200552. doi
- Article Wu Y., Liu D., Chu W., Wang B., Andrey S. Vasenko, Oleg V. Prezhdo. Fluctuations at Metal Halide Perovskite Grain Boundaries Create Transient Trap States: Machine Learning Assisted Ab Initio Analysis // ACS Applied Materials & Interfaces. 2022. Vol. 14. No. 50. P. 55753-55761. doi
- Article Wang K., Liu D., Liu L., Liu J., Hu X. F., Li P., Li M., Andrey S. Vasenko, Xiao C., Ding S. Tuning the local electronic structure of oxygen vacancies over copper-doped zinc oxide for efficient CO2 electroreduction // eScience. 2022. Vol. 2. No. 5. P. 518-528. doi
Machine Learning Helps Improve Perovskite Solar Cells
A team of researchers from HSE MIEM, LPI RAS, and the University of Southern California have applied machine learning to the analysis of internal defects in perovskite solar cells and proposed ways to improve their energy efficiency. The findings of the study performed on the Cs2AgBiBr6 double perovskite can be used to develop more efficient and durable perovskite-based materials. The paper has been published in the Journal of Physical Chemistry Letters.