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yijin.liu@austin.utexas.edu
Office Location: ETC 9.174
Yijin Liu
Associate Professor
Department Research Areas:
Dr. Yijin Liu received his B.S. (2004) and Ph.D. (2009) degrees in Optics from the Physics Department at the University of Science & Technology of China (USTC, Hefei, China). He joined Stanford University (Stanford, CA, USA) as a postdoctoral scholar in 2009 and became an Associate Staff Scientist at the SLAC National Accelerator Laboratory in 2012, a Staff Scientist in 2015, and a Lead Scientist in 2020. In August 2023, Prof. Liu joined the Walker Department of Mechanical Engineering at UT Austin as an Associate Professor.
In his previous role as a National Lab Scientist, Dr. Liu led the technical developments and scientific applications for the Transmission X-ray Microscopy program at SLAC/Stanford. With over 15 years of experience in this field, Dr. Liu has developed and broadly applied X-ray characterization methods for scientific research in renewable energy science, industry catalysis, oil production, and material under extreme conditions.
In more recent years, Dr. Liu’s research focused on studying energy storage materials using high-throughput experimental methods as well as the associated machine learning and data mining approaches. Specific areas of focus include battery manufacturing, safety, degradation, and failure analysis.
Recent Publications
- Jizhou Li, Yijin Liu et al., “Dynamics of particle network in composite battery cathodes,” Science, DOI: 10.1126/science.abm8962 (2022).
- Guibin Zan, Yijin Liu et al., "In situ visualization of multi-components coevolution in a battery pouch cell," PNAS 119 (29), e2203199119 (2022).
- Shaofeng Li, Yijin Liu et al., "Thermal-healing of lattice defects for high-energy single-crystalline battery cathodes," Nature Communications, DOI:10.1038/s41467-022-28325-5 (2022).
- Jin Zhang, Yijin Liu et al., “Depth-dependent valence stratification driven by oxygen redox in lithium-rich layered oxide,” Nature Communications 11, 6342 (2020).
- Zhisen Jiang, Yijin Liu et al., "Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes", Nature Communications 11, 2310 (2020).