Research Project Description: Huolin Xin’s DeepEM lab focuses their research on the imaging of atoms and their bonding electrons with artificially intelligent transmission electron microscopes. His research group uses state-of-the-art transmission electron microscopy (TEM), electron energy loss spectroscopy, 4D electron diffraction, 3D electron tomography, in-operando liquid cells in conjunction with deep learning and other machine learning algorithms to track and quantify the location, species, crystal phase, and electronic structures of individual atoms inside materials. Potential research projects include:
- Development of deep learning enabled self-driving transmission electron microscopy, and big data mining and analytics.
- Development of in-situ live electron tomography and novel reconstruction techniques for the 3D imaging of dissolution or growth of energy materials in liquids and soft materials/molecules at cryogenic temperatures.
- Development of theories and simulations of fast electron channelling in solid materials and novel imaging techniques based on 4D electron diffraction.
- Identifying cation intermixing and phase transformation in lithium-ion battery cathode materials for making high-energy-density batteries,
- 3D Strain mapping of fuel cell nanocatalysts to understand how their strain profile is connected with their catalytic properties.
Group webpage: https://sites.google.com/view/deepem
The students will learn deep learning tools and tomography. The emphasis will be on data analysis and code development.
In the academic year, the student should commit at least 10 hours per week for research. In order to be financially supported in summer, the students are expected to work full time.
Huolin Xin, 220 Rowland Hall, email@example.com