Zhao, Y.; Fantin, A.; Li, Y.; Li, T.; Gong, Y.: Quantifying chemical short-range order and local lattice distortion in Ti–Zr–Nb alloys. DPG Spring Meeting of the Condensed Matter Section, Dresden, Germany (2026)
Li, Y.; Gault, B.: Machine Learning-enabled Tomographic Imaging of Chemical Short-range Order in Fe-based Solid-solutions. DPG 2024, Berlin, Germany (2024)
Li, Y.; Gault, B.: Machine Learning-enabled Tomographic Imaging of Chemical Short-range Order in Fe-based Solid-solutions. TMS 2024, Orlando, FL, USA (2024)
Li, Y.; Gault, B.: Quantitative three-dimensional imaging of chemical short-range order via machine learning enhanced atom probe tomography. BiGmax Spring Meeting 2022, Bochum, Germany (2022)
This project targets to exploit or develop new methodologies to not only visualize the 3D morphology but also measure chemical distribution of as-synthesized nanostructures using atom probe tomography.
The mission of our group is to uncover the fundamental mechanisms of deformation and degradation in battery systems and to leverage mechanical principles to design damage-resilient energy storage systems.
Here the focus lies on investigating the temperature dependent deformation of material interfaces down to the individual microstructural length-scales, such as grain/phase boundaries or hetero-interfaces, to understand brittle-ductile transitions in deformation and the role of chemistry or crystallography on it.
The full potential of energy materials can only be exploited if the interplay between mechanics and chemistry at the interfaces is well known. This leads to more sustainable and efficient energy solutions.
In order to develop more efficient catalysts for energy conversion, the relationship between the surface composition of MXene-based electrode materials and its behavior has to be understood in operando. Our group will demonstrate how APT combined with scanning photoemission electron microscopy can advance the understanding of complex relationships…