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)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
This study investigates the mechanical properties of liquid-encapsulated metallic microstructures created using a localized electrodeposition method. By encapsulating liquid within the complex metal microstructures, we explore how the liquid influences compressive and vibrational characteristics, particularly under varying temperatures and strain…
By using the DAMASK simulation package we developed a new approach to predict the evolution of anisotropic yield functions by coupling large scale forming simulations directly with crystal plasticity-spectral based virtual experiments, realizing a multi-scale model for metal forming.
The aim of this project is to correlate the point defect structure of Fe1-xO to its mechanical, electrical and catalytic properties. Systematic stoichiometric variation of magnetron-sputtered Fe1-xO thin films are investigated regarding structural analysis by transition electron microscopy (TEM) and spectroscopy methods, which can reveal the defect…