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)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
The aim of the work is to develop instrumentation, methodology and protocols to extract the dynamic strength and hardness of micro-/nano- scale materials at high strain rates using an in situ nanomechanical tester capable of indentation up to constant strain rates of up to 100000 s−1.