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)
Polin, N.; Giron, S.; Adabifiroozjaei, E.; Yang, Y.; Saxena, A.; Gutfleisch, O.; Gault, B.: Atomic‐scale insights to design of high‐performing SmCo based sintered permanent magnets gained by atom probe tomography. 12th International Conference on Magnetic and Superconducting Materials (MSM22), Duisburg, Germany (2022)
Gault, B.: Pushing the analytical limits of atom probe tomography via cryo-enabled workflows. Microscience Microscopy Congress 2021, online, Oxford, UK (2021)
Gault, B.; Guillon, O.: Du térawatt au picomètre: Voyage au cœur des technologies de l’hydrogène. Café des Sciences de l’Ambassade de France en Allemagne, online, Berlin, Germany (2021)
Gault, B.: Advancing corrosion understanding with (cryo-) Atom Probe Tomography. Imperial College London - Rolls Royce corrosion seminar, online, London, UK (2021)
Gault, B.: Machine-Learning for Atom Probe Tomography. Workshop 'Research-data management, machine learning and material informatics for Superalloys', online, Bochum, Germany (2021)
Gault, B.: Introduction to atom probe tomography: performance and opportunities in characterizing microstructures. Metallic Microstructures: European Lectures Online (2021)
International researcher team presents a novel microstructure design strategy for lean medium-manganese steels with optimized properties in the journal Science
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization as in micropillar compression. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one.…