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)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.