Gault, B.: Full determination of 3D atomic position by combining APT & EM. Scientific Directions for Future TEM, Forschungszentrum Jülich, Jülich, Germany (2016)
Gault, B.; Katnagallu, S.: Atom probe microscopy: a new playground for big data analysis? Workshop Big-Data-Driven Materials Science, Ringberg Castle, Rottach, Germany (2016)
Gault, B.; De Geuser, F.: A perspective on the ion projection in field ion & atom probe microscopy. Atom Probe Tomography & Microscopy 2016, Gyeongju, South Korea (2016)
Raabe, D.; Choi, P.-P.; Gault, B.; Ponge, D.; Yao, M.; Herbig, M.: Segregation engineering for self-organized nanostructuring of materials - from atoms to properties? APT&M 2016 - Atom Probe Tomography & Microscopy 2016 (55th IFES) , Gyeongju, South Korea (2016)
Kuzmina, M.; Gault, B.; Herbig, M.; Ponge, D.; Sandlöbes, S.; Raabe, D.: From grains to atoms: ping-pong between experiment and simulation for understanding microstructure mechanisms. Res Metallica Symposium, Department of Materials Engineering, KU Leuven, Leuven, The Netherlands (2016)
Herbig, M.; Ponge, D.; Gault, B.; Borchers, C.; Raabe, D.: Segregation and phase transformation at dislocations during aging in a Fe-9%Mn steel studied by correlative TEM-atom probe tomography. MSE 2014, Darmstadt, Germany (2014)
Schwarz, T.; Yang, J.; Aota, L. S.; Woods, E.; Zhou, X.; Neugebauer, J.; Todorova, M.; McCaroll, I.; Gault, B.: Analysis of the reactive solid-liquid interface during the corrosion of magnesium at the near atomic level using cryo-atom probe tomography. Aqueous Corrosion Gordon Research Conference (GRC) 2024, Corrosion Challenges and Opportunities for the Energy Transition, New London, CT, USA (2024)
Schwarz, T.; Yang, J.; Aota, L. S.; Woods, E.; Zhou, X.; Neugebauer, J.; Todorova, M.; McCaroll, I.; Gault, B.: Analysis of the reactive solid-liquid interface during the corrosion of magnesium at the near atomic level using cryo-atom probe tomography. Aqueous Corrosion Gordon Research Seminar (GRS) 2024, Corrosion Monitoring, Modelling and Mitigation Towards a Sustainable Future, New London, CT, USA (2024)
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
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.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.