Woods, E.; Aota, L. S.; Schwarz, T.; Kim, S.-H.; Douglas, J. O.; Singh, M. P.; Gault, B.: In-situ cryogenic protective layers and metal coatings in cryogenic FIB. IMC20 - 20th International Microscopy Congress - Pre-congress workshop, Cryogenic Atom Probe Tomography, Busan, South Korea (2023)
Schwarz, T.: Atom probe tomography: from water to complex liquids to the application of studying liquid-solid interfaces at the near atomic level. APT&M 23, Leuven, Belgium (2023)
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)
Schwarz, T.; Woods, E.; Aota, L. S.; Zhou, X.; McCaroll, I.; Gault, B.: Application of cryo-atom probe tomography to study early-stage corrosion mechanism at liquid-solid interfaces at near atomic scale. EuroCorr 2023, Bruessles, Belgium (2023)
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
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…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
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.