Gault, B.: Atom Probe Tomography to help Understand Deformation Mechanisms in Metallic Alloys. The International Conference on Metallurgical Coatings and Thin Films 2019, San Diego, CA, USA (2019)
Gault, B.: A not-so-brief introduction to atom probe tomography: from fundamentals to atomic-scale insights into engineering materials. Seminar, Imperial College London, London, UK (2019)
Kontis, P.; Cormier, J.; Raabe, D.; Gault, B.: The Role of Chromium and Cobalt Segregation at Dislocations on the γ Dissolution in Nickel Based Superalloys. 18th International Conference on the Strength of Materials (ICSMA 18), Ohio State University, Columbus, OH, USA (2018)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. 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. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.