Ahmad, S.; Liebscher, C.; Dehm, G.: Exploration of atomic structures in Σ3 [111] Al tilt grain boundaries. Sixth Conference on Frontiers of Aberration Corrected Electron Microscopy PICO 2021, virtual, Kasteel Vaalsbroek, The Netherlands (2021)
Ahmad, S.; Liebscher, C.; Dehm, G.: Strain-Induced phase transition in Σ3 [111] (211) tilt grain boundaries in Al. Microscopy conference Joint Meeting of Dreiländertagungn & Multinational Congress on Microscopy MC 2021, virtual, Vienna, Austria (2021)
Ahmad, S.; Meiners, T.; Frolov, T.; Liebscher, C.; Dehm, G.: Grain boundary structure and phase transitions in Cu and Al [111] tilt grain boundaries. International Workshop on Advanced and In-situ Microscopies of Functional Nanomaterials and Devices, IAMNano, Düsseldorf, Germany (2019)
Ahmad, S.: Fundamental investigation of the atomic structures of [111] tilt grain boundaries, their defects and segregation behaviour in pure and alloyed Al. Dissertation, Ruhr-Universität Bochum (2023)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
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
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.