Ahmad, S.; Brink, T.; Liebscher, C.; Dehm, G.: Influence of variation in grain boundary parameters on the evolution of atomic structure and properties of [111] tilt boundaries in aluminum. Acta Materialia 268, 119732 (2024)
Brink, T.; Langenohl, L.; Ahmad, S.; Liebscher, C.; Dehm, G.: Atomistic Modeling of the Thermodynamics of Grain Boundaries in fcc Metals. 19th International Conference on Diffusion in Solids and Liquids, Crete, Greece (2023)
Ahmad, S.; Liebscher, C.; Dehm, G.: To decipher the novel atomic structure of [111] tilt grain boundaries in Al. Material Science and Engineering Congress - MSE 2020, virtual, Darmstadt, Germany (2020)
Saood, S.; Liebscher, C.; Dehm, G.: Observing the atomic structure of high angle [111] tilt grain boundaries in Al. Materials Science and Engineering Congress MSE 2020, virtual (2020)
Saood, S.; Brink, T.; Liebscher, C.; Dehm, G.: Atomic structure of [111] tilt boundaries of Al in relation to their crystallographic parameters. International Microscopy Conference 2023 (IMC-20), Busan, South Korea (2023)
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)
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.
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…