Kanjilal, A.; Best, J. P.; Dehm, G.: Investigation of Intermetallic-Mg interface strength using in-situ microshear testing. Nanomechanical Testing in Materials Research and Development IX, Sicily, Italy (2024)
Lee, J. S.; Dehm, G.; Best, J. P.; Stein, F.: Mechanical properties of B2 FeAl as a function of composition using targeted nanoindentation on diffusion couples. ECI Conference on Nanomechanical Testing in Materials Research and Development, Giardini Naxos, Messina (Sicily), Italy (2024)
Sahu, S.; Dehm, G.; Best, J. P.: High Temperature micropillar compression of Hematite: Insights and experimental challenges. Materials Research and Development IX ECI, Messina (Sicily), Italy (2024)
Riedel, J. L.; Kauffmann, A.; Nizamoglu, S.; Guth, S.; Best, J. P.; Lee, J. S.; Stein, F.; Heilmaier, M.: Application of a novel testing scheme for single-specimen brittle-to-ductile-transition temperature determination to Iron-Aluminides. MSE 2024, Darmstadt, Germany (2024)
Bhat, M. K.; Frommeyer, L.; Prithiv, T. S.; Dehm, G.; Best, J. P.: Using small-scale mechanics to probe the origins of segregation-induced strengthening. Nanomechanical Testing in Materials Research and Development VIII, Split, Croatia (2022)
Rehman, U.; Tian, C.; Stein, F.; Best, J. P.; Dehm, G.: Fracture Toughness of the Intermetallic C15 Al2Ca Laves Phase Determined using a Micropillar Splitting Technique. Intermetallics 2021, Educational Center Kloster Banz, Bad Staffelstein, Germany (2021)
Brognara, A.; Best, J. P.; Djemia, P.; Faurie, D.; Ghidelli, M.; Dehm, G.: On the mechanical properties and thermal stability of ZrxCu100-x thin film metallic glasses with different compositions. Nanobrücken 2021 - Nanomechanical Testing Conference virtual event, Düsseldorf, Germany (2021)
Brognara, A.; Best, J. P.; Djemia, P.; Faurie, D.; Ghidelli, M.; Dehm, G.: Effect of composition on mechanical properties and thermal stability of ZrCu thin film metallic glasses. European Materials Research Society (E-MRS) Spring Meeting 2021, Virtual Conference, Strasbourg, France (2021)
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
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.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
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.
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…