Palm, M.; Sauthoff, G.: Werkstoffcharakterisierung und -optimierung von NiAl–Ta–Cr-Legierungen für Anwendungen im Gasturbinenbau. Werkstoffwoche '98, München, Germany (1998)
Eumann, M.; Palm, M.; Sauthoff, G.: Phase Equilibria in the Ternary Fe–Al–Mo System and Mechanical Properties of Selected Fe–Al–Mo Alloys. Junior Euromat `98, Lausanne, Switzerland (1998)
Palm, M.: Konstitutionsuntersuchungen in den Systemen Ti–Al–X (X = Fe, Cr, Nb) als Grundlage für die Werkstoffentwicklung. 7. DGM Fachausschuß Intermetallische Phasen, Düsseldorf, Germany (1996)
Palm, M.; Inden, G.: Experimentelle Bestimmung der Phasengleichgewichte in den Systemen Fe–Al–Ti und Fe–Al–Cr. 15. Vortragsveranstaltung des DVM Arbeitskreises Rastermikroskopie in der Materialprüfung, Kassel, Germany (1992)
Distl, B.; Palm, M.; Stein, F.; Rackel, M. W.; Hauschildt, K.; Pyczak, F.: Phase equilibria investigations in the ternary Ti–Al–Nb system at elevated temperatures. Intermetallics 2019, Bad Staffelstein, Germany (2019)
Kahrobaee, Z.; Stein, F.; Palm, M.: Experimental evaluation of the isothermal section of the Ti–Al–Zr ternary system at 1273 K. Intermetallics 2019, Bad Staffelstein, Germany (2019)
Jenko, D.; Palm, M.: TEM of Fe-aluminides with additions of Mo, Ti and B. 26th International Conference on Materials and Technology (ICM&T26), Portorož, Slovenia (2018)
Li, X.; Prokopčáková, P.; Palm, M.: Microstructure and mechanical properties of Fe–Al–Ti–B-based alloys with addition of Mo and W. Intermetallics 2013, Educational Center Kloster Banz, Bad Staffelstein, Germany (2013)
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.
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.
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…
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…