Thissen, P.; Özcan, Ö.; Diesing, D.; Grundmeier, G.: Monte Carlo Simulation of Temperature Programmed Desorption Including Binding Energies and Frequency Factors Derived by DFT Calculations. 43rd Symposium on Theoretical Chemistry, Saarbrücken, Germany (2007)
Thissen, P.; Giza, M.; Grundmeier, G.: Adsorptionskinetik von Organophosphonsäure auf plasmamodifizierten Aluminiumoberflächen. 13. Bundesdeutsche Fachtagung für Plasmatechnologie, Bochum, Germany (2007)
Thissen, P.: Adsorption and Self-Organization of Organophosphonic Monolayers on Modi ed Oxide Covered Surfaces. Dissertation, Universitat Paderborn, Fakultät für Naturwissenschaften, Paderborn, Germany (2009)
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
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.