Vlasak, R.; Klueppel, I.; Grundmeier, G.: Combined EIS and FTIR-ATR study of water uptake and diffusion in polymer films on semiconducting electrodes. Electrochim. Acta 52 (28), pp. 8075 - 8080 (2007)
Posner, R.; Giza, G.; Vlasak, R.; Grundmeier, G.: Electrochemical and Spectroscopic Analysis of Ion Transport Processes along Polymer/Oxide/Metal Interfaces in Corrosive and Non-Corrosive Atmosphere. Euradh 2008 - Adhesion '08, St Catherine's College, Oxford, UK (2008)
Grundmeier, G.; Valtiner, M.; Vlasak, R.: Adhesion promoting films and monolayers at polymer/oxide/metal interfaces. NACE2008 RIP Session Coatings and Inhibitors, New Orleans, LA, USA (2008)
Grundmeier, G.; Posner, R.; Vlasak, R.: Combined Spectroscopic and Electrochemical Studies of Water and Ion Transport along Polymer/Oxide/Metal Interphases. ECASIA 2007, 12th European Conference on Applications of Surface and Interface Analysis, Brussels-Flggey, Belgium (2007)
Grundmeier, G.; Fink, N.; Giza, M.; Popova, V.; Vlasak, R.; Wapner, K.: Application of combined spectroscopic, electrochemical and microscopic techniques for the understanding of adhesion and de-adhesion at polymer/metal interfaces. 24. Spektrometertagung, Dortmund, Germany (2005)
Vlasak, R.; Grundmeier, G.: Surface-Enhanced Infrared Spectroscopy of Ultra-Thin Inorganic and Organic Films. 104. Hauptversammlung der Deutschen Bunsen-Gesellschaft für Physikalische Chemie e.V., Frankfurt a. M., Germany (2005)
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
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
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…