Merz, A.; Rohwerder, M.: The protection zone: A long-range corrosion protection mechanism around conducting polymer particles in composite coatings: Part II. PEDOT: PSS. Journal of the Electrochemical Society 166 (12), pp. C314 - C320 (2019)
Merz, A.; Uebel, M.; Rohwerder, M.: The Protection Zone: A Long-Range Corrosion Protection Mechanism around Conducting Polymer Particles in Composite Coatings: Part I. Polyaniline and Polypyrrole. Journal of the Electrochemical Society 166 (12), pp. C304 - C313 (2019)
Merz, A.; Rohwerder, M.: Corrosion protection by composite coatings containing conducting polymer particles: elucidation of the “protection zone”. 232nd ECS Fall Meeting 2017, National Harbour, USA (2017)
Merz, A.; Uebel, M.; Rohwerder, M.: Investigation of the role of protection zone around conducting polymer in composite coatings in inhibiting delamination process. Gordon Research Conferences 2016, New London, NH, USA (2016)
Merz, A.; Uebel, M.; Rohwerder, M.: Investigation of the role of protection zone around conducting polymer in composite coatings in inhibiting delamination process. Gordon Research Seminars 2016, New London, NH, USA (2016)
Merz, A.: Investigation of the “Protection Zone”, a novel mechanism to inhibit delamination of composite organic coatings containing conducting polymer. Dissertation, Ruhr-Universität Bochum (2019)
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
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
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…