Salgin, B.; Rohwerder, M.: Mobility of Water and Charge Carriers in Polymer/Oxide/Aluminium Alloy Interphases. M2i/DPI Project Meeting, Delft, The Netherlands (2009)
Salgin, B.; Rohwerder, M.: A New Approach to Determine Ion Mobility Coefficients for Delamination Scenarios. electrochem09 and 50th Corrosion Science Symposium, Manchester, UK (2009)
Salgin, B.; Rohwerder, M.: A New Approach to Determine Ion Mobility Coefficients for Delamination Scenarios. 60th Annual Meeting of the International Meeting of the International Society of Electrochemistry, Beijing, China (2009)
Salgin, B.; Rohwerder, M.: Effects of Semiconducting Properties of Surface Oxide on the Delamination at the Polymer/Zinc Interface. SurMat Seminar, Kleve, Germany (2008)
Salgin, B.; Rohwerder, M.: Mobility of Water and Charge Carriers in Polymer/Oxide/Aluminium Alloy Interphases. M2i Conference 2011, Noordwijkerhout, The Netherlands (2011)
Salgin, B.; Rohwerder, M.: Scanning Kelvin Probe (SKP) as a tool for monitoring ion mobility on insulators. M2i Conference 2009, Noordwijkerhout, The Netherlands (2009)
Salgin, B.; Rohwerder, M.: Effects of the Semiconducting Properties of Surface Oxide on the Delamination at the Polymer/Metal Interface. 2nd International IMPRS-SurMat Workshop, Bochum, Germany (2008)
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.
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.
New product development in the steel industry nowadays requires faster development of the new alloys with increased complexity. Moreover, for these complex new steel grades, it is more challenging to control their properties during the process chain. This leads to more experimental testing, more plant trials and also higher rejections due to…