Sachs, C.; Nikolov, S.; Fabritius, H.; Raabe, D.: Investigation and Modeling of the Elastic Properties of Lobster Cuticle Depending on its Grade of Mineralization. MRS Spring Meeting, San Francisco, CA, USA (2008)
Al-Sawalmih, A.; Romano, P.; Sachs, C.; Raabe, D.: Structure and texture analysis of chitin-bio-nanocomposites using synchrotron radiation. MRS Spring Meeting, San Francisco, CA, USA (2005)
Romano, P.; Al-Sawalmih, A.; Sachs, C.; Raabe, D.; Brokmeier, H. G.: Mesostructure, microstructure and anisotropy of the lobster cuticle. MRS Spring Meeting, San Francisco, CA, USA (2005)
Romano, P.; Raabe, D.; Al-Sawalmih, A.; Sachs, C.; Servos, G.; Hartwig, H. G.: Influence of sample preparation and anisotropy on lobster claw studied by LOM, SEM and TEM. Focus on Microscopy, Jena, Germany (2005)
Sachs, C.: Microstructure and mechanical properties of the exoskeleton of the lobster Homarus americanus as an example of a biological composite material. Dissertation, RWTH Aachen, Aachen, Germany (2008)
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
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.