Sun, G.; Grundmeier, G.: Surface-enhanced Raman spectroscopy of the growth of ultra-thin organosilicon plasma polymers on nanoporous Ag/SiO2-bilayer films. Thin Solid Films 515 (4), pp. 1266 - 1274 (2006)
Sun, G.: Characterization and Application of New SERS Active Substrates Prepared by Combined Plasma Polymerization and Physical Vapour Deposition. 11th ECASIA, Vienna, Austria (2005)
Sun, G.: Surface-enhanced Raman Spectroscopy Investigation of Surfaces and Interfaces in Thin Films on Metals. Dissertation, Ruhr-Universität, Fakultät für Maschinenbau, Institut für Werkstoffe, Bochum, Germany (2007)
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…
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.