Stechmann, G.; Zaefferer, S.; Konijnenberg, P. J.: Microstructural and Electronic Characterization of CdTe Thin Film Solar Cells: A Correlative SEM-Based Approach. IAMNano, Port Elizabeth, South Africa (2016)
Stechmann, G.; Zaefferer, S.: Microstructural and Electronic Characterization of CdTe Thin Film Solar Cells: A Correlative SEM-Based Approach. IAMNano, Hamburg, Germany (2015)
Zaefferer, S.; Mandal, S.; Stechmann, G.; Bozzolo, N.: Correlative measurement of the 5-parameter grain boundary character and its physical and chemical properties. RMS EBSD 2014, London, UK (2014)
Stechmann, G.: A Study on the Microstructure Formation Mechanisms and Functional Properties of CdTe Thin Film Solar Cells Using Correlative Electron Microscopy and Atomistic Simulations. Dissertation, RWTH Aachen, Aachen, Germany (2017)
Stechmann, G.: Compatibility between Molten Salts and Materials in Concentrated Solar Power Plants. Diploma, École Nationale Supérieure de Chimie de Lille, Lille, France (2013)
Stechmann, G.: Crystallographic and Electronic Characterization of Grain Boundaries in Cd–Te Thin Film Solar Cell. Master, University of Lille I, University of Science and Technology, Lille, France (2013)
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
Complex simulation protocols combine distinctly different computer codes and have to run on heterogeneous computer architectures. To enable these complex simulation protocols, the CM department has developed pyiron.
Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to…
Atom probe tomography (APT) provides three dimensional(3D) chemical mapping of materials at sub nanometer spatial resolution. In this project, we develop machine-learning tools to facilitate the microstructure analysis of APT data sets in a well-controlled way.
Atom probe tomography (APT) is one of the MPIE’s key experiments for understanding the interplay of chemical composition in very complex microstructures down to the level of individual atoms. In APT, a needle-shaped specimen (tip diameter ≈100nm) is prepared from the material of interest and subjected to a high voltage. Additional voltage or laser…