Rechmann, J.; Krzywiecki, M.; Erbe, A.: Carbon-Sulfur Bond Cleavage During Adsorption of Octadecane Thiol to Copper in Ethanol. Langmuir 35 (21), pp. 6888 - 6897 (2019)
Krzywiecki, M.; Grządziel, L.; Powroźnik, P.; Kwoka, M.; Rechmann, J.; Erbe, A.: Oxide – organic heterostructures: a case study of charge displacement absence at a SnO2 – copper phthalocyanine buried interface. Physical Chemistry Chemical Physics 20 (23), pp. 16092 - 16101 (2018)
Mondragón Ochooa, J. S.; Altin, A.; Rechmann, J.; Erbe, A.: Delamination Kinetics of Thin Film Poly(acrylate) Model Coatings Prepared by Surface Initiated Atom Transfer Radical Polymerization on Iron. Journal of the Electrochemical Society 165 (16), pp. C991 - C998 (2018)
Panther, J.; Rechmann, J.; Müller, T. J. J.: Fischer indole synthesis of 3-benzyl-1H-indole via conductive and dielectric heating. Chemistry of Heterocyclic Compounds 52 (11) (2016)
Rabe, M.; Rechmann, J.; Boyle, A. L.; Erbe, A.: Designing Electro Responsive Self-Assembled Monolayers Based on the Coiled-Coil Peptide Binding Motif. 17th International Conference on Organized Molecular Films” (ICOMF17), New York, NY, USA (2018)
Rechmann, J.: Electron transfer characteristics of gold and oxide-covered copper in aqueous electrolytes modified by self-assembled monolayers. ElecNano8, the 8th international conference on Electrochemistry in Nanosciences
, Nancy, France (2018)
Rechmann, J.: Oberflächenmodifizierung von Zink (Eisen) mit Ethinylphenothiazinen und Charakterisierung. Master, Institut für Organische und Makromolekulare Chemie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany (2014)
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
Crystal Plasticity (CP) modeling [1] is a powerful and well established computational materials science tool to investigate mechanical structure–property relations in crystalline materials. It has been successfully applied to study diverse micromechanical phenomena ranging from strain hardening in single crystals to texture evolution in…
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.