Wang, X.; Grundmeier, G.: Thin multifunctional silver/fluorocarbon plasma polymer nanocomposite films on metals. The 9th International Conference on Nanostructured Materials, Rio de Janeiro, Brazil (2008)
Wang, X.; Grundmeier, G.: Combined spectroscopic, microscopic and electrochemical analysis of release properties of Ag-nanoparticles embedded in fluorocarbon plasma polymer films. The 58th Annual Meeting of the International Society of Electrochemistry, Banff, Canada (2007)
Wang, X.; Grundmeier, G.: Understanding of the Barrier and Release Properties of Thin Model Ag/HDFD-Plasma Polymer Nanocomposite Films. International Conference on Metallurgical Coatings and Thin Films (ICMCTF), San Diego, CA, USA (2007)
Grundmeier, G.; Wang, X.; Barranco, V.; Ebbinghaus, P.: Structure and barrier properties of thin plasma polymers and metal/plasma polymer nanocomposite film. ACHEMA, Frankfurt a. M., Germany (2006)
Wang, X.; Grundmeier, G.: Investigation of Structure and Stability of Silver Nanoparticles in Fluorocarbon Plasma Polymer Films. 13. Bundesdeutsche Fachtagung für Plasmatechnologie, Bochum, Germany (2007)
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
Advanced microscopy and spectroscopy offer unique opportunities to study the structure, composition, and bonding state of individual atoms from within complex, engineering materials. Such information can be collected at a spatial resolution of as small as 0.1 nm with the help of aberration correction.
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…