Eisenlohr, P.: Einheitliche Beschreibung dynamischer und statischer Erholung von Stufenversetzungen mittels Dipolweitenverteilungen. Seminar of the Institute of Materials Physics, University of Vienna, Vienna, Austria (2003)
Reuber, J. C.; Eisenlohr, P.; Roters, F.: Boundary Layer Formation in Continuum Dislocation Dynamics. Dislocations 2016, Purdue University, West Lafayette, IN, USA (2016)
Shanthraj, P.; Diehl, M.; Eisenlohr, P.; Roters, F.: Numerically robust spectral methods for crystal plasticity simulations of heterogeneous materials. Materials to Innovate Industry and Society, Noordwijkerhout, The Netherlands (2013)
Diehl, M.; Eisenlohr, P.; Roters, F.; Raabe, D.: Using a "Virtual Laboratory" to Derive Mechanical Properties of Complex Microstructures. 11th GAMM-Seminar on Microstructures, Essen, Germany (2012)
Diehl, M.; Eisenlohr, P.; Roters, F.; Tasan, C. C.; Raabe, D.: Using a "Virtual Laboratory" to Derive Mechanical Properties of Complex Microstructures. Materials to Innovate Industry and Society, Noordwijkerhout, The Netherlands (2011)
Kords, C.; Eisenlohr, P.; Roters, F.: Signed dislocation densities and their spatial gradients as basis for a nonlocal crystal plasticity model. MMM 2010 Fifth International Conference Multiscale Materials Modeling, Freiburg, Germany (2010)
Kords, C.; Eisenlohr, P.; Roters, F.: A Non-Local Dislocation Density Based Constitutive Model for Crystal Plasticity. Junior Euromat 2010, Lausanne, Switzerland (2010)
Eisenlohr, P.: On the role of dislocation dipoles in unidirectional deformation of crystals. Dissertation, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen (2004)
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
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…
Ever since the discovery of electricity, chemical reactions occurring at the interface between a solid electrode and an aqueous solution have aroused great scientific interest, not least by the opportunity to influence and control the reactions by applying a voltage across the interface. Our current textbook knowledge is mostly based on mesoscopic…
Recent developments in experimental techniques and computer simulations provided the basis to achieve many of the breakthroughs in understanding materials down to the atomic scale. While extremely powerful, these techniques produce more and more complex data, forcing all departments to develop advanced data management and analysis tools as well as…