Krüger, T.; Varnik, F.; Raabe, D.: Simulation of a dense suspension of deformable particles using the lattice Boltzmann method. ICMMES 2009, Guangzhou, China (2009)
Varnik, F.: Lattice Boltzmann studies of confined flows at intermediate Reynolds numbers: The role of wall roughness. The 5th International Conference for Mesoscopic Methods in Engineering, Amsterdam, The Netherlands (2008)
Varnik, F.: Stability and kinetics of droplets: A free energy based lattice Boltzmann study. DPG Spring Meeting of the Condensed Matter Division, Berlin, Germany (2008)
Gross, M.; Varnik, F.; Raabe, D.: Stability and kinetic of droplets: A free energy based lattice Boltzmann study. Sommer Workshop on Nano-& Microfluidics, Bad Honnef, Germany (2008)
Varnik, F.: Yield stress discontinuity: A manifest of the glass transition in a sheared glass. 369th Heraeus-Seminar, Interplay of Thermodynamics and Hydrodynamics in Soft Condensed Matter, Bad-Honnef, Germany (2006)
Varnik, F.: Shearing glassy model systems: A test of theoretical predictions on non linear rheology. 6th Liquid Matter Conference, Utrecht, The Nederlands (2005)
Varnik, F.: Confinement effects on the slow dynamics of a simulated supercooled polymer melt. International workshop on dynamics in viscous liquids, München, Germany (2004)
Varnik, F.: Glass Transition in Polymer Films: A Molecular Dynamics Study. International Conference on Computational Physics (CCP), Aachen, Germany (2001)
Varnik, F.: Propriétés statiques et dynamiques des couches minces de polymères. Les Journées de Rencontre Nationale sur les propriétés des verres, Montpellier, France (2001)
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…