Krüger, T.; Varnik, F.; Raabe, D.: Second-order convergence of the deviatoric stress tensor in the standard Bhatnagar-Gross-Krook lattice Boltzmann method. Physical Review E 82 (025701) (2010)
Ayodele, S. G.; Varnik, F.; Raabe, D.: Effect of aspect ratio on transverse diffusive broadening: A lattice Boltzmann study. Physical Review E 80 (1), pp. 016304-1 - 016304-9 (2009)
Ayodele, S. G.; Varnik, F.; Raabe, D.: Transverse diffusive mixing of solutes in pressure driven microchannels: A Lattice Boltzmann study of the scaling laws. La Houille Blanche, International Water Journal 6, pp. 93 - 100 (2009)
Gross, M.; Varnik, F.; Raabe, D.: Fall and rise of small droplets on rough hydrophobic substrates. Europhysics Letters 88 (26002), pp. 26002-p1 - 26002-p6 (2009)
Varnik, F.; Raabe, D.: Scaling effects in microscale fluid flows at rough solid surfaces. Modeling and Simulation in Materials Science and Engineering 14, pp. 857 - 873 (2006)
Baschnagel, J.; Varnik, F.: Computer simulations of supercooled polymer melts in the bulk and in confined geometry. Journal of Physics: Condensed Matter 17 (32), pp. R851 - R953 (2005)
Varnik, F.; Bocquet, L.; Barrat, L.-J.: A study of the static yield stress in a binary Lennard-Jones glass. The Journal of Chemical Physics 120 (6), pp. 2788 - 2801 (2004)
Baschnagel, J.; Meyer, H.; Varnik, F.; Metzger, S.; Aichele, M.; Müller, M.; Binder, K.: Computer Simulations of Polymers close to Solid Interfaces: Some Selected Topics. Special Issue of Interface Science: Polymers at Interfaces 11, pp. 159 - 173 (2003)
Varnik, F.; Baschnagel, J.; Binder, K.; Mareschal, M.: Confinement effects on the slow dynamics of a supercooled polymer melt: Rouse modes and the incoherent scattering function. European Physical Journal E 12 (167) (2003)
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
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.