A3 Multiscale Modeling and Simulation

Exzellenz-Cluster Engineering of Advanced Materials

FAU Kontaktperson:
Leugering, Günter Prof. Dr.


New methods for multiscale and multiphysical modeling for the optimization of structures, properties, and processes

The research concept connects quantum-mechanical approaches on the
molecular scale to discrete approaches for particle systems and to
methods of continuum mechanics

The cross-sectional Research Area A3 is concerned with modeling,
simulating and optimizing macroscopic material and structural properties
based on their constituent components such as particles, molecules and
atoms. A guiding principle of A3 is that simulation is used as a new
paradigm in gaining qualitative knowledge and quantitative data
alongside theoretical and experimental facts.

  • On
    the qualitative side, molecules that have not yet been synthesized can
    e.g. be anticipated via modeling and simulation. Similarly, new
    materials and in particular meta-materials (or utopia-materials) can be
    designed optimally, given their desired functionality.
  • On the
    quantitative side, data-driven model-based simulation and optimization
    in the context of the application areas can be used directly in the
    process chain.

Understanding matter and designing materials,
interfaces, and processes from their nano-structural constitution
necessitates both algorithms that scale almost linearly in order to cope
with the vast number of variables, and hierarchical, multi-scale
modeling, analysis and mathematical optimization in order to bridge the
gap between the scales in space, time, and constitutive models.

Center for Multiscale Modeling and Simulation (CMMS) works on
multiscale approaches and methods for structure, property, and process
optimization. The research concept connects quantum mechanical
approaches on the molecular scale to discrete approaches for particle
systems and to methods of continuum mechanics.

Zugewiesene Publikationen

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Kettner, M., Maisel, S., Stumm, C., Schwarz, M., Schuschke, C., Görling, A., & Libuda, J. (2019). Pd-Ga model SCALMS: Characterization and stability of Pd single atom sites. Journal of Catalysis, 369, 33-46. https://dx.doi.org/10.1016/j.jcat.2018.10.027
Stingl, M., & Wein, F. (2018). A combined parametric shape optimization and ersatz material approach. Structural and Multidisciplinary Optimization, 57(3), 1297-1315. https://dx.doi.org/10.1007/s00158-017-1812-3
Eibl, S., & Rüde, U. (2018). A Local Parallel Communication Algorithm for Polydisperse Rigid Body Dynamics. Parallel Computing, 80, 36-48. https://dx.doi.org/10.1016/j.parco.2018.10.002
Wawra, S., Pflug, L., Thajudeen, T., Kryschi, C., Stingl, M., & Peukert, W. (2018). Determination of the two-dimensional distributions of gold nanorods by multiwavelength analytical ultracentrifugation. Nature Communications, 9(1). https://dx.doi.org/10.1038/s41467-018-07366-9
Bauer, T., Stepic, R., Wolf, P., Kollhoff, F., Karawacka, W., Wick, C.,... Libuda, J. (2018). Dynamic equilibria in supported ionic liquid phase (SILP) catalysis: in situ IR spectroscopy identifies [Ru(CO)xCly]n species in water gas shift catalysis. Catalysis: Science and Technology, 8(1), 344-357. https://dx.doi.org/10.1039/C7CY02199B
Walther, M., & Zahn, D. (2018). From bismuth oxide/hydroxide precursor clusters towards stable oxides: Proton transfer reactions and structural reorganization govern the stability of [Bi18 O13 (OH)10]-nitrate clusters. Chemical Physics Letters, 691, 87-90. https://dx.doi.org/10.1016/j.cplett.2017.10.064
Brilliantov, N., Formella, A., & Pöschel, T. (2018). Increasing temperature of cooling granular gases. Nature Communications, 9. https://dx.doi.org/10.1038/s41467-017-02803-7
Semmler, J., Pflug, L., & Stingl, M. (2018). Material optimization in transverse electromagnetic scattering applications. SIAM Journal on Scientific Computing, 40(1), B85-B109. https://dx.doi.org/10.1137/17M1127569
Schuschke, C., Schwarz, M., Hohner, C., Silva, T.N., Fromm, L., Döpper, T.,... Libuda, J. (2018). Phosphonic Acids on an Atomically Defined Oxide Surface: The Binding Motif Changes with Surface Coverage. Journal of Physical Chemistry Letters, 9(8), 1937-1943. https://dx.doi.org/10.1021/acs.jpclett.8b00668
Scholz, C., Engel, M., & Pöschel, T. (2018). Rotating robots move collectively and self-organize. Nature Communications, 9(1), 931. https://dx.doi.org/10.1038/s41467-018-03154-7

Zuletzt aktualisiert 2019-21-03 um 12:34