In evolving fields such as physics, chemistry, or materials science, factual knowledge changes rapidly but the ability to reason is what allows us to master these changes.
Björn Baumeier is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). His Research Group is part of the Centre for Analysis, Scientific Computing and Applications (CASA) as well as of the Institute for Complex Molecular Systems (ICMS). The group’s research is devoted to the development and application of multiscale simulation techniques for the study of electronic transport processes in soft matter. Its models combine techniques from computational chemistry, statistical physics, and mathematics and allow for the analysis of the interplay between molecular electronic structure and material morphology, relevant for many opto-electronic device properties or bio-molecular processes. Other research lines include studies of (disordered) assemblies of biomolecules and super-coarse-grained modeling of soft granular materials. Typically, large-scale computer simulations are employed linking quantum chemistry, classical Molecular Dynamics at all-atom and coarse-grained levels, and rate-based models.
Björn Baumeier obtained his Diploma and PhD in Theoretical Solid State Science form the University of Münster and joined TU/e as an Assistant Professor in September 2015. He has conducted research at the University of California (Department of Physics and Astronomy, Irvine, and Institute for Pure and Applied Mathematics, Los Angeles) and the Max Planck Institute for Polymer Research. In 2017, Bjorn received a Vidi grant from NWO (The Netherlands Organisation for Scientific Research), with a value of € 800,000. The research project funded with this grant focuses on understanding the mechanisms underlying long-distance and spin-selective electronic transport in complex molecular systems.
Backbone chemical composition and monomer sequence effects on phenylene polymer persistence lengthsMacromolecules (2019)
Evolutionary approach to constructing a deep feedforward neural network for prediction of electronic coupling elements in molecular materialsJournal of Chemical Theory and Computation (2019)
Insights into the kinetics of supramolecular comonomer incorporation in waterMacromolecules (2019)
Improved general-purpose five-point model for water: TIP5P/2018Journal of Chemical Physics (2018)
Morphology of proliferating epithelial cellular tissuearXiv.org, e-Print Archive, Physics (2018)