Organization
Graduate School of Informatics Department of Complex Systems Science 5 Designated Assistant Professor
Title
Designated Assistant Professor
Contact information
Homepage
Other name(s)
Johannes L. Hörmann
Profile
My research focuses on the multiscale modeling of interfacial phenomena in tribological and electrochemical systems. I combine continuum approaches (finite element solutions of coupled Poisson-Nernst-Planck equations), atomistic simulations (molecular dynamics, DFTB, and DFT), and data-driven methods to understand friction, adsorption, lubrication, and electrochemical double layers at rough and chemically complex interfaces.
A central theme of my work is the frictional behavior of surfactant adsorption films and electrolyte-lubricated contacts under mechanical and electrical stimuli. I develop reproducible, high-performance computational workflows for large-scale simulations and integrate research data management as a core scientific principle. Beyond physics-based modeling, I apply Gaussian process regression and classification to predict surface performance from topographical descriptors, bridging fundamental simulation with industrial surface engineering applications.
My long-term research vision is to establish reproducible, multiscale digital twins of functional interfaces by tightly coupling physics-based simulation, machine learning, and FAIR research data infrastructures.
A central theme of my work is the frictional behavior of surfactant adsorption films and electrolyte-lubricated contacts under mechanical and electrical stimuli. I develop reproducible, high-performance computational workflows for large-scale simulations and integrate research data management as a core scientific principle. Beyond physics-based modeling, I apply Gaussian process regression and classification to predict surface performance from topographical descriptors, bridging fundamental simulation with industrial surface engineering applications.
My long-term research vision is to establish reproducible, multiscale digital twins of functional interfaces by tightly coupling physics-based simulation, machine learning, and FAIR research data infrastructures.
External link
