The Computational Materials Physics Group of Shuxia Tao works on the understanding of the process-structure-property-performance relationship of solid-state materials for energy applications. We develop and use multiscale methods, combining quantum methods e.g. Density Functional Theory with classical methods such as Molecular Dynamics and Monte Carlo, to study the complex interplay of chemistry and physics of materials at the nanoscale. Currently, our main focus is perovskite solar cells. We are a part of Materials Simulation & Modelling at the Department of Applied Physics at Eindhoven University of Technology (TU/e) and a member of Center for Computational Energy Research.
Mike and Victor show how machine learning can help creating force fields with near ab-initio accuracy to describe defect dynamics in perovskites.
Sander defended his Master thesis on the refinement of DFTB parameters for studying phase stability of halide perovskites and received a grade of 9.5!
Mike defended his master thesis on reactive force field MD simulations of perovskites and the work is published on J. Phys. Chem. Lett.
Zehua developed a unified thermodynamic theory for the segregation of mixed halide perovskites, published on Nature Communications.
On Nature Communications, Sofia shows PAAI long-chain molecule improves operation lifetime of perovskite LEDs.
On Advanced Materials, Haibo studies the impact of crystallization kinetics on the quality and the morphology of perovskite films.
The absolute energy levels of 18 halide perovskites is published on Nature Communications.
Our article NaF improving the stability of perovskite solar cells is published on Nature Energy.
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