This is a match-making section for QuantERA Call 2023.
quantum-chemistry DFT statistical-thermodynamics electronic-structure materials-modelling
At MODES (RWTH Aachen) we offer in-depth expertise on multiscale modelling and computational materials characterization, which are cornerstones in modern materials and interface structure design. We use quantum mechanics-based calculations, molecular dynamics, and Monte Carlo simulations to investigate chemo- and electrocatalysts, porous materials and various types of interfaces between materials. We also develop schemes to use both experimental and calculated data for training machine learning models for physics-based rational design and discovery of new materials for various applications. The application areas and materials of interest for us are (but not limited to): Na-ion batteries, silicon/carbon anodes, catalysts for fuel cells, catalysts for O2 and H2 evolution, solid state ion conductors, corrosion and temperature resistant surface coatings, polymer coatings, and perovskite oxides. We offer complimentary expertise in developing workflows for linking available simulation software codes to each other to achieve a comprehensive coverage of the required simulation scales: from the molecular to the mesoscale, and finally to the device scale. In addition we offer experience in curating data and designing relational databases.
We are looking to join a project that would benefit from calculations of material properties that are typically only accessible by quantum simulations. Such properties include, band gaps, electronic conductivity, dielectric properties, magnetic properties and spectroscopic properties that are typically validated against high-resolution electron microscopy.
Submitted on 2023-04-03 08:11:33
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