Modeling dynamic processes in realistic nanostructured materials at operating conditions
The research performed within the research group of Van Speybroeck focuses on the simulation of realistic nanostructured materials starting from the atomic and molecular scale with the ambition to mimic as close as possible experimental and process conditions. We study materials with important technological applications in the field energy storage, gas separation, sensing, catalysis. Materials of interest are zeolites, metal-organic frameworks, perovskites. The research is performed by a multidisciplinary team of physicists, engineers, chemists, material scientists.
Experimentally, it is very difficult to unravel how the nanometer scale structure impacts the observed material’s behavior. Modeling in close synergy with experimental groups has the potential to give this nanoscopic insight, provided materials are modeled in a realistic way. It is extremely important to account for defects, finite crystal size or in general spatial disorder from the nano- to the mesoscale. Furthermore, the material’s behavior is strongly determined by the conditions in which they do the work, such as true operating temperatures, pressures.
We have the ambition to model realistic nanostructured materials starting from physical principles ruling at the atomic/molecular scale and to devise methods enable to bridge from the microscopic scale to the macroscopically observed behavior. To this end we develop and apply new methods in various areas. A key ingredient are the methods to describe the interatomic interactions. Ideally, this is done at the quantum mechanical level, such methods are too expensive to be used on large systems. Therefore, we also develop force fields and machine learning potentials that are parametrized based on underlying quantum mechanical data and hold the promise to model systems having length scales up to 50 nm with quantum accuracy. Furthermore some materials are characterized by strong electron correlations, for which advanced many-body techniques are necessary, therefore we are also exploring new methods like tensor networks to model with very high accuracy strongly correlated systems. Lastly our systems have many degrees of freedom, which makes it very difficult to explore the interesting regions of phase space. Therefore, we develop various advanced sampling techniques from which we can derive macroscopic observables like rate constants, thermodynamic, mechanical properties.
Based on all these insights, we aim to steer the development of new functional materials which are tuned at the atomic scale to give the desired functions in technological applications.