Photovoltaic
We use computations, as physics-based simulations and machine learning to provide novel, innovative approaches in photovoltaic field: in particular we can combine ab-initio technique (wave planes) with 3D finite element method (FEM) technique to simulate a planar perovskite solar cell (PSC). This mixed approach allows to predict improvements in the performance of the device depending on the chemical-physical nature of the absorber (in this case perovskite), and on the engineering architecture of the device.
Polymer reaction
We use Monte Carlo method to simulate, for example, the growth of polymer brushes from flat surfaces via a grafting-from approach by atom transfer radical polymerization (ATRP).
Catalysis
We use accurate QM + MM method that adds the solvation effects on top of the QM gas-phase reaction.
Biophysical
We can use coarse-grained molecular dynamics (CGMD) models, namely, the “bottom-up” force-matching- and “top-down” free energy-based approaches to describe biological complex system.