Modeling and Simulation in catalysis

Image shows a graphical abstract of Prof. Piccini's research. Copyright: © GiovanniMaria Piccini

Our research group aims to develop and apply molecular modelling and simulation methods to relevant problems in the field of catalysis, ranging from heterogeneous, homogeneous, supramolecular and biocatalytic systems. By combining modern techniques such as ab initio quantum chemistry, molecular dynamics, enhanced sampling and free energy methods, with the help of machine learning tools we aim to understand the molecular basis of catalysts under experimental operando conditions.

More specifically, our research focuses on sampling the molecular dynamics of “rare events”,
molecular phenomena such as chemical reactions, phase transitions or large conformational
changes occurring over long time scales. These problems are ubiquitous in chemistry and
fundamental to catalysis, but their study with molecular simulation techniques remains a
challenge. To overcome the limitations of time scales, our group develops and applies advanced
sampling techniques, a large family of methods that allow us to frequently observe rare chemical
events and determine their thermodynamic and kinetic properties. These powerful tools are
combined with machine learning techniques to analyze results, characterize structure/reactivity
properties and accelerate statistical sampling.
Our computational approach is constantly oriented towards comparison with experiments and
draws inspiration from experimental synthesis and characterization techniques that can be
modelled and simulated.


  • Catalysis and storage in nanoporous material - zeolites, MOFs, COFs
  • Solid/liquid reactive interfaces
  • Heterogeneous catalysis of biomass conversion towards carbon neutrality
  • Biomimetic supramolecular catalysis
  • Biocatalysis for organic and drug synthesis