Zeolites

A major focus of our work is to understand, predict and manipulate the properties of zeolitic materials, towards optimization of their function as sorbents and catalysts. Much of that interest is focussed on controlling the stability against (and mechanisms of) zeolite decomposition, under operando conditions. Controlling stability means both understanding how to avoid decomposition, but also to selectively utilise hydrolysis to generate new materials with improved properties - e.g. via the ADOR process. We approach these systems by a combination of Ab Initio Molecular and biased dynamical simulations, and via development of machine learning methods to enhance simulation timescales and quality.

Much of this work is done in association with the nanomaterials modelling group and CUCAM project at Charles University in Prague.

Metal Nanoclusters

Another major area of interest is in understanding the dynamic properties of metallic clusters of around (and below) 1 nm in size. Via surface support or encapsulation into porous media, small metal clusters may be stabilised against growth and sintering, giving rise to highly active photonic and catalytic hybrid systems. We are interested in modelling the dynamic behaviour of these clusters under realistic conditions - including migration, sintering, redispersion, and the roles of reactive atmospheres, temperature and aging. To bridge the time gap between computational modelling and experiment, we develop and apply kinetic modelling and ML techniques, alongside traditional density functional methods.