Unveiling the mechanism of proton transfer in H2O-loaded zeolites

The transition to more eco-friendly biomass feedstocks, which are rich in H2O compared to fossil feedstocks, necessitates the
development of a detailed atomic-level understanding of H2O-loaded zeolites to understand the amount and type of protonated H2O
cluster and create new and improved catalysts. This proposal aims to comprehend the mechanism of protonation in H2O-loaded zeolites
by studying two distinct zeolites (RHO and CHA) with distinct Si/Al ratios and H2O-loading using inelastic neutron spectroscopy (INS).
Reactive machine learning potentials (MLP) enable long molecular dynamics simulations, inaccessible with conventional ab initio
methods, and allow modelling of the behaviour of zeolites at the experimental conditions. INS data will be compared with results from
the vibrational density of states, derived from MLP-based trajectories, and with complementary experimental methods, such as 1H NMR.
In an attempt to provide an atomic-level description of how the Al and H2O content, pore size, and shape influence the amount and type
species formed, namely H-bonded and protonated H(H2O)n+ (n>1), and identify the mechanism of proton transfer between Brønsted acid
sites and water.