Biomass and plastic recycling feedstocks hold significant potential to replace chemicals and fuels derived from fossil resources. However, their distinct chemical compositions, and large water content, present challenges to existing infrastructure and catalysts. Zeolites, widely used in chemical and fuel production, face concerns regarding their stability under hot liquid water conditions relevant for converting these novel feedstocks. Thus, understanding the mechanisms behind zeolite deactivation/stabilization is essential. The ZEOLANDO project will use an integrated approach combining experimental and computational operando methods, including NMR and vibrational spectroscopies (IR and inelastic neutron scattering), as well as neural-network-accelerated atomistic simulations. The project objective is to investigate the spatiotemporal evolution of zeolite frameworks, elucidate the structure of active sites, and explore their deactivation when exposed to water under operando conditions, i.e., at temperature, pressure and surface coverage used in catalysis. This research represents a substantial advancement over static or short dynamical simulations and conventional experimental characterization studies, that often ignore the dynamical effects arising under operando conditions. My expertise in experimental characterization, particularly utilizing NMR and vibrational spectroscopies, combined with the host group’s proficiency in advanced computational methods (including neural network potentials), uniquely positions ZEOLANDO to unveil the dynamic nature of the zeolite structure and acid site speciation under operando conditions, and can lead to the development of new and improved catalyst. By ensuring constant feedback between experimental and computational results, this project aims to enhance the understanding of zeolite behaviour during chemical reactions, offering potential benefits beyond zeolite research, and opening doors to career development opportunities.