Electrochemical water splitting represents a promising technology for green hydrogen
production. To design advanced electrocatalysts, it is crucial to identify their active sites and …

Within this Perspective, we critically reflect on the role of first-principles molecular dynamics
(MD) simulations in unraveling the catalytic function within zeolites under operating …

Existing reaction transition state (TS) databases are comparatively small and lack chemical
diversity. Here, this data gap has been addressed using the concept of a graphically-defined …

Transition state search is key in chemistry for elucidating reaction mechanisms and
exploring reaction networks. The search for accurate 3D transition state structures, however …

The adsorption energies of molecular adsorbates on catalyst surfaces are key descriptors in
computational catalysis research. For the relatively large reaction intermediates frequently …

Autonomous reaction network exploration algorithms offer a systematic approach to explore
mechanisms of complex chemical processes. However, the resulting reaction networks are …

New materials for electrochemical energy storage and conversion are the key to the
electrification and sustainable development of our modern societies. Molecular modelling …

This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …

Machine-learning (ML) potentials trained with density functional theory (DFT) data boost the
sampling capabilities in first-principles global surface structure determination. Particular data …

The traditional trial-and-error approach can no longer meet the surging demand for
developing catalysts to address the grand challenges of energy and environment, while …