Operando modeling of zeolite-catalyzed reactions using first-principles molecular dynamics simulations
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 …
(MD) simulations in unraveling the catalytic function within zeolites under operating …
A reactive neural network framework for water-loaded acidic zeolites
Under operating conditions, the dynamics of water and ions confined within protonic
aluminosilicate zeolite micropores are responsible for many of their properties, including …
aluminosilicate zeolite micropores are responsible for many of their properties, including …
Reference‐Quality Free Energy Barriers in Catalysis from Machine Learning Thermodynamic Perturbation Theory
For the first time, we report calculations of the free energies of activation of cracking and
isomerization reactions of alkenes that combine several different electronic structure …
isomerization reactions of alkenes that combine several different electronic structure …
[HTML][HTML] The future of computational catalysis
J Sauer - Journal of Catalysis, 2024 - Elsevier
The future of computational heterogeneous catalysis is shaped by machine learning in two
different but equally important areas:(i) development of atomistic potentials that closely …
different but equally important areas:(i) development of atomistic potentials that closely …
Chemically accurate predictions for water adsorption on Brønsted sites of zeolite H-MFI
We investigate the adsorption of water molecules in the zeolite H-MFI at isolated Brønsted
acid sites (BAS) for loadings of 1, 2, and 3 H2O/BAS. We consider two approaches to the …
acid sites (BAS) for loadings of 1, 2, and 3 H2O/BAS. We consider two approaches to the …
Machine learning thermodynamic perturbation theory offers accurate activation free energies at the RPA level for alkene isomerization in zeolites
The determination of accurate free energy barriers for reactions catalyzed by proton-
exchanged zeolites by quantum chemistry approaches is a challenge. While ab initio …
exchanged zeolites by quantum chemistry approaches is a challenge. While ab initio …
Machine learning applications for thermochemical and kinetic property prediction
Detailed kinetic models play a crucial role in comprehending and enhancing chemical
processes. A cornerstone of these models is accurate thermodynamic and kinetic properties …
processes. A cornerstone of these models is accurate thermodynamic and kinetic properties …
The Operando Nature of Isobutene Adsorbed in Zeolite H− SSZ− 13 Unraveled by Machine Learning Potentials Beyond DFT Accuracy
Unraveling the nature of adsorbed olefins in zeolites is crucial to understand numerous
zeolite‐catalyzed processes. A well‐grounded theoretical description critically depends on …
zeolite‐catalyzed processes. A well‐grounded theoretical description critically depends on …
Understanding Alkene Interaction with Metal-Modified Zeolites: Thermodynamics and Mechanism of Bonding in the π-Complex
AA Gabrienko, ES Kvasova, DI Kolokolov… - Inorganic …, 2024 - ACS Publications
Zeolites modified with metal cations are perspective catalysts for converting light alkenes to
valuable chemicals. A crucial step of the transformation is an alkene interaction with zeolite …
valuable chemicals. A crucial step of the transformation is an alkene interaction with zeolite …
Kinetic Consequences of Quasi-Harmonic Entropies Calculated with Machine Learning Interatomic Potentials for Microkinetic Modeling
Microporous catalysts are ubiquitous in chemical processes including sustainable
transformations of biobased feedstocks into fuels and fine chemicals. The mechanistic …
transformations of biobased feedstocks into fuels and fine chemicals. The mechanistic …