Reference‐Quality Free Energy Barriers in Catalysis from Machine Learning Thermodynamic Perturbation Theory DOI Creative Commons
Jérôme Rey, Céline Chizallet, Dario Rocca

et al.

Angewandte Chemie International Edition, Journal Year: 2023, Volume and Issue: 63(6)

Published: Dec. 7, 2023

For the first time, we report calculations of free energies activation cracking and isomerization reactions alkenes that combine several different electronic structure methods with molecular dynamics simulations. We demonstrate use a high level theory (here Random Phase Approximation-RPA) is necessary to bridge gap between experimental computed values. These transformations, catalyzed by zeolites proceeding via cationic intermediates transition states, are building blocks many chemical transformations for valorization long chain paraffins originating, e.g., from plastic waste, vegetable oils, Fischer-Tropsch waxes or crude oils. Compared energy barriers at PBE+D2 production constrained ab initio dynamics, RPA application Machine Learning thermodynamic Perturbation Theory (MLPT) show significant decrease reaction an increase similar magnitude cracking, yielding unprecedented agreement results obtained experiments kinetic modeling.

Language: Английский

The nature of extraframework aluminum species and Brønsted acid site interactions under catalytic operating conditions DOI Creative Commons
Jenna L. Mancuso, Véronique Van Speybroeck

Journal of Catalysis, Journal Year: 2023, Volume and Issue: 429, P. 115211 - 115211

Published: Nov. 22, 2023

A systematic investigation of hydrated extraframework aluminum (EFAl) species interacting with Brønsted acid sites (BAS) in H-ZSM-5 is presented to understand the active site structure under catalytic operating conditions. Static models EFAl confined unit cell show that isolated BAS protonate neutral form cations. Ab-initio molecular dynamics (AIMD) simulations and enhanced sampling performed at temperature for methanol-to-hydrocarbon conversion reveal two regimes stable species, namely [Al(OH)2]+ ion existing bonds zeolite scaffold or as a pore-guest [Al(OH)2(H2O)2]+. Our results indicate hydrogen-bonding plays significant role BAS-EFAl structure, especially higher density can function both Bronsted Lewis acidic components alter proton transfer kinetics well shape selectivity within these microporous solids.

Language: Английский

Citations

7
The Operando Nature of Isobutene Adsorbed in Zeolite H‐SSZ‐13 Unraveled by Machine Learning Potentials Beyond DFT Accuracy DOI Creative Commons
Massimo Bocus, Sander Vandenhaute, Véronique Van Speybroeck

et al.

Angewandte Chemie International Edition, Journal Year: 2024, Volume and Issue: 64(1)

Published: Oct. 31, 2024

Abstract Unraveling the nature of adsorbed olefins in zeolites is crucial to understand numerous zeolite‐catalyzed processes. A well‐grounded theoretical description critically depends on both an accurate determination potential energy surface (PES) and a reliable account entropic effects at operating conditions. Herein, we propose transfer learning approach perform random phase approximation (RPA) quality enhanced sampling molecular dynamics simulations, thereby approaching chemical accuracy exploration PES. The proposed methodology used investigate isobutene adsorption H−SSZ−13 as prototypical system estimate relative stability physisorbed olefins, carbenium ions alkoxide species (SAS) Brønsted‐acidic zeolites. We show that tert ‐butyl ion formation highly endothermic no stabilization observed compared complex within H−SSZ−13. Hence, its predicted concentration lifetime are negligible, making direct experimental observation unlikely. Yet, it remains shallow minimum free over whole considered temperature range (273–873 K), being therefore short‐lived reaction intermediate rather than transition state species.

Language: Английский

Citations

2
Data efficient machine learning potentials for modeling catalytic reactivity via active learning and enhanced sampling DOI Creative Commons
Simone Perego, Luigi Bonati

npj Computational Materials, Journal Year: 2024, Volume and Issue: 10(1)

Published: Dec. 19, 2024

Language: Английский

Citations

2
Computational Modeling of Reticular Materials: The Past, the Present, and the Future DOI Creative Commons
Wim Temmerman,

Ruben Goeminne,

Kuber Singh Rawat

et al.

Advanced Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 26, 2024

Abstract Reticular materials rely on a unique building concept where inorganic and organic units are stitched together giving access to an almost limitless number of structured ordered porous materials. Given the versatility chemical elements, underlying nets, topologies, reticular provide platform design for timely technological applications. have now found their way in important societal applications, like carbon capture address climate change, water harvesting extract atmospheric moisture arid environments, clean energy Combining predictions from computational chemistry with advanced experimental characterization synthesis procedures unlocks strategy synthesize new desired properties functions. Within this review, current status modeling is addressed supplemented topical examples highlighting necessity molecular This review as templated study starting structure realistic material towards prediction functions At end, authors perspective past, present future formulate open challenges inspire model method developments.

Language: Английский

Citations

2
Reference‐Quality Free Energy Barriers in Catalysis from Machine Learning Thermodynamic Perturbation Theory DOI Creative Commons
Jérôme Rey, Céline Chizallet, Dario Rocca

et al.

Angewandte Chemie International Edition, Journal Year: 2023, Volume and Issue: 63(6)

Published: Dec. 7, 2023

For the first time, we report calculations of free energies activation cracking and isomerization reactions alkenes that combine several different electronic structure methods with molecular dynamics simulations. We demonstrate use a high level theory (here Random Phase Approximation-RPA) is necessary to bridge gap between experimental computed values. These transformations, catalyzed by zeolites proceeding via cationic intermediates transition states, are building blocks many chemical transformations for valorization long chain paraffins originating, e.g., from plastic waste, vegetable oils, Fischer-Tropsch waxes or crude oils. Compared energy barriers at PBE+D2 production constrained ab initio dynamics, RPA application Machine Learning thermodynamic Perturbation Theory (MLPT) show significant decrease reaction an increase similar magnitude cracking, yielding unprecedented agreement results obtained experiments kinetic modeling.

Language: Английский

Citations

4