scholarly journals Revisiting Catalytic Cycles: A Broader View Through the Energy Span Model

2020 ◽  
Author(s):  
Diego Garay-Ruiz ◽  
Carles Bo
Keyword(s):  
Catalytic Reaction ◽  
Reaction Mechanisms ◽  
Computational Study ◽  
Reaction Network ◽  
Co2 Hydrogenation ◽  
Level Of Detail ◽  
Reaction Pathways ◽  
Catalytic Systems ◽  
Computational Code ◽  
Catalytic Cycles

<div><div><div><p>The computational study of catalytic processes allows discovering really intricate and detailed reaction mechanisms that involve many species and transformations. This increasing level of detail can even result detrimental when drawing conclusions from the computed mechanism, as many co-existing reaction pathways can be in close com- petence. Here we present a reaction network-based implementation of the energy span model in the form of a computational code, gTOFfee, capable of dealing with any user-specified reaction network. This approach, compared to microkinetic simulations, enables a much easier and straightforward analysis of the performance of any catalytic reaction network. In this communication, we will go through the foundations and appli- cability of the underlying model, and will tackle the application to two relevant catalytic systems: homogeneous Co-mediated propene hydroformylation and heterogeneous CO2 hydrogenation over Cu(111).</p></div></div></div>

scholarly journals Revisiting Catalytic Cycles: A Broader View Through the Energy Span Model

2020 ◽  
Author(s):  
Diego Garay-Ruiz ◽  
Carles Bo
Keyword(s):  
Catalytic Reaction ◽  
Reaction Mechanisms ◽  
Computational Study ◽  
Reaction Network ◽  
Co2 Hydrogenation ◽  
Level Of Detail ◽  
Reaction Pathways ◽  
Catalytic Systems ◽  
Computational Code ◽  
Catalytic Cycles

<div><div><div><p>The computational study of catalytic processes allows discovering really intricate and detailed reaction mechanisms that involve many species and transformations. This increasing level of detail can even result detrimental when drawing conclusions from the computed mechanism, as many co-existing reaction pathways can be in close com- petence. Here we present a reaction network-based implementation of the energy span model in the form of a computational code, gTOFfee, capable of dealing with any user-specified reaction network. This approach, compared to microkinetic simulations, enables a much easier and straightforward analysis of the performance of any catalytic reaction network. In this communication, we will go through the foundations and appli- cability of the underlying model, and will tackle the application to two relevant catalytic systems: homogeneous Co-mediated propene hydroformylation and heterogeneous CO2 hydrogenation over Cu(111).</p></div></div></div>

scholarly journals A computational study of the competing reaction mechanisms of the photo-catalytic reduction of CO2 on anatase(101)

2016 ◽  
Vol 18 (36) ◽  
pp. 25010-25021 ◽  
Author(s):  
Chung Man Ip ◽  
Alessandro Troisi
Keyword(s):  
Carbon Dioxide ◽  
Density Functional Theory ◽  
Reaction Mechanisms ◽  
Density Functional ◽  
Catalytic Reduction ◽  
Computational Study ◽  
Density Functional Theory Calculations ◽  
Reaction Pathways ◽  
Functional Theory ◽  
Reduction Of Co2

Three reaction pathways for the photocatalytic reduction of carbon dioxide to methane are investigated with density functional theory calculations.

scholarly journals Activated Self-Resolution and Error-Correction in Catalytic Reaction Networks

2021 ◽  
Author(s):  
Fredrik Schaufelberger ◽  
Olof Ramstrom
Keyword(s):  
Dynamic System ◽  
Error Correction ◽  
Small Molecule ◽  
Catalytic Reaction ◽  
Reaction Network ◽  
Reaction Networks ◽  
Complex Reaction ◽  
Catalytic Systems ◽  
Systems Chemistry ◽  
Mbh Reaction

<p>To understand the emergence of function in complex reaction networks is a primary goal of systems chemistry and origin-of-life studies. Especially challenging is the establishment of systems that simultaneously exhibit several functionality parameters that can be independently tuned. In this work, a multifunctional complex reaction network of nucleophilic small molecule catalysts for the Morita-Baylis-Hillman (MBH) reaction is demonstrated. The dynamic system exhibited triggered self-resolution, preferentially amplifying a specific catalyst/product set out of a many potential alternatives. By utilizing selective reversibility of the products of the reaction set, systemic thermodynamically driven error-correction could also be introduced. To achieve this, a dynamic covalent MBH reaction based on adducts with internal H-transfer capabilities was developed, displaying rate accelerations of retro-MBH reactions up to 104 times. This study demonstrates how efficient self-sorting of catalytic systems can be achieved through an interplay of several complex emergent functionalities.</p>

scholarly journals Activated Self-Resolution and Error-Correction in Catalytic Reaction Networks

2021 ◽  
Author(s):  
Fredrik Schaufelberger ◽  
Olof Ramstrom
Keyword(s):  
Dynamic System ◽  
Error Correction ◽  
Small Molecule ◽  
Catalytic Reaction ◽  
Reaction Network ◽  
Reaction Networks ◽  
Complex Reaction ◽  
Catalytic Systems ◽  
Systems Chemistry ◽  
Mbh Reaction

<p>To understand the emergence of function in complex reaction networks is a primary goal of systems chemistry and origin-of-life studies. Especially challenging is the establishment of systems that simultaneously exhibit several functionality parameters that can be independently tuned. In this work, a multifunctional complex reaction network of nucleophilic small molecule catalysts for the Morita-Baylis-Hillman (MBH) reaction is demonstrated. The dynamic system exhibited triggered self-resolution, preferentially amplifying a specific catalyst/product set out of a many potential alternatives. By utilizing selective reversibility of the products of the reaction set, systemic thermodynamically driven error-correction could also be introduced. To achieve this, a dynamic covalent MBH reaction based on adducts with internal H-transfer capabilities was developed, displaying rate accelerations of retro-MBH reactions up to 104 times. This study demonstrates how efficient self-sorting of catalytic systems can be achieved through an interplay of several complex emergent functionalities.</p>

scholarly journals Selectivity control in hydrogenation through adaptive catalysis using ruthenium nanoparticles on a CO2-responsive support

2021 ◽  
Author(s):  
Alexis Bordet ◽  
Sami El Sayed ◽  
Matthew Sanger ◽  
Kyle J. Boniface ◽  
Deepti Kalsi ◽  
...  
Keyword(s):  
Real Time ◽  
Carbonyl Group ◽  
Catalytic Reaction ◽  
Renewable Resources ◽  
Gas Composition ◽  
Ruthenium Nanoparticles ◽  
Catalytic Systems ◽  
Amine Functionalized ◽  
Hydrogenation Reactions ◽  
Selectivity Control

AbstractWith the advent of renewable carbon resources, multifunctional catalysts are becoming essential to hydrogenate selectively biomass-derived substrates and intermediates. However, the development of adaptive catalytic systems, that is, with reversibly adjustable reactivity, able to cope with the intermittence of renewable resources remains a challenge. Here, we report the preparation of a catalytic system designed to respond adaptively to feed gas composition in hydrogenation reactions. Ruthenium nanoparticles immobilized on amine-functionalized polymer-grafted silica act as active and stable catalysts for the hydrogenation of biomass-derived furfural acetone and related substrates. Hydrogenation of the carbonyl group is selectively switched on or off if pure H2 or a H2/CO2 mixture is used, respectively. The formation of alkylammonium formate species by the catalytic reaction of CO2 and H2 at the amine-functionalized support has been identified as the most likely molecular trigger for the selectivity switch. As this reaction is fully reversible, the catalyst performance responds almost in real time to the feed gas composition.

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