scholarly journals First Principles Micro-kinetic Model of Catalytic Non-oxidative Dehydrogenation of Ethane over Close-packed Metallic Facets

2019 ◽  
Author(s):  
Martin Hangaard Hansen ◽  
Jens K. Nørskov ◽  
Thomas Bligaard
Keyword(s):  
Kinetic Model ◽  
Oxidative Dehydrogenation ◽  
Reaction Network ◽  
Building Blocks ◽  
Light Olefins ◽  
Catalytic Dehydrogenation ◽  
Reaction Conditions ◽  
Model Code ◽  
Ethane Dehydrogenation ◽  
Oxidative Dehydrogenation Of Ethane

<div> <div> <p>Catalytic dehydrogenation of light alkanes may other more efficient routes to selectively producing light olefins, which are some of the most important chemical building blocks in the industry, in terms of scale. We present a descriptor based micro-kinetic model of the trends in selectivity and activity of non-oxidative dehydrogenation of ethane over close-packed metal facets and through varied reaction conditions. Our model predicts and explains the experimentally observed promotion effect on turnover rate from co-feeding hydrogen as an effect of the shifting equilibria in steady state. At low conversion reaction conditions over Pt, the path to ethene goes through ethane dehydrogenation to ethyl, CH 3 CH 2 *, then to ethene while the non-selective pathway to methane and deeply dehydrogenated species is predicted to go through dehydrogenation via CH 3 CH*. This implies that the desorption step of ethene is not the limiting step for selectivity and that geometric effects that stabilize CH 2 CH 2 * compared to CH 3 CH* are desirable properties of a better catalyst. Removing reactive bridge and 3-fold sites facilitates this, which may be achievable by sufficient concentrations of tin in platinum. The included model code furthermore provides a base for easy tuning and for expanding the study to other thermodynamic conditions, other facets, alloys or the reaction network to longer hydrocarbons or to oxidative pathways.</p> </div> </div>

scholarly journals First Principles Micro-kinetic Model of Catalytic Non-oxidative Dehydrogenation of Ethane over Close-packed Metallic Facets

2019 ◽  
Author(s):  
Martin Hangaard Hansen ◽  
Jens K. Nørskov ◽  
Thomas Bligaard
Keyword(s):  
Kinetic Model ◽  
Oxidative Dehydrogenation ◽  
Reaction Network ◽  
Building Blocks ◽  
Light Olefins ◽  
Catalytic Dehydrogenation ◽  
Reaction Conditions ◽  
Model Code ◽  
Ethane Dehydrogenation ◽  
Oxidative Dehydrogenation Of Ethane

<div> <div> <p>Catalytic dehydrogenation of light alkanes may other more efficient routes to selectively producing light olefins, which are some of the most important chemical building blocks in the industry, in terms of scale. We present a descriptor based micro-kinetic model of the trends in selectivity and activity of non-oxidative dehydrogenation of ethane over close-packed metal facets and through varied reaction conditions. Our model predicts and explains the experimentally observed promotion effect on turnover rate from co-feeding hydrogen as an effect of the shifting equilibria in steady state. At low conversion reaction conditions over Pt, the path to ethene goes through ethane dehydrogenation to ethyl, CH 3 CH 2 *, then to ethene while the non-selective pathway to methane and deeply dehydrogenated species is predicted to go through dehydrogenation via CH 3 CH*. This implies that the desorption step of ethene is not the limiting step for selectivity and that geometric effects that stabilize CH 2 CH 2 * compared to CH 3 CH* are desirable properties of a better catalyst. Removing reactive bridge and 3-fold sites facilitates this, which may be achievable by sufficient concentrations of tin in platinum. The included model code furthermore provides a base for easy tuning and for expanding the study to other thermodynamic conditions, other facets, alloys or the reaction network to longer hydrocarbons or to oxidative pathways.</p> </div> </div>

scholarly journals First Principles Micro-kinetic Model of Catalytic Non-oxidative Dehydrogenation of Ethane over Close-packed Metallic Facets

2018 ◽  
Author(s):  
Martin Hangaard Hansen ◽  
Jens K. Nørskov ◽  
Thomas Bligaard
Keyword(s):  
Kinetic Model ◽  
Oxidative Dehydrogenation ◽  
Reaction Network ◽  
Building Blocks ◽  
Platinum Group Metals ◽  
Light Olefins ◽  
Catalytic Dehydrogenation ◽  
Ethane Dehydrogenation ◽  
Oxidative Dehydrogenation Of Ethane ◽  
Thermodynamic Conditions

<div> <div> <div> <p>Catalytic dehydrogenation of light alkanes may offer more efficient routes to selectively producing light olefins, which are some of the most important chemical building blocks in the industry, in terms of scale. We present a descriptor based micro-kinetic model of the trends in selectivity and activity of the non-oxidative dehydrogenation of ethane over the close-packed metal facets and through varied thermodynamic conditions. Our model predicts and explains the experimentally observed promotion effect on turnover rate from co-feeding hydrogen as an effect of the shifting equilibria in steady state. Our model predicts platinum group metals to have the most intrinsically active close-packed facets for ethane dehydrogenation and adding small amounts of tin to platinum is predicted to promote selectivity through a purely electronic effect. The trend in selectivity is understood through linear scaling relations and it is due to the re-action mechanism predicted by the model, which shows the path to ethene going through ethane dehydrogenation to ethyl, CH3CH2*, then to ethene. The non-selective pathway to methane and deeply dehydrogenated species is predicted to go through dehydrogenation via CH3CH*. This implies that the desorption step of ethene is not the limiting step for selectivity and that geometric effects that stabilize CH2CH2* compared to CH3CH* are desirable properties of a better catalyst. Removing reactive bridge and 3-fold sites facilitates this, which may be achievable by sufficient concentrations of tin in platinum. The included model code furthermore provides a base for easy tuning and reproduction and for expanding the study to other thermodynamic conditions, other facets, alloys or the reaction network to longer hydrocarbons or to oxidative pathways. </p> </div> </div> </div>

Oxidative dehydrogenation of ethane to ethylene over phase-pure M1 MoVNbTeOx catalysts in a micro-channel reactor

2015 ◽  
Vol 5 (5) ◽  
pp. 2807-2813 ◽  
Author(s):  
Bozhao Chu ◽  
Lara Truter ◽  
Tjeerd Alexander Nijhuis ◽  
Yi Cheng
Keyword(s):  
Heat Transfer ◽  
Oxidative Dehydrogenation ◽  
Fixed Bed ◽  
Fixed Bed Reactor ◽  
Micro Channel ◽  
Channel Reactor ◽  
Reaction Conditions ◽  
Oxidative Dehydrogenation Of Ethane ◽  
Phase Pure

Due to its excellent heat transfer ability, the micro-channel reactor with coated phase-pure M1 catalysts can achieve reactor productivity nearly 5 times higher than that of a traditional fixed-bed reactor under the same reaction conditions in oxidative dehydrogenation of ethane (ODHE).

Kinetic Study of the Oxidative Dehydrogenation of Cyclohexane over Mg3(VO4)2 Catalyst

2012 ◽  
Vol 550-553 ◽  
pp. 379-382
Author(s):  
Mei Jin ◽  
Ping Lu ◽  
Guo Xian Yu
Keyword(s):  
Kinetic Model ◽  
Kinetic Study ◽  
Oxidative Dehydrogenation ◽  
Power Law ◽  
Rate Constants ◽  
Reaction Network ◽  
Rough Approximation ◽  
Dehydrogenation Of Cyclohexane ◽  
Exponential Factors ◽  
Kinetic Investigations

A Mg3(VO4)2catalyst was synthesized and investigated for the oxidative dehydrogenation of cyclohexane to cyclohexene. Integral measurements were performed to determine the reaction network and products distribution, and differential measurements for kinetic investigations. The kinetic study indicated the oxidative dehydrogenation of cyclohexane to cyclohexene follow a parallel-consecutive network. The power law kinetic model was considered as a rough approximation of the experimental results. The rate constants, which included the activation energies, the pre-exponential factors as well as the orders of cyclohexane and oxygen, were evaluated.

Intrinsic kinetic model for oxidative dehydrogenation of ethane over MoVTeNb mixed metal oxides: A mechanistic approach

2020 ◽  
Vol 383 ◽  
pp. 123195 ◽  
Author(s):  
Philipp J. Donaubauer ◽  
Daniel M. Melzer ◽  
Klaus Wanninger ◽  
Gerhard Mestl ◽  
Maricruz Sanchez-Sanchez ◽  
...  
Keyword(s):  
Kinetic Model ◽  
Metal Oxides ◽  
Oxidative Dehydrogenation ◽  
Mixed Metal Oxides ◽  
Mixed Metal ◽  
Oxidative Dehydrogenation Of Ethane ◽  
Mechanistic Approach ◽  
Intrinsic Kinetic

scholarly journals Searching for the origin of life using a computational search engine

2018 ◽  
Author(s):  
Jan H. Jensen
Keyword(s):  
Metabolic Pathways ◽  
Reaction Network ◽  
Building Blocks ◽  
Reaction Networks ◽  
Early Earth ◽  
Complex Reaction ◽  
Reaction Conditions ◽  
Computational Search ◽  
The Origin Of Life ◽  
Simple Molecules

Life is essentially an organised network of chemical reactions (metabolic pathways) that can create copies of itself given a source of energy. How was this complex reaction network formed from the simple molecules that were present on the early Earth? I will answer this question by simulating how simple reaction networks evolve starting from different combinations of building blocks and reaction conditions. Computer simulations will allow me to search many more combinations than is possible experimentally, thereby increasing the chances of finding reaction networks that resemble those found in modern cells. Finding a plausible explanation for how life originated on Earth will not only have profound implications for how we view ourselves and other species, but also give us a much better idea of how likely life is to have evolved on other planets.

scholarly journals Searching for the origin of life using a computational search engine

2018 ◽  
Author(s):  
Jan H. Jensen
Keyword(s):  
Metabolic Pathways ◽  
Reaction Network ◽  
Building Blocks ◽  
Reaction Networks ◽  
Early Earth ◽  
Complex Reaction ◽  
Reaction Conditions ◽  
Computational Search ◽  
The Origin Of Life ◽  
Simple Molecules

Life is essentially an organised network of chemical reactions (metabolic pathways) that can create copies of itself given a source of energy. How was this complex reaction network formed from the simple molecules that were present on the early Earth? I will answer this question by simulating how simple reaction networks evolve starting from different combinations of building blocks and reaction conditions. Computer simulations will allow me to search many more combinations than is possible experimentally, thereby increasing the chances of finding reaction networks that resemble those found in modern cells. Finding a plausible explanation for how life originated on Earth will not only have profound implications for how we view ourselves and other species, but also give us a much better idea of how likely life is to have evolved on other planets.

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