Reaction network flux analysis: Optimization-based evaluation of reaction pathways for biorenewables processing

AIChE Journal ◽  
2011 ◽  
Vol 58 (6) ◽  
pp. 1788-1801 ◽  
Author(s):  
A. Voll ◽  
W. Marquardt
Keyword(s):  
Reaction Network ◽  
Reaction Pathways ◽  
Flux Analysis

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 Bayesian metabolic flux analysis reveals intracellular flux couplings

2019 ◽  
Vol 35 (14) ◽  
pp. i548-i557 ◽  
Author(s):  
Markus Heinonen ◽  
Maria Osmala ◽  
Henrik Mannerström ◽  
Janne Wallenius ◽  
Samuel Kaski ◽  
...  
Keyword(s):  
Steady State ◽  
Metabolic Flux Analysis ◽  
Metabolic Flux ◽  
Reaction Network ◽  
Reaction Rates ◽  
Supplementary Information ◽  
Flux Analysis ◽  
Metabolic Reaction ◽  
Metabolic Systems ◽  
Genome Scale

AbstractMotivationMetabolic flux balance analysis (FBA) is a standard tool in analyzing metabolic reaction rates compatible with measurements, steady-state and the metabolic reaction network stoichiometry. Flux analysis methods commonly place model assumptions on fluxes due to the convenience of formulating the problem as a linear programing model, while many methods do not consider the inherent uncertainty in flux estimates.ResultsWe introduce a novel paradigm of Bayesian metabolic flux analysis that models the reactions of the whole genome-scale cellular system in probabilistic terms, and can infer the full flux vector distribution of genome-scale metabolic systems based on exchange and intracellular (e.g. 13C) flux measurements, steady-state assumptions, and objective function assumptions. The Bayesian model couples all fluxes jointly together in a simple truncated multivariate posterior distribution, which reveals informative flux couplings. Our model is a plug-in replacement to conventional metabolic balance methods, such as FBA. Our experiments indicate that we can characterize the genome-scale flux covariances, reveal flux couplings, and determine more intracellular unobserved fluxes in Clostridium acetobutylicum from 13C data than flux variability analysis.Availability and implementationThe COBRA compatible software is available at github.com/markusheinonen/bamfa.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Discovery of metabolite biomarkers: flux analysis and reaction-reaction network approach

2013 ◽  
Vol 7 (Suppl 2) ◽  
pp. S13 ◽  
Author(s):  
Limin Li ◽  
Hao Jiang ◽  
Yushan Qiu ◽  
Wai-Ki Ching ◽  
Vassilios S Vassiliadis
Keyword(s):  
Reaction Network ◽  
Flux Analysis ◽  
Network Approach

scholarly journals A graph-based network for predicting chemical reaction pathways in solid-state materials synthesis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Matthew J. McDermott ◽  
Shyam S. Dwaraknath ◽  
Kristin A. Persson
Keyword(s):  
Solid State ◽  
Chemical Reaction ◽  
Reaction Pathway ◽  
Reaction Network ◽  
Functional Materials ◽  
Reaction Pathways ◽  
Materials Synthesis ◽  
Pathway Prediction ◽  
Solid State Materials ◽  
Cost Paths

AbstractAccelerated inorganic synthesis remains a significant challenge in the search for novel, functional materials. Many of the principles which enable “synthesis by design” in synthetic organic chemistry do not exist in solid-state chemistry, despite the availability of extensive computed/experimental thermochemistry data. In this work, we present a chemical reaction network model for solid-state synthesis constructed from available thermochemistry data and devise a computationally tractable approach for suggesting likely reaction pathways via the application of pathfinding algorithms and linear combination of lowest-cost paths in the network. We demonstrate initial success of the network in predicting complex reaction pathways comparable to those reported in the literature for YMnO3, Y2Mn2O7, Fe2SiS4, and YBa2Cu3O6.5. The reaction network presents opportunities for enabling reaction pathway prediction, rapid iteration between experimental/theoretical results, and ultimately, control of the synthesis of solid-state materials.

scholarly journals On the use of catalysis to bias reaction pathways in out-of-equilibrium systems

2021 ◽  
Author(s):  
Michelle P. van der Helm ◽  
Tuanke de Beun ◽  
Rienk Eelkema
Keyword(s):  
Chemical Reaction ◽  
Reaction Network ◽  
Steady States ◽  
Chemical Reaction Network ◽  
Reaction Pathways ◽  
Maximum Conversion ◽  
Equilibrium Chemical Reaction ◽  
Equilibrium Chemical ◽  
Non Equilibrium

We show, via simulations, how catalytic control over individual paths in a fuel-driven non-equilibrium chemical reaction network in batch or flow gives rise to responses in maximum conversion, lifetime and steady states.

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>

Towards kinetic control of coordination self-assembly: a case study of a Pd3L6 double-walled triangle to predict the outcomes by a reaction network model

2020 ◽  
Vol 22 (45) ◽  
pp. 26614-26626
Author(s):  
Satoshi Takahashi ◽  
Tomoki Tateishi ◽  
Yuya Sasaki ◽  
Hirofumi Sato ◽  
Shuichi Hiraoka
Keyword(s):  
Numerical Analysis ◽  
Network Model ◽  
Self Assembly ◽  
Reaction Network ◽  
The Self ◽  
Reaction Pathways ◽  
Kinetic Control ◽  
Assembly Process

Numerical analysis of self-assembly process (NASAP) was performed for a Pd3L6 double-walled triangle and revealed the reaction pathways in detail. The prediction of the outcome of the self-assembly under kinetic control was also succeeded.

Direct versus acetalization routes in the reaction network of catalytic HMF etherification

2018 ◽  
Vol 8 (5) ◽  
pp. 1304-1313 ◽  
Author(s):  
P. Lanzafame ◽  
G. Papanikolaou ◽  
S. Perathoner ◽  
G. Centi ◽  
M. Migliori ◽  
...  
Keyword(s):  
Reaction Network ◽  
Zeolite Catalysts ◽  
Reaction Pathways ◽  
Type Zeolite

The etherification of HMF (5-hydroxymethylfurfural) to EMF (5-(ethoxymethyl)furan-2-carbaldehyde) is studied over a series of MFI-type zeolite catalysts containing different heteroatoms (B, Fe, Al), aiming to understand the effect of different isomorph substitutions in the MFI framework on the reaction pathways of HMF conversion.

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