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 Uncertainty quantification for quantum chemical models of complex reaction networks

2016 ◽  
Vol 195 ◽  
pp. 497-520 ◽  
Author(s):  
Jonny Proppe ◽  
Tamara Husch ◽  
Gregor N. Simm ◽  
Markus Reiher
Keyword(s):  
Free Energy ◽  
Electronic Structure ◽  
State Space ◽  
Time Scales ◽  
Reaction Network ◽  
Reaction Networks ◽  
Multiple Time Scales ◽  
Complex Reaction ◽  
Discrete State ◽  
Continuous State

For the quantitative understanding of complex chemical reaction mechanisms, it is, in general, necessary to accurately determine the corresponding free energy surface and to solve the resulting continuous-time reaction rate equations for a continuous state space. For a general (complex) reaction network, it is computationally hard to fulfill these two requirements. However, it is possible to approximately address these challenges in a physically consistent way. On the one hand, it may be sufficient to consider approximate free energies if a reliable uncertainty measure can be provided. On the other hand, a highly resolved time evolution may not be necessary to still determine quantitative fluxes in a reaction network if one is interested in specific time scales. In this paper, we present discrete-time kinetic simulations in discrete state space taking free energy uncertainties into account. The method builds upon thermo-chemical data obtained from electronic structure calculations in a condensed-phase model. Our kinetic approach supports the analysis of general reaction networks spanning multiple time scales, which is here demonstrated for the example of the formose reaction. An important application of our approach is the detection of regions in a reaction network which require further investigation, given the uncertainties introduced by both approximate electronic structure methods and kinetic models. Such cases can then be studied in greater detail with more sophisticated first-principles calculations and kinetic simulations.

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 Molecular Diversity and Network Complexity in Growing Protocells

Life ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 53
Author(s):  
Atsushi Kamimura ◽  
Kunihiko Kaneko
Keyword(s):  
Molecular Species ◽  
Catalytic Reaction ◽  
Molecular Diversity ◽  
Reaction Network ◽  
Cellular Growth ◽  
Reaction Networks ◽  
Cell Reproduction ◽  
A Cell ◽  
Molecular Components ◽  
Cellular Components

A great variety of molecular components is encapsulated in cells. Each of these components is replicated for cell reproduction. To address the essential role of the huge diversity of cellular components, we studied a model of protocells that convert resources into catalysts with the aid of a catalytic reaction network. As the resources were limited, the diversity in the intracellular components was found to be increased to allow the use of diverse resources for cellular growth. A scaling relation was demonstrated between resource abundances and molecular diversity. In the present study, we examined how the molecular species diversify and how complex catalytic reaction networks develop through an evolutionary course. At some generations, molecular species first appear as parasites that do not contribute to the replication of other molecules. Later, the species turn into host species that contribute to the replication of other species, with further diversification of molecular species. Thus, a complex joint network evolves with this successive increase in species. The present study sheds new light on the origin of molecular diversity and complex reaction networks at the primitive stage of a cell.

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 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.

scholarly journals An intermediate level of abstraction for computational systems chemistry

2017 ◽  
Vol 375 (2109) ◽  
pp. 20160354 ◽  
Author(s):  
Jakob L. Andersen ◽  
Christoph Flamm ◽  
Daniel Merkle ◽  
Peter F. Stadler
Keyword(s):  
Large Scale ◽  
Optimization Techniques ◽  
Reaction Networks ◽  
Computational Techniques ◽  
Complex Reaction ◽  
Level Of Abstraction ◽  
Systems Chemistry ◽  
Quantum Chemical Methods ◽  
The Right ◽  
Computational Systems

Computational techniques are required for narrowing down the vast space of possibilities to plausible prebiotic scenarios, because precise information on the molecular composition, the dominant reaction chemistry and the conditions for that era are scarce. The exploration of large chemical reaction networks is a central aspect in this endeavour. While quantum chemical methods can accurately predict the structures and reactivities of small molecules, they are not efficient enough to cope with large-scale reaction systems. The formalization of chemical reactions as graph grammars provides a generative system, well grounded in category theory, at the right level of abstraction for the analysis of large and complex reaction networks. An extension of the basic formalism into the realm of integer hyperflows allows for the identification of complex reaction patterns, such as autocatalysis, in large reaction networks using optimization techniques. This article is part of the themed issue ‘Reconceptualizing the origins of life’.

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