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Enzyme catalysis in reactors for industrial applications usually require an external intervention of the species involved in the chemical reactions. We analyze the most elementary open enzyme catalysis with competitive inhibition where a time-dependent inflow of substrate and inhibitor supplies is modeled by almost periodic functions. We prove global stability of an almost periodic solution for the non-autonomous dynamical system arising from the mass-law action. This predicts a well behaved situation in which the reactor oscillates with global stability. This is a first case study in the path toward broader global stability results regarding intraspecific and monotone open reaction networks. [ABSTRACT FROM AUTHOR]

Industrial implementation of the heterogeneously catalyzed CO hydrogenation to higher alcohols is highly desired, but deeper insights into the reaction mechanisms and active sites are still needed. This review summarizes the established and well‐investigated cobalt‐based catalysts and the mechanisms resulting in oxygenate formation. Recently, a cobalt‐based system derived from Mn‐Co‐based Prussian blue analogs by pyrolysis has shown great potential for higher‐alcohol synthesis. In addition to the heterogeneously catalyzed reaction pathways involved in Fischer‐Tropsch synthesis and methanol synthesis, the homogeneously catalyzed reaction pathways like reductive olefin hydroformylation and reductive primary alcohol carbonylation were found to play a key role. [ABSTRACT FROM AUTHOR]

Creation of complex chemical mechanisms for hydrocarbon pyrolysis and combustion is challenging due to the large number of species and reactions involved. Reactive molecular dynamics (RMD) enables the simulation of thousands of reactions and the discovery of previously unknown components of the reaction network. However, due to the inherent imprecision of reactive force fields, it is necessary to verify RMD‐obtained reaction paths using more accurate methods such as Density Functional Theory (DFT). We demonstrate a method for identification and confirmation of reaction pathways from RMD that supplement an established mechanism, using the example of benzene formation from n‐heptane and iso‐octane pyrolysis. We establish a validation workflow to extract reaction geometries from RMD and optimize transition states using the Nudged‐Elastic‐Band method on semi‐empirical and quantum mechanical levels of theory. Our findings demonstrate that the widely recognized ReaxFF parameterization, CHO2016, can identify known pathways from a established soot formation mechanism while also indicating new ones. We also show that CHO2016 underestimates hydrogen migration barriers by up to 40kcalmol−1$40\,{\rm {kcal\,mol}}^{-1}$ as compared to DFT and can lower activation barriers significantly for spin‐forbidden reactions. This highlights the necessity for validation or potentially even reparametrization of CHO2016. [ABSTRACT FROM AUTHOR]

The formation of humins hampers the large-scale production of 5-hydroxymethylfurfural (HMF) in biorefinery. Here, a detailed reaction network of humin formation at the initial stage of fructose-to-HMF dehydration in water is delineated by combined experimental, spectroscopic, and theoretical studies. Three bimolecular reaction pathways to build up soluble humins are demonstrated. That is, the intermolecular etherification of β-furanose at room temperature initiates the C12 path, whereas the C–C cleavage of α-furanose at 130–150 °C leads to C11 path, and that of open-chain fructose at 180 °C to C11′ path. The successive intramolecular dehydrations and condensations of the as-formed bimolecular intermediates lead to three types of soluble humins. We show that the C12 path could be restrained by using HCl or AlCl3 catalyst, and both the C12 and C11′ paths could be effectively inhibited by adding THF as a co-solvent or accelerating heating rate via microwave heating. [ABSTRACT FROM AUTHOR]

Dehydrochlorination of 1,3‐dichloropropanol with alkali is a key step to industrially produce epichlorohydrin. But there are many side reactions involved in the synthesis process. In this work, a complete mechanism and kinetics investigation of the related reaction network was constructed. Density functional theory simulation method was first used to simulate the possible reactions so as to confirm the reaction mechanism and simplify the reaction network. Based on the simulation results, the complex reaction network was simplified into a three‐step consecutive reaction. The kinetic parameters of the three consecutive steps, including the order of the reaction, the pre‐exponential factor, and activation energy, were experimentally determined by conductance and other methods. All the experimental results are basically consistent with the simulation. The obtained kinetics data provide a basis for epichlorohydrin synthesis process optimization. [ABSTRACT FROM AUTHOR]

For reaction networks arising in systems biology, the capacity for two or more steady states, that is, multistationarity, is an important property that underlies biochemical switches. Another property receiving much attention recently is absolute concentration robustness (ACR), which means that some species concentration is the same at all positive steady states. In this work, we investigate the prevalence of each property while paying close attention to when the properties occur together. Specifically, we consider a stochastic block framework for generating random networks and prove edge-probability thresholds at which, with high probability, multistationarity appears and ACR becomes rare. We also show that the small window in which both properties occur only appears in networks with many species. Taken together, our results confirm that, in random reversible networks, ACR and multistationarity together, or even ACR on its own, is highly atypical. Our proofs rely on two prior results, one pertaining to the prevalence of networks with deficiency zero and the other "lifting"" multistationarity from small networks to larger ones. [ABSTRACT FROM AUTHOR]

The hydroconversion of γ-valerolactone (GVL) over Co/SiO2 catalyst proceeds in a complex reaction network, resulting in 2-methyltetrahydrofuran (2-MTHF) as the main product, and C4–C5 alcohol and alkane side-products. The catalyst was shown to contain Co0 sites and Lewis acid (Co2+ ion)/Lewis base (O2− ion) pair sites, active for hydrogenation/dehydrogenation and dehydration reactions, respectively. The initial reaction step was confirmed to be the hydrogenation of GVL to key intermediate 1,4-pentanediol (1,4-PD). Cyclodehydration of 1,4-PD led to the main product 2-MTHF, whereas its dehydration/hydrogenation gave 1-pentanol and 2-pentanol side-products, with about the same yield. In contrast, 2-pentanol was the favored alcohol product of 2-MTHF hydrogenolysis. 2-Butanol was formed by decarbonylation of 4-hydroxypentanal intermediate. The latter was the product of 1,4-PD dehydrogenation. Alkanes were formed from the alcohol side-products via dehydration/hydrogenation reactions. [ABSTRACT FROM AUTHOR]

We consider reaction networks that admit a singular perturbation reduction in a certain parameter range. The focus of this paper is on deriving “small parameters” (briefly for small perturbation parameters), to gauge the accuracy of the reduction, in a manner that is consistent, amenable to computation and permits an interpretation in chemical or biochemical terms. Our work is based on local timescale estimates via ratios of the real parts of eigenvalues of the Jacobian near critical manifolds. This approach modifies the one introduced by Segel and Slemrod and is familiar from computational singular perturbation theory. While parameters derived by this method cannot provide universal quantitative estimates for the accuracy of a reduction, they represent a critical first step toward this end. Working directly with eigenvalues is generally unfeasible, and at best cumbersome. Therefore we focus on the coefficients of the characteristic polynomial to derive parameters, and relate them to timescales. Thus, we obtain distinguished parameters for systems of arbitrary dimension, with particular emphasis on reduction to dimension one. As a first application, we discuss the Michaelis–Menten reaction mechanism system in various settings, with new and perhaps surprising results. We proceed to investigate more complex enzyme catalyzed reaction mechanisms (uncompetitive, competitive inhibition and cooperativity) of dimension three, with reductions to dimension one and two. The distinguished parameters we derive for these three-dimensional systems are new. In fact, no rigorous derivation of small parameters seems to exist in the literature so far. Numerical simulations are included to illustrate the efficacy of the parameters obtained, but also to show that certain limitations must be observed. [ABSTRACT FROM AUTHOR]

It is standard in chemistry to represent a sequence of reactions by a single overall reaction, often called a complex reaction in contrast to an elementary reaction. Photosynthesis $6 \text{CO}_2+6 \text{H}_2\text{O} \longrightarrow \text{C}_6\text{H}_{12}\text{O}_6 + 6 \text{O}_2$ is an example of such complex reaction. We introduce a mathematical operation that corresponds to summing two chemical reactions. Specifically, we define an associative and non-communicative operation on the product space ${\mathbb{N}}_0^n\times {\mathbb{N}}_0^n$ (representing the reactant and the product of a chemical reaction, respectively). The operation models the overall effect of two reactions happening in succession, one after the other. We study the algebraic properties of the operation and apply the results to stochastic reaction networks (RNs), in particular to reachability of states, and to reduction of RNs. [ABSTRACT FROM AUTHOR]

Direct infusion nanoelectrospray high-resolution mass spectrometry (DI-nESI-HRMS) is a promising tool for high-throughput metabolomics analysis. However, metabolite assignment is limited by the inadequate mass accuracy and chemical space of the metabolome database. Here, a serum metabolome characterization method was proposed to make full use of the potential of DI-nESI-HRMS. Different from the widely used database search approach, unambiguous formula assignments were achieved by a reaction network combined with mass accuracy and isotopic patterns filter. To provide enough initial known nodes, an initial network was directly constructed by known metabolite formulas. Then experimental formula candidates were screened by the predefined reaction with the network. The effects of sources and scales of networks on assignment performance were investigated. Further, a scoring rule for filtering unambiguous formula candidates was proposed. The developed approach was validated by a pooled serum sample spiked with reference standards. The coverage and accuracy rates for the spiked standards were 98.9% and 93.6%, respectively. A total of 1958 monoisotopic features were assigned with unique formula candidates for the pooled serum, which is twice more than the database search. Finally, a case study of serum metabolomics in diabetes was carried out using the developed method. [ABSTRACT FROM AUTHOR]

Algorithms that automatically explore the chemical space have been limited to chemical systems with a low number of atoms due to expensive involved quantum calculations and the large amount of possible reaction pathways. The method described here presents a novel solution to the problem of chemical exploration by generating reaction networks with heuristics based on chemical theory. First, a second version of the reaction network is determined through molecular graph transformations acting upon functional groups of the reacting. Only transformations that break two chemical bonds and form two new ones are considered, leading to a significant performance enhancement compared to previously presented algorithm. Second, energy barriers for this reaction network are estimated through quantum chemical calculations by a growing string method, which can also identify non‐octet species missed during the previous step and further define the reaction network. The proposed algorithm has been successfully applied to five different chemical reactions, in all cases identifying the most important reaction pathways. [ABSTRACT FROM AUTHOR]

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We develop and test a relatively simple enhancement of the classical model reduction method applied to a class of chemical networks with mass conservation properties. Both the methods, being (i) the standard quasi-steady-state approximation method, and (ii) the novel so-called delayed quasi-steady-state approximation method, firstly proposed by Vejchodský (2014), are extensively presented. Both theoretical and numerical issues related to the setting of delays are discussed. Namely, for one slightly modified variant of an enzyme-substrate reaction network (Michaelis-Menten kinetics), the comparison of the full non-reduced system behavior with respective variants of reduced model is presented and the results discussed. Finally, some future prospects related to further applications of the delayed quasi-steady-state approximation method are proposed. [ABSTRACT FROM AUTHOR]

Absolute concentration robustness (ACR) and concordance are novel concepts in the theory of robustness and stability within Chemical Reaction Network Theory. In this paper, we have extended Shinar and Feinberg’s reaction network analysis approach to the insulin signaling system based on recent advances in decomposing reaction networks. We have shown that the network with 20 species, 35 complexes, and 35 reactions is concordant, implying at most one positive equilibrium in each of its stoichiometric compatibility class. We have obtained the system’s finest independent decomposition consisting of 10 subnetworks, a coarsening of which reveals three subnetworks which are not only functionally but also structurally important. Utilizing the network’s deficiency-oriented coarsening, we have developed a method to determine positive equilibria for the entire network. Our analysis has also shown that the system has ACR in 8 species all coming from a deficiency zero subnetwork. Interestingly, we have shown that, for a set of rate constants, the insulin-regulated glucose transporter GLUT4 (important in glucose energy metabolism), has stable ACR. [ABSTRACT FROM AUTHOR]

The mechanism of reaction in isobutane/2-butene alkylation systems is extremely complicated, accompanied by numerous side reactions. Therefore, a comprehensive understanding of the reaction pathways in this system is essential for an in-depth discussion of the reaction mechanism and for improving the selectivity of the major products (clean fuel blend components). The alkylation of isobutane/2-butene was studied using a self-made intermittent reaction device with a metering, cooling, reaction, vacuum and analysis system. The alkylates were qualitatively and quantitatively analyzed using a capillary gas chromatography-mass spectrometry-data system (CGC-MS-DS) and capillary gas chromatography with flame ionization detection (CCGC-FID), respectively, and the precision and recovery of the quantitative analytical methods were verified. The results showed that the relative standard deviation (RSD) of the standard sample was below 0.78%, and the recoveries were from 98.53% to 102.85%. Under the specified reaction conditions, 79 volatile substances were identified from the alkylates, and the selectivity of C8 and trimethylpentanes (TMPs) reached 63.63% and 53.81%, respectively. The changes of the main chemical components in the alkylation reaction with time were tracked and analyzed, based on which reaction pathways were determined, and a complex reaction network containing the main products' and the by-products' generation pathway was constructed. [ABSTRACT FROM AUTHOR]

Highlights: Second-derivative (DDTG) curves helped overcome the challenges of overlapping peaks in the DTG curves of wheat straw; Deconvolution methods lead to high errors in the estimation of lignin content; Curve-fitting methods lead to lower errors when determining the kinetics of biomass degradation, especially for hemicellulose; Reaction networks were modified to consider K content to describe straw pyrolysis. Wheat straw is a renewable agricultural by-product that is currently underutilized in the production of bioenergy and bioproducts due to its high ash content, as well as high transport costs due to its low volumetric energy density. The thermogravimetric analysis of this material produces derivative curves with a single broad peak, making it difficult to identify the three conventional pseudo-components (cellulose, hemicellulose, and lignin), which is resolved using the second derivative to determine inflection points. Model-fitting methods and isoconversional methods were applied to determine the degradation kinetics of wheat straw at two different particle sizes, as well as that of a reference feedstock (beech wood), and the obtained values were used to divide the degradation curves to be compared to the experimental data. Seven different pyrolysis reaction networks from the literature were given a similar treatment to determine which provides the best estimation of the actual pyrolysis process for the case of the feedstocks under study. The impact of the potassium content in the feedstock was considered by comparing the original pathway with a modification dependent on the experimental potassium content and an estimated optimum value. [ABSTRACT FROM AUTHOR]

Ethylenediamine is an important organic chemical and commercially produced from non‐renewable starting material. In the present work, amination of ethylene glycol to ethylenediamine was studied using an aqueous ammonia as ammonia source. A series of supported bimetallic catalysts were prepared by impregnation method and characterized by means of H2‐TPR, H2‐TPD, XRD, XPS and N2 adsorption‐desorption. Their catalytic performance for amination of ethylene glycol was investigated and Co−Cu/γ‐Al2O3 catalyst exhibited high activity and good selectivity to ethylenediamine. There exists obvious interaction and synergistic effect between Cu and Co in Co−Cu/γ‐Al2O3 for lowering catalyst reduction temperature and improving catalytic performance separately. The selectivity of ethylenediamine and ethanolamine respectively attained 45.7 % and 23.7 % at an ethylene glycol conversion of 41.5 % under the suitable reaction conditions. On this basis, a majority of by‐products in the amination of ethylene glycol were identified by gas chromatography‐mass spectrometry analysis and a reaction network was proposed. [ABSTRACT FROM AUTHOR]

The reaction pathways of higher alcohol synthesis over a bulk Co−Cu catalyst (Co : Cu=2 : 1) were investigated by applying high‐pressure pulse experiments as a surface‐sensitive operando method at 280 °C and 60 bar. Using high‐pressure CO and H2 pulses in a syngas flow with a H2:CO ratio of 1, it was shown that the surface of the working 2CoCu catalyst is saturated with adsorbed CO, but not with adsorbed atomic hydrogen, because only the H2 pulses increased the yields of all alcohols and alkanes. The reverse water gas shift reaction (WGSR) was investigated by pulsing CO2. The CO2 pulses poisoned the formation of methanol, ethanol, and 1‐propanol, and the absence of significant CO and H2O responses indicates that the WGSR is not efficiently catalyzed by the applied 2CoCu catalyst excluding the presence of exposed Cu0 sites. A series of ethylene pulses showed that when a threshold mole fraction of ethylene of about 1 vol % is surpassed, 2CoCu is an active catalyst for the hydroformylation of ethylene to 1‐propanol pointing to the presence of highly coordinatively unsaturated Co sites. [ABSTRACT FROM AUTHOR]

Reaction networks are commonly used within the mathematical biology and mathematical chemistry communities to model the dynamics of interacting species. These models differ from the typical graphs found in random graph theory since their vertices are constructed from elementary building blocks, i.e. the species. We consider these networks in an Erdös–Rényi framework and, under suitable assumptions, derive a threshold function for the network to have a deficiency of zero, which is a property of great interest in the reaction network community. Specifically, if the number of species is denoted by n and the edge probability by $p_n$ , then we prove that the probability of a random binary network being deficiency zero converges to 1 if $p_n\ll r(n)$ as $n \to \infty$ , and converges to 0 if $p_n \gg r(n)$ as $n \to \infty$ , where $r(n)=\frac{1}{n^3}$. [ABSTRACT FROM AUTHOR]

The phase space data produced in molecular dynamics (MD) simulations of many-atom systems contain complete classical descriptions of the processes determined by the force field for the specific initial conditions. The usefulness of the simulation results comes from gleaning physically meaningful information from the mass of phase space points. This is especially difficult in the case of chemical reactions in bulk phases. Determining the major pathways from reactants to products directly from MD simulation results and without assuming a given mechanism is particularly challenging. We propose the reaction stream method based on the cluster representation for gases to identify, directly from MD simulations, the sequences of isolated reactions that are responsible for progress of the overall chemistry in complex reactions. The goal is to obviate the need for pre-convinced mechanisms to characterize the overall chemistry. To illustrate the applicability of the reaction stream method, we identify the dominant reaction pathways for the dissociation of H2O2 in MD simulations with the ReaxFF force field. The significance of rare reaction pathways to predict the progress of the evolving chemistry is also studied. [ABSTRACT FROM AUTHOR]

A micro-kinetic reaction rate analysis based on elementary reaction network was conducted to investigate the role of water in BRM. The reaction rate analysis showed that water was much easier than methane to dissociate H*, which would promote CO2 conversion via its key step CO2* + H* → COOH* + *. CO2 conversion ratio increased by 23.18%, while water content increased from 0 to 20%. More O* would be generated as water existed, which would switch the most difficult step of CH3* + * → CH2* + H* along the CH4 conversion path to much easier step of CH3* + O* → CH2* + OH*. This resulted in CH4 conversion ratio increasing from 85.77 to 92.45%, as water content increased from 0 to 20%. The third role of water was to change the major path of C* conversion, as the presence of water proved abundant OH*. And the C* conversion would follow a much easier path of C* + OH* → CO* + H* rather than C* + O* → CO* + * any more as pure dry reforming. This resulted in reducing surface coverage of C*, which was believed to be the precursor of carbon deposition. This might be the very result that water was benefit for inhibiting carbon deposition. The results in this paper could help optimize and promote the industrialization process of BRM. [ABSTRACT FROM AUTHOR]

In this work we characterize the set of persistent species in dynamical systems related to chemical reaction networks. Chemical reaction networks consist of a set of species and a set of reaction rules describing the interactions between the species. From a reaction network, by differentiation with respect to time and space, a reaction-diffusion system (RDS) can be derived describing the dynamics of the concentrations of the species. We show how double integration with respect to time and space of the solutions of the RDS conversely leads back to the reaction network and reveals all the possibly persistent subsets of species. We show that organizations as defined in chemical organization theory (COT) are strongly related to the persistent subsets of species. Organizations are subsets of species that have two properties. First, they are closed, that is, there is no reaction running on them that produces new species which are not contained in the organizations. Second, organizations are selfmaintaining. By additionally allowing for the distribution of species, we generalize organizations towards distributed organizations (DOs). After introducing our concept of persistence as the first main result of this study, we prove that for a given reaction network the set of DOs is always a lattice. The second main result is that the set of persistent species of a solution of an RDS is always a DO. By linking these two results we achieve a connection between persistence concerning a single solution of an RDS and persistence with regard to all solutions of all RDSs having one and the same underlying reaction network. We show how this strongly benefits reaction network analysis. By presenting simulation results performed with MATLAB, we illustrate the discussed phenomena. [ABSTRACT FROM AUTHOR]

Deficiency zero is an important network structure and has been the focus of many celebrated results within reaction network theory. In our previous paper Prevalence of deficiency zero reaction networks in an Erdős-Rényi framework, we provided a framework to quantify the prevalence of deficiency zero among randomly generated reaction networks. Specifically, given a randomly generated binary reaction network with n species, with an edge between two arbitrary vertices occurring independently with probability p n , we established the threshold function r (n) = 1 n 3 such that the probability of the random network being deficiency zero converges to 1 if p n r (n) → 0 and converges to 0 if p n r (n) → ∞ , as n → ∞ . With the base Erdős-Rényi framework as a starting point, the current paper provides a significantly more flexible framework by weighting the edge probabilities via control parameters α i , j , with i , j ∈ { 0 , 1 , 2 } enumerating the types of possible vertices (zeroth, first, or second order). The control parameters can be chosen to generate random reaction networks with a specific underlying structure, such as "closed" networks with very few inflow and outflow reactions, or "open" networks with abundant inflow and outflow. Under this new framework, for each choice of control parameters { α i , j } , we establish a threshold function r (n , { α i , j }) such that the probability of the random network being deficiency zero converges to 1 if p n r (n , { α i , j }) → 0 and converges to 0 if p n r (n , { α i , j }) → ∞ . [ABSTRACT FROM AUTHOR]

Summary: Kinetic of anisole upgrading as a model compound of lignin‐derived pyrolysis bio‐oil to jet‐grade fuels via catalytic hydrotreatment process has been investigated. Hydrodeoxygenation (HDO) process has been performed in a fixed‐bed tubular reactor at operating temperature of 573 to 723 K, space velocity of 3 to 120 (anisole weight)/(catalyst weight × h), and hydrogen pressure of 8 bar. Benzene formation through demethoxylation reaction of anisole was identified to be the primary reaction route in contrast to demethylation, alkylation, and transalkylation reaction classes, which are more dominant for synthesized Cu/γ‐Al2O3 catalyst. Benzene is formed as the primary product through HDO of phenol assigning the lowest activation energy of 1.18 kJ/mol. Toluene and hexamethylbenzene are derived from alkylation reaction of benzene. Phenol is produced rapidly with highest selectivity among different products as the primary product via hydrogenolysis reaction. According to the kinetic data, phenol formation possesses the highest activation energy of about 59 kJ/mol. Moreover, 2‐methylphenol and other phenol‐derivatives are produced from alkylation and transalkylation reactions of phenol. The developed comprehensive quantitative reaction network for anisole catalytic hydrotreatment over Cu/γ‐Al2O3 is in appropriate agreement with previous studies. [ABSTRACT FROM AUTHOR]

The cracking furnace is the core of an ethylene plant. An optimization method is built based on the integration of reaction network. Starting from atomic scope, an algebraic procedure is used to seek all possible reactions and establish the reaction network. Based on this, the reaction network is integrated and simplified to identify the variation rate of every component. The calculation procedure is developed to identify the variation of each component's concentration and the selectivity and identify the optimal furnace parameters. For the studied furnace, the residence time corresponding to the minimum by-product production is identified to be 0.4 s, and its by-product generation is 4.3% less than that at the initial residence time (0.3 s). [ABSTRACT FROM AUTHOR]

Tyrosol β-galactoside (TG) is a phenylethanoid glycoside with proven neuroprotective properties. This work deals with its biocatalytic production from tyrosol and lactose using Aspergillus oryzae β-galactosidase in immobilized form. Six commercial carriers were examined to find the optimal biocatalyst. Besides standard biocatalyst performance characteristics, adsorption of the hydrophobic substrate on immobilization carrier matrices was also investigated. The adsorption of tyrosol was significant, but it did not have adverse effects on TG production. On the contrary, TG yield was improved for some biocatalysts. A biocatalyst prepared by covalent binding of β-galactosidase on an epoxy-activated carrier was used for detailed investigation of the effect of reaction conditions on glycoside production. Temperature had a surprisingly weak effect on the overall process rate. A lactose concentration of 0.83 M was found to be optimal to enhance TG formation. The impact of tyrosol concentration was rather complex. This substrate caused inhibition of all reactions. Its concentration had a strong effect on the hydrolysis of lactose and all products. Higher tyrosol concentrations, 30–40 g/L, were favorable as pseudo-equilibrium concentrations of TG and galactooligosaccharide were reached. Repeated batch results revealed excellent operational stability of the biocatalyst. [ABSTRACT FROM AUTHOR]

Parametric sensitivity analysis is a critical component in the study of mathematical models of physical systems. Due to its simplicity, finite difference methods are used extensively for this analysis in the study of stochastically modeled reaction networks. Different coupling methods have been proposed to build finite difference estimators, with the "split coupling," also termed the "stacked coupling," yielding the lowest variance in the vast majority of cases. Analytical results related to this coupling are sparse and include an analysis of the variance of the coupled processes under the assumption of globally Lipschitz intensity functions [SIAM J. Numer. Anal., 50 (2012), pp. 2237-2258]. Because of the global Lipschitz assumption utilized in [SIAM J. Numer. Anal., 50 (2012), pp. 2237-2258], the main result there is only applicable to a small percentage of the models found in the literature, and it was conjectured that similar results should hold for a much wider class of models. In this paper we demonstrate this conjecture to be true by proving the variance of the coupled processes scales in the desired manner for a large class of non-Lipschitz models. We further extend the analysis to allow for time dependence in the parameters. In particular, binary systems with or without time-dependent rate parameters, a class of models that accounts for the vast majority of systems considered in the literature, satisfy the assumptions of our theory. [ABSTRACT FROM AUTHOR]

We show that weakly reversible mass-action systems can have a continuum of positive steady states, coming from the zeroes of a multivariate polynomial. Moreover, the same is true of systems whose underlying reaction network is reversible and has a single connected component. In our construction, we relate operations on the reaction network to the multivariate polynomial occurring as a common factor in the system of differential equations. [ABSTRACT FROM AUTHOR]

Ethanol Guerbet condensation is an environmentally friendly process for preparing biofuel such as n‐butanol and alcohols with more than 4 carbon atoms. In this work, a multifunctional catalyst Ni/TiO2 was prepared by an excess impregnation method and its catalytic performance for ethanol Guerbet condensation was evaluated. The selectivity of C4‐C8 alcohols reached up to almost 70% (41.4% of n‐butanol) at nearly half conversion of ethanol at 210 °C and 10 h. Based on GC‐MS analysis results, the products in ethanol Guerbet condensation were identified and a reaction network was established. The presence of acetaldehyde and 2‐crotonaldehyde in the reaction products verified that Ni/TiO2‐catalyzed ethanol condensation followed the traditional dehydrogenation‐condensation‐hydrogenation reaction mechanism. [ABSTRACT FROM AUTHOR]

In systems and synthetic biology, much research has focused on the behavior and design of single pathways, while, more recently, experimental efforts have focused on how cross-talk (coupling two or more pathways) or inhibiting molecular function (isolating one part of the pathway) affects systems-level behavior. However, the theory for tackling these larger systems in general has lagged behind. Here, we analyze how joining networks (e.g., cross-talk) or decomposing networks (e.g., inhibition or knock-outs) affects three properties that reaction networks may possess—identifiability (recoverability of parameter values from data), steady-state invariants (relationships among species concentrations at steady state, used in model selection), and multistationarity (capacity for multiple steady states, which correspond to multiple cell decisions). Specifically, we prove results that clarify, for a network obtained by joining two smaller networks, how properties of the smaller networks can be inferred from or can imply similar properties of the original network. Our proofs use techniques from computational algebraic geometry, including elimination theory and differential algebra. [ABSTRACT FROM AUTHOR]

Optimization and execution of chemical reactions are to a large extend based on experience and chemical intuition of a chemist. The chemical intuition is rooted in the phenomenological Le Chatelier's principle that teaches us how to shift equilibrium by manipulating the reaction conditions. To access the underlying thermodynamic parameters and their condition‐dependencies from the first principles is a challenge. Here, we present a theoretical approach to model non‐standard free energies for a complex catalytic CO2 hydrogenation system under operando conditions and identify the condition spaces where catalyst deactivation can potentially be suppressed. Investigation of the non‐standard reaction free energy dependencies allows rationalizing the experimentally observed activity patterns and provides a practical approach to optimization of the reaction paths in complex multicomponent reactive catalytic systems. [ABSTRACT FROM AUTHOR]

In this study, 27 groups of hydrogenation experiments were carried out in a single-tube fixed-bed reactor using 9 phenolic compounds extracted from coal tar (fraction before 240 °C) as raw materials. Based on the experimental results, a set of molecular reaction kinetics model which involve 21 compounds and 33 chemical reactions was established. In this paper, the Runge–Kutta method was used to solve the dynamic equations, and the BFGS algorithm (a quasi-Newton optimization algorithm) is used to optimize the parameters of the dynamic model. The whole calculation process was completed on MATLAB software. The experimental results show that the maximum error of the model for predicting phenolic, unsaturated hydrocarbon and saturated hydrocarbon content in products is less than 5%, while the maximum error for predicting single substance is less than 10%. It could be calculated that the optimum temperature for hydrodeoxygenation of phenolic compounds is 633 K, which aims to retain aromatic hydrocarbons. [ABSTRACT FROM AUTHOR]

For given integers k, n, r we aim at families of k sub-cliques called blocks, of a clique with n vertices, such that every block has r vertices, and the blocks together cover a maximum number of edges. We demonstrate a combinatorial optimization method that generates such optimal partial clique edge coverings. It takes certain packages of columns (corresponding to vertices) in the incidence matrix of the blocks, considers the number of uncovered edges as an energy term that has to be minimized by transforming these packages. As a proof of concept we can completely solve the above maximization problem in the case of k ≤ 4 blocks and obtain optimal coverings for all integers n and r with r / n ≥ 5 / 9 . This generalizes known results for total coverings to partial coverings. The method as such is not restricted to k ≤ 4 blocks, but a challenge for further research (also on total coverings) is to limit the case distinctions when more blocks are involved. [ABSTRACT FROM AUTHOR]

Many dynamical systems arising in biology and other areas exhibit multistationarity (two or more positive steady states with the same conserved quantities). Although deciding multistationarity for a polynomial dynamical system is an effective question in real algebraic geometry, it is in general difficult to determine whether a given network can give rise to a multistationary system, and if so, to identify witnesses to multistationarity, that is, specific parameter values for which the system exhibits multiple steady states. Here we investigate both problems. First, we build on work of Conradi, Feliu, Mincheva, and Wiuf, who showed that for certain reaction networks whose steady states admit a positive parametrization, multistationarity is characterized by whether a certain "critical function" changes sign. Here, we allow for more general parametrizations, which make it much easier to determine the existence of a sign change. This is particularly simple when the steady-state equations are linearly equivalent to binomials; we give necessary conditions for this to happen, which hold for many networks studied in the literature. We also give a sufficient condition for multistationarity of networks whose steady-state equations can be replaced by equivalent triangular-form equations. Finally, we present methods for finding witnesses to multistationarity, which we show work well for certain structured reaction networks, including those common to biological signaling pathways. Our work relies on results from degree theory, on the existence of explicit rational parametrizations of the steady states, and on the specialization of Gröbner bases. [ABSTRACT FROM AUTHOR]

We present an elaborate framework for formally modelling pathways in chemical reaction networks on a mechanistic level. Networks are modelled mathematically as directed multi-hypergraphs, with vertices corresponding to molecules and hyperedges to reactions. Pathways are modelled as integer hyperflows and we expand the network model by detailed routing constraints. In contrast to the more traditional approaches like Flux Balance Analysis or Elementary Mode analysis we insist on integer-valued flows. While this choice makes it necessary to solve possibly hard integer linear programs, it has the advantage that more detailed mechanistic questions can be formulated. It is thus possible to query networks for general transformation motifs, and to automatically enumerate optimal and near-optimal pathways. Similarities and differences between our work and traditional approaches in metabolic network analysis are discussed in detail. To demonstrate the applicability of the mathematical framework to real-life problems we first explore the design space of possible non-oxidative glycolysis pathways and show that recent manually designed pathways can be further optimized. We then use a model of sugar chemistry to investigate pathways in the autocatalytic formose process. A graph transformation-based approach is used to automatically generate the reaction networks of interest. [ABSTRACT FROM AUTHOR]

We consider stochastically modeled reaction networks and prove that if a constant solution to the Kolmogorov forward equation decays fast enough relatively to the transition rates, then the model is non-explosive. In particular, complex-balanced reaction networks are non-explosive. [ABSTRACT FROM AUTHOR]

A new software, called tsscds2018, has been developed to discover reaction mechanisms and solve the kinetics in a fully automated fashion. The program employs algorithms based on Graph Theory to find transition state (TS) geometries from accelerated semiempirical dynamics simulations carried out with MOPAC2016. Then, the TSs are connected to the corresponding minima and the reaction network is obtained. Kinetic data like populations vs time or the abundancies of each product can also be obtained with our program thanks to a Kinetic Monte Carlo routine. Highly accurate ab initio potential energy diagrams and kinetics can also be obtained using an interface with Gaussian09. The source code is available on the following site: http://forge.cesga.es/wiki/g/tsscds/HomePage © 2018 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Abstract: A mechanistic model for the ultraviolet degradation of methane and ethane in waste gas was developed with the focus on reaction network development and optimization. The research serves a dual purpose of removing natural gas condensate emissions, and converting condensates to added‐value products. A comprehensive reaction network including all possible reactions was developed, and kinetic constants were taken from the literature or estimated based on analogues. Overall, 162 reactions were included for the most complete case. Next, the model was screened for reactions that did not affect the simulation results. As complexity increases, it was shown that the model devotes an increasing fraction of time calculating reactions that are negligible in the overall process. Based on the simulation results it is expected that the model can be extended to higher alkanes with a reasonable run‐time in addition to keeping precise simulation results. The model predicts that high ethane conversion is possible while maintaining low methane conversion, and it is expected that this effect will be even more pronounced in the presence of higher alkanes. Overall, the projected model can be used to establish the feasibility of converting natural gas condensates to value‐added products without degrading its main content, methane; provided that oxygen and water vapour are available for the oxidation. [ABSTRACT FROM AUTHOR]

We study chemical reaction networks with discrete state spaces and present sufficient conditions on the structure of the network that guarantee the system exhibits an extinction event. The conditions we derive involve creating a modified chemical reaction network called a domination-expanded reaction network and then checking properties of this network. Unlike previous results, our analysis allows algorithmic implementation via systems of equalities and inequalities and suggests sequences of reactions which may lead to extinction events. We apply the results to several networks including an EnvZ-OmpR signaling pathway in Escherichia coli. [ABSTRACT FROM AUTHOR]

The analysis and simulation of complex interacting biochemical reaction pathways in cells is important in all of systems biology and medicine. Yet, the dynamics of even a modest number of noisy or stochastic coupled biochemical reactions is extremely time consuming to simulate. In large part, this is because of the expensive cost of random number and Poisson process generation and the presence of stiff, coupled, nonlinear differential equations. Here, we demonstrate that we can amplify inherent thermal noise in chips to emulate randomness physically, thus alleviating these costs significantly. Concurrently, molecular flux in thermodynamic biochemical reactions maps to thermodynamic electronic current in a transistor such that stiff nonlinear biochemical differential equations are emulated exactly in compact, digitally programmable, highly parallel analog “cytomorphic” transistor circuits. For even small-scale systems involving just 80 stochastic reactions, our 0.35-μm BiCMOS chips yield a 311× speedup in the simulation time of Gillespie's stochastic algorithm over COPASI, a fast biochemical-reaction software simulator that is widely used in computational biology; they yield a 15 500× speedup over equivalent MATLAB stochastic simulations. The chip emulation results are consistent with these software simulations over a large range of signal-to-noise ratios. Most importantly, our physical emulation of Poisson chemical dynamics does not involve any inherently sequential processes and updates such that, unlike prior exact simulation approaches, they are parallelizable, asynchronous, and enable even more speedup for larger-size networks. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce a reaction graph-based analysis method to study the mathematical structure and dynamical behavior of thin-film deposition reaction network models. Using this approach, we identify reaction network invariants and determine the chemical significance of these conserved modes for thin-film deposition reaction mechanisms. Furthermore, the species-reaction graphs can be used to distinguish “proper” from problematic reaction networks during the initial stages of reaction kinetic modeling studies. Results are presented in the context of a titania deposition process where the transition from atomic layer deposition to chemical vapor deposition growth modes is observed. [ABSTRACT FROM AUTHOR]

The oxidation of propane has been studied over silica-supported vanadium oxide and polycrystalline, bulk MoVTeNb oxide with M1 structure. Temperature-programmed reaction experiments were performed, and the reactivity of propane molecules labeled with deuterium and 13C, respectively, was analyzed under steady-state conditions. The measurement of kinetic isotope effects reveals fundamental differences in the activation of propane over the two catalysts. The reaction network of consecutive and parallel reactions of the formed propylene is comparable. However, oxygen insertion into the CHO group of acrolein under formation of acrylic acid is faster over M1 than oxidation at the CH2 group and decarbonylation to acetaldehyde. In contrast, the latter process is preferred over silica-supported vanadium oxide resulting in lower selectivity to unsaturated oxygenates. [ABSTRACT FROM AUTHOR]

Biomass conversion to chemicals and fuels through fast pyrolysis shows great potential but requires a more fundamental approach for its deployment. To this end, molecular-based kinetic modeling is starting to play a central role in the prediction of the molecular composition of bio-oil. A molecular-level representation of biomass provides the start point for the generation of detailed pyrolysis reaction networks for both the condensed and the gas phases. Significant progress has been made for cellulose, glucose-based carbohydrates, and lignin, together with the incorporation of the catalytic effects of minerals. Ab initio techniques are widely used to discriminate between reaction mechanisms and to calculate kinetic parameters. Automatic kinetic model generation is expected to play an even more important role in fast pyrolysis as it does already today. Experimental techniques enabled to obtain intrinsic kinetics and to decouple the timescales between reaction kinetics and analytic techniques. This greatly benefits the improvement of detailed kinetic models. The prospects for achieving a first-principles based kinetic model of biomass fast pyrolysis are promising. However, significant work is still needed to couple condensed- and gas-phase reaction networks. [ABSTRACT FROM AUTHOR]

The reaction network of the ethene-to-propene (ETP) reaction over Ni/AlMCM-41 catalysts was studied. This reaction consists of the dimerization of ethene, the isomerization of 1-butene, and the metathesis of ethene and 2 -butene to propene. This work focused on the latter. ETP experiments followed by in situ diffuse reflectance infrared Fourier transform spectroscopy were carried out. Metathesis activities were evaluated by the isomerization of butenes, the metathesis of ethene and 2-butene, and the retro-metathesis of propene. Metathesis activities of Ni/AlMCM-41 catalysts were not observed. Thus, a conjunct polymerization of ethene to propene is proposed. [ABSTRACT FROM AUTHOR]

Reaction networks can be simplified by eliminating linear intermediate species in partial steady states. In this paper, we study the question whether this rewrite procedure is confluent, so that for any given reaction network with kinetic constraints, a unique normal form will be obtained independently of the elimination order. We first show that confluence fails for the elimination of intermediates even without kinetics, if "dependent reactions" introduced by the simplification are not removed. This leads us to revising the simplification algorithm into a variant of the double description method for computing elementary modes, so that it keeps track of kinetic information. Folklore results on elementary modes imply the confluence of the revised simplification algorithm with respect to the network structure, i.e., the structure of fully simplified networks is unique. We show, however, that the kinetic rates assigned to the reactions may not be unique, and provide a biological example where two different simplified networks can be obtained. Finally, we give a criterion on the structure of the initial network that is sufficient to guarantee the confluence of both the structure and the kinetic rates. [ABSTRACT FROM AUTHOR]

We study two specific measures of quality of chemical reaction networks, Precision and Sensitivity. The two measures arise in the study of sensory adaptation, in which the reaction network is viewed as an input-output system. Given a step change in input, Sensitivity is a measure of the magnitude of the response, while Precision is a measure of the degree to which the system returns to its original output for large time. High values of both are necessary for high-quality adaptation. We focus on reaction networks without dissipati on, which we interpret as detailedbalance, mass-action networks. We give various upper and lower bounds on the optimal values of Sensitivity and Precision, characterized in terms of the stoich iometry, by using a combination of ideas from matroid theory and differential-equation theory. Among other results, we show that this class of nondissipative systems contains networks with arbitrarily high values of both Sensitivity and Precision. This good performance does come at a cost, however; since certain ratios of concentrations need to be large, the network has to contain many species and reactions, or the network should show strongly different time scales. [ABSTRACT FROM AUTHOR]

Catalytic hydroprocessing of 4-methylanisole as a representative of lignin-derived bio-oils was catalyzed by a commercial sulphided CoMo/γ-Al2O3 catalyst in a fixed-bed flow reactor at various space velocities, temperatures, pressures, and feed compositions. An approximate reaction network is presented that accounts for the major products, and approximate kinetics are also presented. The kinetically significant reactions are 4-methylanisole conversion to (a) 4-methylphenol via hydrogenolysis, (b) toluene and benzene via hydrodeoxygenation, (c) cyclohexanone and methylcyclohexanone via hydrogenation, and (d) methylphenol derivatives via alkylation and transalkylation. The formation of toluene and benzene along with water and methanol from 4-methylanisole is inferred to result from direct scission of the Caromatic-O bond. Cleavage of the Cmethyl-O bond is faster than cleavage of the Caromatic-O bond. The main pathway to toluene formation is the hydrogenolysis of the Caromatic-O bond of the intermediate 4-methylphenol. [ABSTRACT FROM AUTHOR]

In this paper we review various information-theoretic characterizations of the approach to equilibrium in biological systems. The replicator equation, evolutionary game theory, Markov processes and chemical reaction networks all describe the dynamics of a population or probability distribution. Under suitable assumptions, the distribution will approach an equilibrium with the passage of time. Relative entropy--that is, the Kullback-Leibler divergence, or various generalizations of this--provides a quantitative measure of how far from equilibrium the system is. We explain various theorems that give conditions under which relative entropy is nonincreasing. In biochemical applications these results can be seen as versions of the Second Law of Thermodynamics, stating that free energy can never increase with the passage of time. In ecological applications, they make precise the notion that a population gains information from its environment as it approaches equilibrium. [ABSTRACT FROM AUTHOR]

The paper proposes new computational methods of computing confidence bounds for the least-squares estimates (LSEs) of rate constants in mass action biochemical reaction network and stochastic epidemic models. Such LSEs are obtained by fitting the set of deterministic ordinary differential equations (ODEs), corresponding to the large-volume limit of a reaction network, to network's partially observed trajectory treated as a continuous-time, pure jump Markov process. In the large-volume limit the LSEs are asymptotically Gaussian, but their limiting covariance structure is complicated since it is described by a set of nonlinear ODEs which are often ill-conditioned and numerically unstable. The current paper considers two bootstrap Monte-Carlo procedures, based on the diffusion and linear noise approximations for pure jump processes, which allow one to avoid solving the limiting covariance ODEs. The results are illustrated with both in-silico and real data examples from the LINE 1 gene retrotranscription model and compared with those obtained using other methods. [ABSTRACT FROM PUBLISHER]