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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]

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]

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]

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.

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 Togashi Kaneko model (TK model) is a simple stochastic reaction network that displays discreteness-induced transitions between meta-stable patterns. Here we study a constrained Langevin approximation (CLA) of this model. This CLA, derived under the classical scaling, is an obliquely reflected diffusion process on the positive orthant and hence respects the constraint that chemical concentrations are never negative. We show that the CLA is a Feller process, is positive Harris recurrent and converges exponentially fast to the unique stationary distribution. We also characterize the stationary distribution and show that it has finite moments. In addition, we simulate both the TK model and its CLA in various dimensions. For example, we describe how the TK model switches between meta-stable patterns in dimension six. Our simulations suggest that, when the volume of the vessel in which all of the reactions that take place is large, the CLA is a good approximation of the TK model in terms of both the stationary distribution and the transition times between patterns.

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]

A multistationarity region is the part of a reaction network's parameter space that gives rise to multiple steady states. Mathematically, this region consists of the positive parameters for which a parametrized family of polynomial equations admits two or more positive roots. Much recent work has focused on analyzing multistationarity regions of biologically significant reaction networks and determining whether such regions are connected; indeed, a better understanding of the topology and geometry of such regions may help elucidate how robust multistationarity is to perturbations. Here we focus on the multistationarity regions of small networks, those with few species and few reactions. For two families of such networks – those with one species and up to three reactions, and those with two species and up to two reactions – we prove that the resulting multistationarity regions are connected. We also give an example of a network with one species and six reactions for which the multistationarity region is disconnected. Our proofs rely on the formula for the discriminant of a trinomial, a classification of small multistationary networks, and a recent result of Feliu and Telek that partially generalizes Descartes' rule of signs. [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]

Focusing on the effects of active centers and supports of polycyclic aromatic hydrocarbons hydrogenation catalysts on saturated hydrogenation of polycyclic aromatic hydrocarbons, and introduces some typical saturated hydrogenation networks of polycyclic aromatic hydrocarbons・ The development of polycyclic aromatic hydrocarbon hydrogenation catalyst is prospected・ It is pointed out that the key to improve the performance of polycyclic aromatic hydrocarbon hydrogenation catalyst is to introduce a variety of supported components, improve the particle dispersion and stability of supported components, and appropriate pore size and structure. [ABSTRACT FROM AUTHOR]

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]

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]

[Display omitted] • Ethylbenzene is synthesized by alkylation of benzene using CO 2. • A Single-bed catalyst system for forming ethylbenzene is constructed. • Effect of Brønsted Acid Density and Intragranular Diffusion of HZSM-5 on Product Distribution. • Reaction networks were extensively explored using GC–MS and various model reactions. The selective synthesis of specific value-added aromatic hydrocarbons through CO 2 hydrogenation holds significant strategic importance in mitigating energy and climate issues. However, the process of forming ethylated side chains on benzene rings is challenging, and the methods reported are often limited by multi-bed systems. Here, we show the first CO 2 hydrogenation in tandem coupling with benzene alkylation to synthesize ethylbenzene over a single-bed system containing ZnFeO x and nano ZSM-5 catalysts. The results indicated that the bifunctional catalyst composed of ZnFeO x with a Zn/Fe ratio of 0.5 and nano-HZSM-5 exhibits excellent catalytic performance under optimized conditions. The benzene conversion reaches 28.0 %, ethylbenzene selectivity is 61.3 % and the conversion of CO 2 is remarkably high, achieving 45.0 %. This single-bed system significantly promotes the in-situ utilization of ethylation intermediates. The introduction of zinc promoted the formation of ZnFe 2 O 4 spinel, which increased the number of active sites due to its superior dispersibility and reducibility. Nano-HZSM-5 demonstrated outstanding ethylbenzene selectivity and catalytic stability owing to its unique shape selectivity, moderate acidity, and superior diffusion properties. This study further explores the reaction network and mechanism through GC–MS analysis and various model reactions, elucidating the formation pathways of primary products in detail. This research provides a new strategy for the controllable synthesis of ethylbenzene using CO 2 as a C 1 source in a single-bed system. [ABSTRACT FROM AUTHOR]

The concept of "reaction network" represents a system that is constructed from reactions between different organic units basing on logical transformation relationships. This network is refined through multiple parallel cascade reaction sequences, showcasing attributes such as "self-direction, self-sorting, convergence and normalization". The ability of synthesizing tissues within molecular systems is a key aspect that could serve as a valuable tool for the rational design of new reactions. In this paper, we summarized our research work on self-organized reaction network in the past two decades from three aspects: self-sorting convergent integration reaction network, self-labor convergent integration reaction network and complex integration reaction network. [Display omitted] [ABSTRACT FROM AUTHOR]

The interaction between genipin and a model protein bovine serum albumin (BSA), with and without the addition of acetic acid, has been studied experimentally and by modelling. The number of amino groups available to react was determined to be 5.6 % of the total number of amino acid building blocks on BSA. Fluorescence intensity was used to record the progress of the reaction over the 24 h, while the modelling study focused on capturing the kinetic profiles of the reaction. The experiments revealed a slow start to the BSA and genipin interaction, that subsequently accelerated in an S-shaped curve which the modelling study linked with the existence of the feedback cycle for both reactive amino groups and genipin. At BSA concentrations ≥30 mg/mL the reaction was accelerated in the presence of acid, while below 30 mg/mL the acidified conditions delayed the onset of the reaction. Contrary to the reaction mechanisms previously proposed, a degree of breakdown of the fluorescent links in the products formed was denoted both experimentally and in a modelling study. This indicated the reversibility of the processes forming fluorescent product/s and suggested feasibility of the successful release of the protein following prospective encapsulation within the genipin-crosslinked hydrogel structure. • Interaction of bovine serum albumin (BSA) and genipin was followed using Fluorescence Intensity (FI) measurements; • The number of reactive amino groups was measured to be 5.6 % of the total number of amino acid building blocks in BSA; • The experiments revealed a slow start of the BSA and genipin interaction, that subsequently accelerated in an S-shaped curve; • In the presence of acid at ≥30 mg/mL BSA the reaction was accelerated, while below 30 mg/mL BSA, it was delayed; • A degree of breakdown of the fluorescent links in the products was denoted both experimentally and in a modelling study. [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 review the state of the art on approaches for the determination of reaction networks and the real-time monitoring of reactions in complex chemical systems consisting of multiple reactive components using automated and data-driven methods. This complexity of the system results in uncertainty about both the dominant species and reactions in the system. Automated approaches to reaction network or pathway determination include rule-based or algorithmically extracted methods, quantum mechanical simulations, and machine learning approaches. We also identify the effect of explicit pathway determination on the approach for reaction monitoring. Furthermore, we compare and contrast the automated and data-driven approaches for reaction pathway determination with some heuristics commonly used to develop reaction mechanisms in complex chemistries.

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.

Metal ions are liable to form metal-dissolved organic matter [dissolved organic matter (DOM)] complexes, changing the chemistry and chlorine reactivity of DOM. Herein, the impacts of iron and zinc ions (Fe 3+ and Zn 2+ ) on the formation of unknown chlorinated disinfection byproducts (Cl-DBPs) were investigated in a chlorination system. Fe 3+ preferentially complexed with hydroxyl and carboxyl functional groups, while Zn 2+ favored the amine functional groups in DOM. As a consequence, electron-rich reaction centers were created by the C-O-metal bonding bridge, which facilitated the electrophilic attack of α-C in metal-DOM complexes. Size-reactivity continuum networks were constructed in the chlorination system, revealing that highly aromatic small molecules were generated during the oxidation and decarbonization of metal-DOM complexes. Molecular transformation related to C-R (R represents complex sites) loss was promoted via metal complexation, including decarboxylation and deamination. Consequently, complexation with Fe 3+ and Zn 2+ promoted hydroxylation by the C-O-metal bonding bridge, thereby increasing the abundances of unknown polychlorinated Cl-DBPs by 9.6 and 14.2%, respectively. The study provides new insights into the regulation of DOM chemistry and chlorine reactivity by metal ions in chlorination systems, emphasizing that metals increase the potential health risks of drinking water and more scientific control standards for metals are needed.

[Display omitted] • Hydrothermal carbonization converted up to 80% of problematic paunch waste. • The mechanisms of hydrothermal treatment of paunch waste was explained. • The kinetic study revealed the reactiveness of paunch waste in hot compressed water. • Formation of aqueous phase is much faster than that of bio-oil. • Holding time can substantially affect the commercial viability of the process. Hydrothermal carbonization of paunch waste, the main wet waste generated at abattoirs, was investigated in batch mode. A mass loss of 58% was achieved at 240 °C in a flash experiment, whereas prolonging the reaction to 4 h increased it to 79%, indicating the ability of a hydrothermal medium for managing this wet waste. XRD analysis suggested that the amorphous portion of paunch waste was readily hydrolysed, whereas crystalline cellulose I was retained. Longer holding time partially destroyed the formed porous structure and halved the BET surface area from 68.1 to 37 m2 g−1. Aromatic, cyclic, and phenolic compounds were found in light bio-oil, while heavy bio-oil contained long-chain fatty acids derivatives. A reaction network was suggested containing 12 reaction pathways during the process, and lumped kinetic modelling was performed reasonably accurately. The techno-economic analysis also revealed that with a solids content of 3 wt.%, only processing time as short as 5 min can promise a positive net present value of $8.3 million, while longer residence times led to negative values. [ABSTRACT FROM AUTHOR]

[Display omitted] • Eight networks of varying complexity were used to describe the hydrodeoxygenation of benzofuran over PdCoP/KUSY. • Mathematical modeling found that the networks that considered adsorbed species best fit the kinetic data. • The Delplot method of plotting selectivity to conversion ratios was applied to adsorbed species. • The Delplot method of plotting selectivity to conversion ratios was not generally applicable. • The best analysis involves plotting selectivity versus contact time, with the contact time defined on the basis of sites. The Delplot method provides a means of analyzing conversion and selectivity data to derive a reaction sequence and has been applied so far to gas-phase or liquid-phase species. This study analyses the applicability of the method for catalytic reactions and considers for the first time adsorbed intermediates. The method is applied to a contact time study of the hydrodeoxygenation (HDO) of benzofuran at 0.5 MPa and 350 °C over a catalyst consisting of bimetallic CoPd phosphide supported on a potassium ion-exchanged ultra-stable Y (KUSY) zeolite. Both simple and detailed reaction networks were derived. The simple networks considered only gas-phase species and were modeled by a first-order sequence of steps, whereas the detailed network took into account adsorbed intermediates and was simulated using a rake mechanism. The networks were compared using F-statistics, which accounted for the differences in the number of fitting parameters. The detailed network gave a better fit to the experimental data because it represented a more realistic description of the transformation. A suggested sequence from the Delplot method was consistent with the simple network but not with the detailed network. The lack of applicability of the Delplot analysis to the network with adsorbates was linked to overly large equilibrium constants, a determination supported by Delplot fitting for a model sequence. This study indicated the inapplicability of the Delplot method in determining reaction sequences that involve adsorbed species with large equilibrium constants for formation. [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]

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]

Identification of the underlying cause of carbon loss in fatty acid hydrodeoxygenation (HDO) on the acidic catalyst is very important to understand the reaction mechanism and design high efficiency catalyst for biomass conversion. Herein, HDO reactions of palmitic acid catalyzed by Ni supported on mesoporous Beta (HBeta-M) zeolites with different acidities were investigated. It was found that a significant carbon loss (47.5%) occurred during the entire reaction process on Ni/HBeta-M catalyst with high acid density. This is because the hexadecyl ether intermediate was formed and trapped in the porous structure of the catalyst and interacted with strong acidic sites. On the Ni/HBeta-M-0.5 catalyst with medium acid density, carbon loss occurred in the initial reaction stage because hexadecanol was trapped in the porous catalyst. Investigations further demonstrated that the hexadecyl ether intermediate can also be converted to hexadecanol and hexadecane via hydrogenolysis on Brønsted acid and Ni sites. [Display omitted] • Carbon loss mainly caused by the hexadecyl ether trapped in the Ni/HBeta-M catalyst. • Carbon loss mainly caused by the hexadecanol trapped in the Ni/HBeta-M-0.5 catalyst. • The catalyst acidities strongly affect the transformation of hexadecanol. • The formation and transformation process of hexadecyl ether were clarified. [ABSTRACT FROM AUTHOR]

Mass-action kinetics and its generalizations appear in mathematical models of (bio)chemical reaction networks, population dynamics, and epidemiology. The dynamical systems arising from directed graphs are generally non-linear and difficult to analyze. One approach to studying them is to find conditions on the network which either imply or preclude certain dynamical properties. For example, a vertex-balanced steady state for a generalized mass-action system is a state where the net flux through every vertex of the graph is zero. In particular, such steady states admit a monomial parametrization. The problem of existence and uniqueness of vertex-balanced steady states can be reformulated in two different ways, one of which is related to Birch's theorem in statistics, and the other one to the bijectivity of generalized polynomial maps, similar to maps appearing in geometric modelling. We present a generalization of Birch's theorem, by providing a sufficient condition for the existence and uniqueness of vertex-balanced steady states.

This paper presents an algebraic framework to study sign-sensitivities for reaction networks modeled by means of systems of ordinary differential equations. Specifically, we study the sign of the derivative of the concentrations of the species in the network at steady state with respect to a small perturbation on the parameter vector. We provide a closed formula for the derivatives that accommodates common perturbations, and illustrate its form with numerous examples. We argue that, mathematically, the study of the response to the system with respect to changes in total amounts is not well posed, and that one should rather consider perturbations with respect to the initial conditions. We find a sign-based criterion to determine, without computing the sensitivities, whether the sign depends on the steady state and parameters of the system. This is based on earlier results of so-called injective networks. Finally, we address systems with multiple steady states and the restriction to stable steady states.