A collision theory-based derivation of semiempirical equations for modeling dispersive kinetics and their application to a mixed-phase crystal decomposition

In recent works, the author has shown the utility of new, semiempirical kinetic model equations for treating dispersive chemical processes ranging from slow (minute/hour time scale) solid-state phase transformations to ultrafast (femtosecond) reactions in the gas phase. These two fundamental models (one for homogeneous/deceleratory sigmoidal conversion kinetics and the other for heterogeneous/acceleratory sigmoidal kinetics; isothermal conditions), based on the assumption of a "Maxwell-Boltzmann-like" distribution of molecular activation energies, provide a novel, quantum-based interpretation of the kinetics. As an extension to previous work, it is shown here that the derivation of these dispersive kinetic equations is supported by classical collision theory (i.e., for gas-phase applications). Furthermore, the successful application of the approach to the kinetic modeling of the solid-state decomposition of a binary system, CO2.C2H2, is demonstrated. Finally, the models derived appear to explain some of the (solid-state) kinetic data collected using isoconversional techniques such as those often reported in the thermal analysis literature.     

Experimental and computational studies of the phenyl radical reaction with propyne.

The kinetics for the gas-phase reaction of phenyl radical with propyne has been measured by cavity ring-down spectrometry (CRDS), and the mechanism and initial product branching have been elucidated with the help of quantum chemical calculations. Absolute rate constants measured by the CRDS technique can be expressed by the following Arrhenius equation: (k/cm(3) mol(-1) s(-1)): k(propyne)(T=301-428 K)=(3.68+/-0.92) x 10(11)exp[-(1685+/-80)/T]. The experiment is unable to distinguish between the possible reactive channels, but theory indicates that phenyl radicals preferably add to the unsaturated terminal carbon atom in propyne under our experimental conditions. Theoretical kinetic calculations, employing high-level G2M(RCC, RMP2) and G3 energetic and IRCMax(RCCSD(T)//B3LYP-DFT) molecular parameters, reproduce the total experimental rate constants within a factor of three. Calculated total and branching rate constants are provided for high-T kinetic modeling. Addition reactions of phenyl to C3H4 are estimated to be less important molecular-growth pathways in high-T conditions (T>1000 K) in comparison to the C6H5 + C2H2 reaction.     

Polynomial time algorithms to determine weakly reversible realizations of chemical reaction networks

Weak reversibility is a crucial structural property of chemical reaction networks (CRNs) with mass action kinetics, because it has major implications related to the existence, uniqueness and stability of equilibrium points and to the boundedness of solutions. In this paper, we present two new algorithms to find dynamically equivalent weakly reversible realizations of a given CRN. They are based on linear programming and thus have polynomial time-complexity. Hence, these algorithms can deal with large-scale biochemical reaction networks, too. Furthermore, one of the methods is able to deal with linearly conjugate networks, too.     

Combining artificial neural networks and experimental design to prediction of kinetic rate constants

A “soft-modelling” computational approach of artificial neural networks (ANNs) combined with experimental design (ED) has been applied successfully in Chemical Kinetics for the prediction of kinetic rate constants. The system studied comprises two consecutive first-order reactions and the kinetic data were computed determining the values of both rate constants. The kinetic curves were distributed according to an ED, and the central star composite experimental design (CSCED) was chosen as the most appropriate. Computational treatments were performed on synthetic data endowed with noise, after which they were applied to the data measured in an experimental reaction between carbonyl cyanide 3-clorophenylhydrazone with 2-mercaptoethanol, computing the experimental kinetic data of absorbance acquired at 3 wavelengths. The combined ANN and ED approach applied in chemical kinetics proved to be robust and of general applicability and has the advantage of being a “soft-modelling” method such that it was not necessary to solve the system of ordinary differential equations to determine the explicit mathematical function between the data and the kinetic rate constants. Additionally, upon using the CSCED experimental design, it was possible to substantially reduce the number of experiments.     

Mutual sensitization of the oxidation of nitric oxide and a natural gas blend in a JSR at elevated pressure: experimental and detailed kinetic modeling study

The mutual sensitization of the oxidation of NO and a natural gas blend (methane-ethane 10:1) was studied experimentally in a fused silica jet-stirred reactor operating at 10 atm, over the temperature range 800-1160 K, from fuel-lean to fuel-rich conditions. Sonic quartz probe sampling followed by on-line FTIR analyses and off-line GC-TCD/FID analyses were used to measure the concentration profiles of the reactants, the stable intermediates, and the final products. A detailed chemical kinetic modeling of the present experiments was performed yielding an overall good agreement between the present data and this modeling. According to the proposed kinetic scheme, the mutual sensitization of the oxidation of this natural gas blend and NO proceeds through the NO to NO2 conversion by HO2, CH3O2, and C2H5O2. The detailed kinetic modeling showed that the conversion of NO to NO2 by CH3O2 and C2H5O2 is more important at low temperatures (ca. 820 K) than at higher temperatures where the reaction of NO with HO2 controls the NO to NO2 conversion. The production of OH resulting from the oxidation of NO by HO2, and the production of alkoxy radicals via RO2 + NO reactions promotes the oxidation of the fuel. A simplified reaction scheme was delineated: NO + HO2 --> NO2 + OH followed by OH + CH4 --> CH3 + H2O and OH + C2H6 --> C2H5 + H2O. At low-temperature, the reaction also proceeds via CH3 + O2 (+ M) --> CH3O2 (+ M); CH3O2 + NO --> CH3O + NO2 and C2H5 + O2 --> C2H5O2; C2H5O2 + NO --> C2H5O + NO2. At higher temperature, methoxy radicals are produced via the following mechanism: CH3 + NO2 --> CH3O + NO. The further reactions CH3O --> CH2O + H; CH2O + OH --> HCO + H2O; HCO + O2 --> HO2 + CO; and H + O2 + M --> HO2 + M complete the sequence. The proposed model indicates that the well-recognized difference of reactivity between methane and a natural gas blend is significantly reduced by addition of NO. The kinetic analyses indicate that in the NO-seeded conditions, the main production of OH proceeds via the same route, NO + HO2 --> NO2 + OH. Therefore, a significant reduction of the impact of the fuel composition on the kinetics of oxidation occurs.     

煤气化动力学模型研究

煤的气化动力学是煤气化技术研究开发和模型化的基础 ,对实现煤的高效利用具有重要指导意义。目前 ,有关煤气化动力学的模型很多 ,但还未见有将这些模型进行详细的分析与比较的文章。本文总结了目前常用的煤气化动力学模型 ,提出了两种新的半经验模型 ;并运用这些模型处理了彬县、神木、王封煤的气化数据。通过各模型的相关系数及对各模型进行的分析与比较发现 ,所提出的下述煤气化动力学模型简单、适用、精度高。dxdt=k0 ynH2 O exp( EaRT) (1 x) m ,m =a bT　　在模型中 ,把m定义为煤种与温度的函数。此模型不但能有效地描述气化过程 ,同时它还能很好地描述煤气化在不同温度下的不同阶段性。     

Extrapolating H-atom transfer rate constants via thermochemical kinetics: The effect of tunneling

One of the important applications of chemical kinetics is the attempt to understand complex processes through kinetic modeling. This process frequently requires that rate constants be obtained by extrapolation of data either to higher or lower temperatures than the experimental, or by estimation or correlation with such data. Thermochemical kinetics combined with conventional transition state theory forms a framework from which this may be done. However, rate data for H transfer reactions may have a significant contribution from tunneling. In this work, a one dimensional approach to tunneling, consistent with conventional transition state theory, is taken to show how tunneling affects the extrapolation and correlation of rate constants in thermochemical kinetics. It is concluded that extrapolation and correlation are both quite good even when tunneling comprises 80% of the reaction. However, this is not without limitations, which are discussed. © 1993 John Wiley & Sons, Inc.     

Experimental microkinetic approach of the photocatalytic oxidation of isopropyl alcohol on TiO2. Part 1. Surface elementary steps involving gaseous and adsorbed C3H(x)O species

The present study concerns an experimental microkinetic approach of the photocatalytic oxidation (PCO) of isopropyl alcohol (IPA) into acetone on a pure anatase TiO2 solid according to a procedure previously developed. Mainly, the kinetic parameters of each surface elementary step of a plausible kinetic model of PCO of IPA are experimentally determined: natures and amounts of the adsorbed species and rate constants (preexponential factor and activation energy). The kinetics parameters are obtained by using experiments in the transient regime with either a FTIR or a mass spectrometer as a detector. The deep oxidation (CO2 and H2O formation) of low concentrations of organic pollutants in air is one of the interests of the PCO. For IPA, literature data strongly suggest that acetone is the single route to CO2 and H2O and this explains that the present study is dedicated to the elementary steps involving gaseous and adsorbed C3H(x)O species. The microkinetic study shows that strongly adsorbed IPA species (two species denoted nd-IPA(sads) and d-IPA(sads) due to non- and dissociative chemisorption of IPA, respectively) are involved in the PCO of IPA. A strong competitive chemisorption between IPA(sads) and a strongly adsorbed acetone species controls the high selectivity in acetone of the PCO at a high coverage of the surface by IPA(sads). The kinetic parameters of the elementary steps determined in the present study are used in part 2 to provide a modeling of macroscopic kinetic data such as the turnover frequency (TOF in s(-1)) of the PCO using IPA/O2 gas mixtures.     

Sensitivity analysis in chemical kinetics by the method of polynomial approximations

A new approach, the method of polynomial approximations (PAM), to the sensitivity analysis in chemical kinetics is presented. The method is based on first dividing the time domain of interest into subintervals, and then, within each subinterval, using low-degree interpolation polynomials to mimic the system temporal behavior. This procedure forces all parametric dependences of the system to reside in the expansion coefficients and transforms the differential sensitivity equations into a set of algebraic ones. The major computational effort of PAM is proportional to the number of components in the system, not to the number of parameters. In addition, higher order sensitivity coefficients in PAM can be generated quite readily once first-order ones are known. The information required to divide the time domain comes from a preliminary simulation study of the system temporal behavior, which is always available in any kind of modeling studies. Typically, for an interpolation polynomial of degree 3–4, only 10–20 subintervals are needed to attain satisfactory accuracy. The application of PAM is well suited to large-scale kinetic models, especially when an inexpensive scanning of the system sensitivity behavior is desired. The extremely high computational speed of PAM in securing sensitivity informations was demonstrated by two illustrative kinetic examples. Furthermore the problem of utilizing sensitivity information to unravel the functional dependence of a species concentration upon rate coefficients, to simplify a complex reaction model, and to elucidate mechanistic details of a reaction process was examined in detail.     

Recognition and dissociation kinetics in the interfacial molecular recognition of barbituric acid by amphiphilic melamine-type monolayers

Progress in the understanding of interfacial molecular recognition kinetics is obtained by use of the sweeping technique for experimental studies of the reaction kinetics between a host monolayer and a non-surface-active species dissolved in the aqueous subphase. The experimental results show that the interfacial recognition reaction between a 2C(11)H(23)-melamine (2,4-di(n-undecylamino)-6-amino-1,3,5-triazine) monolayer and dissolved barbituric acid is reversible when the 2C(11)H(23)-melamine/barbituric acid monolayer is transferred back onto a pure water subphase. The kinetics of the recognition and dissociation reaction is experimentally and theoretically investigated. The approximate additive theoretical model developed recently is extended to consider the dissociation kinetics of the interfacial supramolecular complex. The kinetic constants for the recognition and dissociation reactions in the mixed monolayer consisting of 2C(11)H(23)-melamine and 2C(11)H(23)-melamine/barbituric acid complex are determined. It is shown that the kinetic constant of the recognition reaction is nearly independent of temperature, whereas that of the dissociation reaction increases with increasing temperature.     

Kinetic isotope effect for H2 and D2 quantum molecular sieving in adsorption/desorption on porous carbon materials

Adsorption and desorption of H(2) and D(2) from porous carbon materials, such as activated carbon at 77 K, are usually fully reversible with very rapid adsorption/desorption kinetics. The adsorption and desorption of H(2) and D(2) at 77 K on a carbon molecular sieve (Takeda 3A), where the kinetic selectivity was incorporated by carbon deposition, and a carbon, where the pore structure was modified by thermal annealing to give similar pore structure characteristics to the carbon molecular sieve substrate, were studied. The D(2) adsorption and desorption kinetics were significantly faster (up to x1.9) than the corresponding H(2) kinetics for specific pressure increments/decrements. This represents the first experimental observation of kinetic isotope quantum molecular sieving in porous materials due to the larger zero-point energy for the lighter H(2), resulting in slower adsorption/desorption kinetics compared with the heavier D(2). The results are discussed in terms of the adsorption mechanism.     

Hydrolysis of Methylal Catalyzed by Ion Exchange Resins in Aqueous Media

In the present work, the chemical equilibrium and kinetics of methylal (PODE₁) hydrolysis catalyzed by ion–exchange resin in aqueous solutions were investigated. The study covers temperatures between 333.15 and 363.15 K at various starting compositions covering (PODE₁ + MeOH)/water molar ratio ranges from 0.5 to 1.5 in a time scale. On the basis of the experimental results, a mole fraction-based model of the chemical equilibrium and a pseudohomogeneous model are proposed to fit data based on true amount of monomeric formaldehyde. It has been demonstrated that the hydrolysis of PODE1 is slightly endothermic with the enthalpy 8.19 kJ/mol and the rate determining step. Finally, a feed–forward artificial neural networks (ANN) model is developed to model the concentration change of methanol in aqueous solutions. The results showed that the predicted data from designed ANN model were in good agreement with the experimental data with the coefficient (R²) of 0.98. Designed ANN provides a reliable method for modeling the hydrolysis reaction of methylal (PODE1).     

Automatic assignment of absolute configuration from 1D NMR data

[reaction: see text] Opposite enantiomers exhibit different NMR properties in the presence of an external common chiral element, and a chiral molecule exhibits different NMR properties in the presence of external enantiomeric chiral elements. Automatic prediction of such differences, and comparison with experimental values, leads to the assignment of the absolute configuration. Here two cases are reported, one using a dataset of 80 chiral secondary alcohols esterified with (R)-MTPA and the corresponding (1)H NMR chemical shifts and the other with 94 (13)C NMR chemical shifts of chiral secondary alcohols in two enantiomeric chiral solvents. For the first application, counterpropagation neural networks were trained to predict the sign of the difference between chemical shifts of opposite stereoisomers. The neural networks were trained to process the chirality code of the alcohol as the input, and to give the NMR property as the output. In the second application, similar neural networks were employed, but the property to predict was the difference of chemical shifts in the two enantiomeric solvents. For independent test sets of 20 objects, 100% correct predictions were obtained in both applications concerning the sign of the chemical shifts differences. Additionally, with the second dataset, the difference of chemical shifts in the two enantiomeric solvents was quantitatively predicted, yielding r(2) 0.936 for the test set between the predicted and experimental values.     

Extracting the mechanisms and kinetic models of complex reactions from atomistic simulation data

Determining reaction mechanisms and kinetic models, which can be used for chemical reaction engineering and design, from atomistic simulation is highly challenging. In this study, we develop a novel methodology to solve this problem. Our approach has three components: (1) a procedure for precisely identifying chemical species and elementary reactions and statistically calculating the reaction rate constants; (2) a reduction method to simplify the complex reaction network into a skeletal network which can be used directly for kinetic modeling; and (3) a deterministic method for validating the derived full and skeletal kinetic models. The methodology is demonstrated by analyzing simulation data of hydrogen combustion. The full reaction network comprises 69 species and 256 reactions, which is reduced into a skeletal network of 9 species and 30 reactions. The kinetic models of both the full and skeletal networks represent the simulation data well. In addition, the essential elementary reactions and their rate constants agree favorably with those obtained experimentally. © 2019 Wiley Periodicals, Inc.     

Model‐free multivariate curve resolution combined with model‐based kinetics: algorithm and applications

Multivariate curve resolution techniques are powerful tools to extract from sequences of spectra of a chemical reaction system the number of independent chemical components, their associated spectra, and the concentration profiles in time. Usually, these solutions are not unique because of the so‐called rotational ambiguity. In the present work, we reduce the non‐uniqueness by enforcing the consistency of the computed concentration profiles with a given kinetic model. Traditionally, the kinetic modeling is realized in a separate step, which follows the multivariate curve resolution procedure. In contrast to this, we consider a hybrid approach that combines the model‐free curve resolution technique with the model‐based kinetic modeling in an overall optimization. For a two‐component model problem, the range of possible solutions is analyzed, and its reduction to a single, unique solution by means of the hybrid kinetic modeling is shown. The algorithm reduces the rotational ambiguity and improves the quality of the kinetic fitting. Numerical results are also presented for a multi‐component catalytic reaction system that obeys the Michaelis–Menten kinetics. Copyright © 2012 John Wiley & Sons, Ltd.     

A perturbation analysis of rate theory of self-regulating genes and signaling networks

A thorough kinetic analysis of the rate theory for stochastic self-regulating gene networks is presented. The chemical master equation kinetic model in terms of a coupled birth-death process is deconstructed into several simpler kinetic modules. We formulate and improve upon the rate theory of self-regulating genes in terms of perturbation theory. We propose a simple five-state scheme as a faithful caricature that elucidates the full kinetics including the "resonance phenomenon" discovered by Walczak et al. [Proc. Natl. Acad. Sci. U.S.A. 102, 18926 (2005)]. The same analysis can be readily applied to other biochemical networks such as phosphorylation signaling with fluctuating kinase activity. Generalization of the present approach can be included in multiple time-scale numerical computations for large biochemical networks.     

Vibrational energy transfer and relaxation in O2 and H2O

Near-resonant vibrational energy exchange between oxygen and water molecules is an important process in the Earth's atmosphere, combustion chemistry, and the chemical oxygen iodine laser (COIL). The reactions in question are (1) O2(1) + O2(0) --> O2(0) + O2(0); (2) O2(1) + H2O(000) --> O2(0) + H2O(000); (3) O2(1) + H2O(000) <--> O2(0) + H2O(010); (4) H2O(010) + H2O(000) --> H2O(000) + H2O(000); and (5) H2O(010) + O2(0) --> H2O(000) + O2(0). Reanalysis of the data available in the chemical kinetics literature provides reliable values for rate coefficients for reactions 1 and 4 and strong evidence that reactions 2 and 5 are slow in comparison with reaction 3. Analytical solution of the chemical rate equations shows that previous attempts to measure the rate of reaction 3 are unreliable unless the water mole fraction is higher than 1%. Reanalysis of data from the only experiment satisfying this constraint provides a rate coefficient of (5.5 +/- 0.4) x 10(-13) cm3/s at room temperature, between the values favored by the atmospheric and laser modeling communities.