International Journal of Chemical Kinetics最新文献

A longstanding project of the chemical kinetics community is to predict reaction rates and the behavior of reacting systems, even for systems where there are no experimental data. Many important reacting systems (atmosphere, combustion, pyrolysis, partial oxidations) involve a large number of reactions occurring simultaneously, and reaction intermediates that have never been observed, making this goal even more challenging. Improvements in our ability to compute rate coefficients and other important parameters accurately from first principles, and improvements in automated kinetic modeling software, have partially overcome many challenges. Indeed, in some cases quite complicated kinetic models have been constructed which accurately predicted the results of independent experiments. However, the process of constructing the models, and deciding which reactions to measure or compute ab initio, relies on accurate estimates (and indeed most of the numerical rate parameters in most large kinetic models are estimates.) Machine-learned models trained on large datasets can improve the accuracy of these estimates, and allow a better integration of quantum chemistry and experimental data. The need for continued development of shared (perhaps open-source) software and databases, and some directions for improvement, are highlighted. As we model more complicated systems, many of the weaknesses of the traditional ways of doing chemical kinetic modeling, and of testing kinetic models, have been exposed, identifying several challenges for future research by the community.

In the realm of combustion kinetic modeling, the norm involves employing thousands of reactions to delineate the chemical conversion of hundreds of species. Notably, theoretically predicted rate coefficients and branching ratios, derived through the RRKM/master equation (ME) model, play an increasing role in kinetic modeling. Thus minimizing the uncertainty of theoretical prediction across wide working conditions is crucial to refine a kinetic model. The present study takes ethyl (C₂H₅) + oxygen (O₂) reaction system to show that combined forward and reverse uncertainty analysis can be used to further constrain calculated rate coefficients and branching ratios, which were already calculated by high-level quantum chemistry methods. Forward global uncertainty analysis with the artificial neural network-high dimensional model representation (ANN-HDMR) method is employed to select key parameters affecting total rate coefficients of C₂H₅ + O₂ and branching ratios of C₂H₅ + O₂ = C₂H₄ + HO₂ (C1). Reverse uncertainty analysis with Bayesian method was then applied to refine the key input parameters based on experimental data at working conditions selected by sensitivity entropy. Although the target RRKM/ME model system was built on high level theoretical calculations, the combined forward and reverse uncertainty analyses are still able to reduce uncertainties of predicted total rate coefficients of C₂H₅ + O₂ and branching ratios for C1 across a wide range of working conditions. Specifically, the uncertainties of total rate coefficient and C1 branching ratio have been reduced from 1.46 and 1.52 to 1.30 and 1.36 at 298 K and 1 Torr. The analysis process proposed in the present work effectively extrapolates the constraint ability of accurate measured data at one condition to wide working conditions based on the RRKM/ME model.

For net-zero carbon emissions, hydrogen/ammonia blends have drawn considerable attention for the application in industrial combustion devices. Various chemical mechanisms have been developed to describe the oxidation and combustion of hydrogen/ammonia mixtures at certain conditions. A comprehensive evaluation and comparison of the performance of these mechanisms is thus of high interest, especially in terms of their application for particular computational studies. Thus, this work aims to compare the existing chemical mechanisms in terms of their performance for the combustion of hydrogen/ammonia mixtures over a wide range of experimental conditions. In addition to previous literature studies, the model performance is evaluated by using two different methods for the assessment of prediction accuracy. Besides the conventional measure of point-wise differences between model and data, the curve-matching method is also applied, which quantifies the dependence of model response on physical conditions additionally, by comparing the similarity between the curve shapes of the predicted and measured results. Extensive experimental data are taken into account in the model evaluation, including 136 datasets obtained from various facilities in the past 10 years. Nineteen mechanisms are compared, which were published in recent five years. It is revealed that these models give strongly different numerical results for combustion targets, such as laminar burning velocities, ignition delay times, and species concentrations. The chemical mechanisms of Zhang et al. (2021), Han et al. (2023), Mei et al. (2019), Li et al. (2019), and Stagni et al. (2020) show relatively satisfactory performance over the entire investigated domain. Moreover, it is found that the estimated prediction accuracy of chemical mechanisms is highly sensitive to model evaluation methods.

Corrosion protection of steel bars in alkaline concrete environments poses a common challenge in marine engineering. One approach to mitigate steel bar corrosion is the addition of corrosion inhibitors to the concrete. In alkaline environments, the passivation of rebars occurs through anodic passivation coupled with the cathodic oxygen reduction reaction (ORR). The catalysis of ORR can expedite anode passivation. To investigate the corrosion inhibition of steel bars in alkaline environments, meso-tetra(4-carboxyphenyl)porphine (TCPP), known for its ORR catalytic properties, is selected. TCPP forms adsorption films on the surface of steel bars, facilitating the formation of passivation films. TCPP primarily adsorbs onto active sites on the surface of the passivation film, where lattice iron ions have leached. The adsorbed TCPP accelerates the formation of the passivation film through ORR catalysis, inhibiting the development of passivation film defects and enhancing the integrity and protection of the passivation film. The most significant effect is observed when the concentration of TCPP is 0.5 mmol/L. The physical adsorption of TCPP is primarily determined by the negative charge centers, namely the carboxyl group O and the pyrrole N. However, due to steric hindrance caused by the unrestricted rotation of the carboxyl benzene, the pyrrole N does not play a dominant role in chemical adsorption. Instead, the active site for chemical adsorption is the carboxyl group O. The adsorption process significantly reduces the diffusion coefficient of TCPP molecules, providing a robust and stable adsorption binding. Phthalocyanine molecules without carboxyl benzene groups adopt a planar structure, allowing them to form stable adsorption configurations on the iron surface through flat adsorption. This observation provides guidance for the design of novel metal phthalocyanine molecules. Specifically, the development of metal phthalocyanine molecules with modifying groups that are coplanar with the phthalocyanine ring and possess restricted rotation can achieve flat adsorption, improve coverage rate, and enhance adsorption configuration stability.

The permanganate–H₂SO₄ redox reaction, useful in oxidative treatments under aqueous conditions, was studied spectrophotometrically in the absence and presence of cetyltrimethylammonium bromide (CTAB). The decolorization reactions were influenced by the [MnO₄⁻], [H₂SO₄], and temperature. Permanganate reduction follows first-, and complex–order kinetics with permanganate, and H₂SO₄ concentrations, respectively. The reduction of permanganate (Mn(VII)) proceeds through a complex formation between MnO₄⁻ and H₂SO₄. The characteristic absorption peaks for MnO₄²⁻ (λ_max = 439 and 606 nm), MnO₄³⁻ (λ_max = 667 nm), and MnO₂ (λ_max = 400–418 nm) were not appeared during the redox reaction. The KMnO₄ degradation efficiency remains unaffected with sodium pyrophosphate and sodium fluoride. The results of this study demonstrated the formation of Mn(II) as the stable product in acidic reaction media. The degradation efficiency increases drastically from 15 to 100% with 2.0 × 10⁻⁴ to 16.0 × 10⁻⁴ mol/L CTAB concentration under sub-, and post-micellar reaction conditions, respectively. The thermodynamic parameters (activation energy = 98.8 and 43.2 kJ/mol), activation of enthalpy (96.3, and 39.0 kJ/mol), activation of entropy (16.2 and −149.5 J/K/mol), free energy of activation (93.1 and 83.5 kJ/mol) were calculated without and with CTAB, respectively. Hence, CTAB can be exploited for its multifunctional applications, and specifically for the catalytic role in the permanganate-assisted redox reactions in future.

Benzyl radical (C₇H₇), one of the resonantly stabilized hydrocarbon radicals, is one of the significant precursors of polycyclic aromatic hydrocarbons in interstellar media and combustion engines. The unimolecular decomposition of benzyl radical is still incompletely understood despite of its importance and relatively small molecular size. The decomposition reactions of benzyl radical were investigated in the present study by using the ab initio transition state theory (TST) and the multi-well master equation theory. Specifically, all reaction pathways on the potential energy surface of C₇H₇ was calculated at the level of QCISD(T)/CBS. For the reactions with multireference characters, the CASPT2(9e,7o)/aug-cc-pVTZ method was used to calculate the vibrational frequencies and energies of structures along the one-dimensional reaction coordinate of the breaking bond. The high-pressure limits of rate constants for all the reactions were obtained by using the TST except those for C₇H₆ + H and C₆H₄ + CH₃ by the variational TST. The pressure-dependent rate constants were obtained by using the multi-well master equation simulations. The calculated rate constants agree well with available experimental and theoretical data in the literature. Moreover, the present results identify the composition of the non-hydrogen-atom production observed in previous experiments, which provide new insights into the reactions of aromatic compounds.

Removing polychlorinated biphenyls (PCBs) from subsurface water, soils, and transformer oil is crucial to save the environment from these pollutant materials. Hydrodechlorination (HDC) of PCBs consists of numerous chemical reactions and the simple kinetic models may not provide details for the process. To gain more awareness of the reaction mechanism, in the proposed approach, the isoconversional methods of the Friedman were investigated paralleling other kinetic models of Langmuir-Hinshelwood (L-H), Eley-Rideal (E-R), pseudo-first-order, and pseudo-second-order methods. The analysis was validated by laboratory results of HDC of contaminated transformer oil in front of Pd/MWCNTs. The most reactivity was observed for biphenyls with a higher number of chlorines. Finding a suitable model, Akaike Information Criteria were applied. It was attained that Friedman model was the most suitable for monitoring of HDC of PCBs in front of catalyst. Besides, E-R reaction was appropriate to elucidate the theoretical interpretations of the adsorption and desorption of reactants and chlorinated benzene.

Quasi-tetrahedral o-azophenylboronic acid (azoB-ROH), which contains the protic solvent ROH, is a key species in the colorimetric sensing of saccharides by o-azophenylboronic acid (azoB). In this study, we compared the reactivity of azoB-ROH with that of trigonal azoB and tetrahedral o-azophenylboronate (azoB-OH⁻), and clarified the reaction mechanism of azoB-ROH with cis-1,2-cyclopentanediol and D-glucose. Analysis of the kinetics of the reactions of azoB with cis-1,2-cyclopentanediol and D-glucose in DMSO:water = 1:9 and azoB with cis-1,2-cyclopentanediol in tetrahydrofuran containing a small amount of methanol revealed that there was not much difference in the reactivity of azoB-H₂O and azoB-OH⁻, although the reactivity of azoB was higher than that of azoB-MeOH, that is, the reaction mechanism of azoB-H₂O was essentially the same as that of azoB-OH⁻.

The effect of small fractions of acetaldehyde (CH₃CHO) on the ignition delay time of methane (CH₄) was examined at high pressure. Measurements are reported for the ignition delay time obtained in a rapid compression machine (RCM) at a compression pressure (P_c) of ∼60 bar and temperatures after compression (T_c) in the range 750–900 K for fuel-air equivalence ratios ϕ in the range 1–4. The results show that mixtures of 2%–5% CH₃CHO in CH₄ ignite under conditions at which pure methane does not ignite experimentally. The efficiency of acetaldehyde as a promoter seems to be comparable to that of other oxygenated fuels like alcohols and ethers. For comparison with the experimental results, ignition delay times are computed using an updated reaction mechanism and two mechanisms from the literature for CH₃CHO oxidation. For most conditions, the simulations using the current mechanism agree with the measurements to within a factor of two. The ignition profile shows a pre-ignition temperature rise and two-stage ignition similar to that previously observed in low fractions of dimethyl ether in ammonia; both phenomena are captured by the simulations. Analysis of simulations at constant volume indicates that CH₃CHO is oxidized much more rapidly than CH₄, producing reactive species that initiate the oxidation of CH₄ and generates heat that accelerates oxidation toward ignition. The low-temperature chain-branching reactions of CH₃CHO are important in the early oxidation of the fuel mixture. Additional simulations were performed for equivalence ratios of ϕ = 1 and 4, at a compression pressure (P_c) of 100 bar and T_c = 750–1000 K. The simulations indicate that CH₃CHO has a strong ignition-enhancing effect on CH₄, with small fractions reducing the ignition delay time by up to a factor of 100, depending on the temperature, as compared to pure CH₄.

The inherent autocatalytic kinetics of the urea–urease–H⁺ system positions it as a promising candidate for the design of dynamic materials with time-domain programmable functions. Nevertheless, the stability of the enzyme can markedly influence the temporal evolution dynamics of the system and curtail its widespread applicability. This work employs several kinds of enzyme stabilization methods, including chemical cross-linking, physical coating, solvent stabilization, and solvent-physical coating co-modification, to systematically explore the impact of enzyme stabilization on clock reaction dynamics. Extensive experimental tests and analysis indicate that solvent and chemical cross-linking stabilization methods can better preserve clock dynamics with sensitive switching ability. Nevertheless, due to significant pH changes in the reacting system, the reusability of the enzyme is better retained in the physical coating and solvent-physical coating co-modification methods.