Chemical Kinetic Parameters Research Articles

Rapid pyrolysis technique for determination of kinetic parameters of ammonium perchlorate decomposition

A laser pyrolyser setup is developed to achieve isothermal conditions using a heating rate of up to ∼105 °C.s−1 for rapid pyrolysis of a sample. It provides mechanistic information about the decomposition behavior of the sample during combustion, typically in the condensed phase. Typically, chemical kinetics data for condensed phase reactions during combustion is not derived from ab initio techniques, but rather by fitting the variation of linear burning rate with pressure with appropriate kinetic parameters. This leads to a wide variation of chemical kinetic parameters governing the decomposition of the same solid propellant ingredient, such as the commonly used oxidizer, ammonium perchlorate (AP). Therefore, a newly developed laser pyrolyser along with Fourier transform infrared (FTIR) spectroscopy was used to study the rapid pyrolysis of AP at 1 bar. The concentration profiles of the evolved gases were used to develop the global reaction mechanism. The global reaction mechanism that emerged is: NH4ClO4→1.09H2O+0.06HNO3+0.56NO2+0.18N2O+0.5Cl2+0.71O2+0.88H2 with pre-exponential factor (A) = 6.6×107 s−1 and activation energy (Ea) = 108 kJ.mol−1. Kinetic parameters of the same AP sample from thermogravimetric analysis are A = 5.6 ×105 s−1, and Ea = 100 kJ.mol−1. This suggests that kinetic parameters obtained from slow heating experiments predict a reaction rate significantly lower than that observed under high heating rates. Therefore, the raw data generated from rapid pyrolysis would be useful as an input to solid propellant combustion models improving their predictive capability.

Thermal degradation assessment, impact strength, and hardness of combination epoxy and polystyrene powder composite

The present study investigates the reactions of polystyrene and epoxy/polystyrene powder composites, exploring different weight percentages (8%, 12%, and 16%) of polystyrene during decomposition under highly elevated temperatures within a nitrogen atmosphere. The findings reveal that polystyrene content significantly influences the thermal behavior of pure epoxy, with a higher polystyrene content correlating with the increased thermal stability of the composites. This study observed a three-stage mass loss process by examining the reaction kinetics of thermal decomposition using the Coats-Redfern approach. Initially, weight reduction occurs due to moisture and volatile elimination, followed by a smooth mass loss phase attributed to weaker polymer chain linkages and, ultimately, char formation. Chemical kinetic parameters, such as activation energy and frequency factor, were successfully determined using the Coats-Redfern approach, with a first-order reaction observed across all data points, demonstrating a high R-square mean value of 99.8%. Differential scanning calorimetry (DSC) and thermal gravitational analysis (TGA) analyses revealed an increase in glass temperature from 86.95 to 92.85 °C and an elevation in activation energy from 75.38 to 92.85 kJ/mol with increasing polystyrene content (0–16 wt%). Furthermore, the study investigated the influence of thermodynamic parameters. In terms of mechanical properties, increasing polystyrene content reduced impact strength (from 8.5 to 4.23 Kj/m2). In contrast, hardness increased from 77.5 for pure epoxy to 80.4 at 12 wt% polystyrene content in the composite. These findings underscore the importance of thermal stability results in developing a comprehensive understanding of thermal decomposition processes, informing future research endeavors and industrial applications.

Potential enhancements in commercial glucose biosensors utilizing electrochemical faradaic spectroscopy: Analyzing the sum component in the EC’ mechanism

AbstractHerein we report the use of electrochemical faradaic spectroscopy in biosensors, with application on a commercially used first‐generation glucose biosensor manufactured by Zimmer and Peacock. The mechanism for the glucose sensor was explained and approximated as an EC’ mechanism, where E is for electron transfer step, whereas C’ signifies catalytical chemical step. Experimental chronoamperograms in electrochemical faradaic spectroscopy are compared to chronoamperometry, where it was found that the sum component in electrochemical faradaic spectroscopy gives higher response, resulting in better sensitivity of the sensor. Theoretical simulations give an insight of the response in electrochemical faradaic spectroscopy for an EC’ mechanism and its dependence on different parameters (dimensionless electrode kinetic parameter, mid potential, dimensionless chemical kinetic parameter). For some specific set of parameters (large electrode and catalytic reaction kinetics), theoretical chronoamperograms in electrochemical faradaic spectroscopy can become similar to the experimental. The property of the sum component to have higher response in EC’ mechanism for specific parameters is not limited only for electrochemical faradaic spectroscopy. Exemplified with square‐wave voltammetry, it is shown that other pulse techniques for an EC’ mechanism can also result with higher sum component. Hence, for better sensitivity in quantitative analysis in EC’ mechanism, one should quantify the sum component.

Impact of Composition Ratio on the Expansion Behavior of Polyurethane Grout.

Different formulations of foaming polyurethane grout offer controlled expansion rates. This is crucial for precision in filling voids without exerting excessive pressure on surrounding structures, which could potentially cause damage. This study focuses on the impact of composition on the expansion performance of tailor-made polyurethane grouting materials. Initially, multiple unknown chemical reaction kinetic parameters were identified by combining free expansion tests, which involved measuring density and temperature changes, with the particle swarm optimization algorithm. A numerical simulation, integrating chemical kinetic models and fluid flow equations, was established to replicate the free expansion process of polyurethane grout in a cup, aligning with our experimental results. Subsequently, we analyzed the polymerization process of polyurethane grout with varying compositions to determine the effect of composition ratios on grout expansion. Our findings reveal that the expansion ratio of foaming polyurethane is predominantly influenced by the concentrations of physical and chemical foaming agents, followed by isocyanate concentration. Polyol, in contrast, exerts a relatively minor influence. Furthermore, the solubility of the physical foaming agent in the grout determines both its maximum allowable concentration and its maximum contribution to volume increase. This study provides valuable insights for the design and selection of polyurethane grout components tailored to diverse applications.

Detonation Cell Size Prediction Using Artificial Neural Networks (ANNs) for Hydrogen/Hydrocarbon/Ammonia/Nitrous Oxide Mixtures

In this work, a previously developed three-feature Artificial Neural Network (ANN) model with dimensional inputs is directly applied to predict the cell size of hydrocarbon/ammonia/nitrous oxide mixtures and compare these to experimental data. This model uses as inputs three ZND parameters (MCJ, ΔI, and σ˙max), which are mainly calculated using Konnov’s and Mével’s mechanisms. A similar prediction is obtained with the two mechanisms for the biogas–O2, H2–O2, H2–N2O, and NH3–O2 mixtures, indicating that the model is not only limited to Konnov’s chemical kinetic mechanism which was used for its training. The overall good agreement between the ANN predictions and the actual experimental values for the aforementioned mixtures, which are not used in the original training of the ANN model, is promising and shows its potential for application and extension to other mixtures and initial conditions, provided that the chemical kinetic parameters describing the ideal reaction zone structure could be computed. The model is then used to compare experimental cell size data from two detonation tube facilities, and also different chemical kinetic mechanisms for NH3-N2O mixtures. In the end, the original ANN model is expanded with the inclusion of additional cell size data, showing a slightly lower mean error for the predicted cell sizes if the data for the mixtures considered in this study are taken into account for the training of the new ANN model.

Physics-informed data-driven model of dehydration reaction stage in the sintering process of ternary cathode materials

The sintering process is the main process that affects the performance of ternary cathode materials. Due to the closed, continuous, and long-term characteristics of the sintering process carried out in a roller kiln, the reaction state including reaction degree, particle size, and etc., of the raw materials cannot be directly obtained through sampling detection, resulting in ineffective temperature control. This article mainly focuses on modeling the dehydration reaction stage of the sintering process to obtain the reaction state of the raw materials. Firstly, a two-sphere model is established based on Newton’s second law and the particle volume conservation equation to describe the relationship between the particle radius and sintering temperature of lithium hydroxide and ternary precursor; Secondly, the chemical kinetic parameters of the dehydration reaction in the two-sphere model are obtained by combining the single heating rate scanning method with the multiple heating rate scanning method; Then, in order to improve the accuracy of the two-sphere model and reduce the impact of external environmental temperature changes, a physics-informed neural network model is constructed by combining the two-sphere model with the neural ordinary differential equation model. Finally, the effectiveness of the modeling method is verified through numerical simulation and empirical data.

Prediction of Hydrogen Abstraction Rate Constants at the Allylic Site between Alkenes and OH with Multiple Machine Learning Models.

Hydrogen abstraction reactions between hydrocarbons and hydroxyl radicals are important propagation steps in radical chain reactions, playing a crucial role in atmospheric and combustion chemistry. This study focuses on predicting the rate constants of the prototype of the reaction class of hydrogen abstractions, i.e., the primary allylic hydrogen abstraction from alkenes by the OH radical, via utilizing machine learning (ML) methods. Specifically, three distinct models, namely, feedforward neural network (FNN), support vector regression (SVR), and Gaussian process regression (GPR), have been employed to construct robust ML models for prediction. We proposed a novel strategy that seamlessly integrates descriptor preprocessing, a pairwise linear correlation analysis, and a model-specific Wrapper method to enhance the effectiveness of the feature selection procedure. The selected feature subset was then evaluated using two cross-validation techniques, i.e., leave-one-group-out (LOGO) and K-fold cross-validations, for each of the three ML models (FNN, SVR, and GPR) to assess their predictive and stability performance. The results demonstrate that the FNN model, trained with seven representative descriptors, achieves superior performance compared to the other two methods. For the FNN model, the average percentage deviation is 39.06% on the test set by performing LOGO cross-validation, while the repeated 10-fold cross-validation achieves a percentage prediction deviation of 19.1%. Two larger alkenes with 10 carbons were selected to test the prediction performance of the trained FNN model on primary allylic hydrogen abstraction. Results show that the kinetic predictions follow well the modified three-parameter Arrhenius equation, indicating the reliable performance of FNN in predicting hydrogen abstraction rate constants, especially for the primary allylic site. Hopefully, this work can shed useful light on the application of ML in generating chemical kinetic parameters of hydrocarbon combustion chemistry.

Investigation of Thermal Degradation Properties and Chemical Kinetic Characteristics of Biomass Pyrolysis via TG/DTG and FTIR Techniques: Sesame Stalks as Potential Source of Bioenergy in Ethiopia

The dependence on fossil fuels and the overexploitation of it is a bottlenecked problem of the globe leading to finding alternative renewable resources that may be used as an energy source in place of fossil fuels. Thermogravimetric analysis (TGA) is a technique used to identify potential renewable energy sources. This study investigated the kinetic, thermodynamic parameters, and pyrolysis characteristics of sesame stalk (SS) biomass pyrolysis using thermogravimetric (%) (TG)‐derivative thermogravimetry (DTG) techniques. The pyrolysis was carried out at different heating rates (15, 20, and 25°C/min). The chemical kinetics parameters were determined using isoconversional model‐free methods, including Kissinger–Akahira–Sunose (KAS), the Ozawa–Flynn–Wall (OFW), and model fitting techniques like the Coats–Redfern (CR) model. The thermodynamic parameters (∆H, ∆G, and ∆S) were calculated using kinetic data. The average activation energy for SS biomass was found to be 77.96 and 84.15 kJ/mole for the KAS and OFW methods, respectively. The activation energy (E) for SS biomass from the integral method varied between 29.61–142.58 kJ/mole for reaction order models and 4.90–122.33 kJ/mole for diffusion models. The distributions of pre‐exponential factor (A) for the reaction order models are virtually normal in the range of 0.2–0.7, upon the Eα values obtained using the OFW and KAS approach. The average value of enthalpy, Gibbs free energy, and entropy of SS were also reported. The study suggests that SSs are a potential biomass for sustainable bioenergy production, and kinetic and thermodynamic data are crucial for reactor design for the pyrolysis of SSs.

Effect of lemon balm (Melissa officinalis L.) essential oil on some characteristics of oil/water food emulsions

Food emulsions are used on a daily basis by people, therefore it is of great importance to study the factors that can influence their stability. The aim of this work is to track the influence of lemon balm essential oil (Melissa officinalis L.) on the change of some physical and chemical indicators, kinetic (turbidity) and thermodynamic (Gibbs free energy, enthalpy and entropy) parameters, which are related to their stability. 24 food emulsions were developed with oleic type sunflower oil acting as an oil phase in concentrations of 20 and 30%, soybean protein emulsifier in concentrations of 1, 2, and 3% and lemon balm essential oil in concentrations of 0.1, 0.2 and 0.3%. The pH of the emulsions was determined, microscopic photographs were taken to measure the sizes of the colloidal particles, turbidity was observed for 15 days, their absorbance was determined, Gibbs energy, enthalpy and entropy were calculated. The most stable is the emulsion with 30% oil phase, 3% soybean protein emulsifier and 0.3% lemon balm essential oil.

Nitration of biodiesel by acetyl nitrate: Kinetic study and chemical safety parameters

The aim of this study was to synthesize a bio-sourced substitute to the 2-Ethyl Hexyl Nitrate (EHN) by nitrating a biodiesel. EHN is commonly used to improve the auto-ignition properties of diesel fuels. The biodiesel was obtained by trans-esterification of canola oil. The nitration reaction of biodiesel by acetyl nitrate was carried out in a reaction calorimeter RC1 with semi-batch mode to study its kinetic and exothermic behavior and acetyl nitrate as nitrating agent. The impact of the synthesis temperature on the thermal behavior and on the reaction medium composition was investigated. The final product was analyzed by using several analytical techniques such as iodine value, infrared spectrometry, GC–MS. Three nitrated products have been identified: Methyl-8-nitro oleate, Methyl-10-nitrate-9-nitrostearate and 10-acetoxy-methyl-9-nitrostearate, whose selectivity depends on the synthesis temperature. A chemical model for nitration is proposed and the thermal power profiles released by the reaction mixture are used to estimate the energy and chemical kinetic parameters. Safety parameters, maximum temperature of the synthesis reaction (MTSR) and TD24 were also determined. In addition, a Cooperative Fuel Research (CFR) engine was used to analyze the cetane number of diesel fuel mixed with our additive. The results showed an increase in cetane number by 6 points.

Chemical composition and gas production kinetic parameters of sweet potato vine waste silage after preserved for short and prolonged periods

The sweet potato (Ipomoea batata L.) culture produces by-products with animal feeding potential, such as vines. Given that sweet potato vines are seasonal and highly perishable, the adoption of conservation strategies such as silage becomes necessary to ensure their availability during food shortage periods. The knowledge of the optimal conservation period of this type of silage is limited, with very few studies available on this topic. The objective of this work was to evaluate the chemical composition, fermentative characteristics, and in vitro gas production kinetics of sweet potato vine silage after 45 and 120 days of conservation and to compare them with those of fresh sweet potato vine. The sweet potato vines were collected, cut into 2-3 cm pieces, and ensiled for 45 and 120 days. After this period, the nutritional value was determined using the standard methods of AOAC. The gas production and kinetics were fitted to the exponential equation proposed by Ørskov and McDonald. It was found that the sweet potato vine can be successfully preserved as silage, regardless of the conservation period, and that it shows a high potential for being used as an alternative food source for ruminants. In vitro dry matter and organic matter digestibility were not much different for the fresh sweet potato vine, and the silage was conserved for 120 days. However, the silage for 120 days had lower accumulated in vitro gas production compared to the fresh sweet potato vine. It was concluded that the silage conservation period did not produce significant changes in chemical composition or in vitro digestibility, with the sweet potato vine showing good nutritional values both fresh and after a conservation period. Therefore, sweet potato vine silage can be used as an alternative food source in ruminant diets.

Utilization of Salmon fish bone wastes as a novel bio-based heterogeneous catalyst-support toward the production of biodiesel: Process optimizations and kinetics studies

This study investigated the feasibility of using calcined Salmon fish bone wastes as an inexpensive and reusable catalyst-support for the biodiesel production via transesterification of sunflower oil. In this venue, a series of catalysts were synthesized by impregnating potassium hydroxide (KOH) onto the calcined Salmon fish bones. The as-prepared catalysts were characterized through several techniques, including the FESEM, BET-BJH, TGA, FT-IR, and XRD. In this regard, the effects of the calcination temperature of the waste Salmon fish bone, KOH loading amount, and the calcination temperature of KOH-impregnated support upon the catalytic activity of the final catalyst were understudied. Results displayed that the calcination temperature of fish bones at 1273 K with 40 wt% of KOH loading, which was calcined at 873 K, led to the highest catalytic performance. For this optimum material, the effects of the parameters, such as the catalyst loading, the methanol: oil molar ratio, and the reaction time and temperature upon the biodiesel production yield were examined. It was determined that the optimum operating conditions for the reaction included the catalyst loading of 10 wt%, the methanol: oil molar ratio of 10:1, and the reaction temperature of 338 K for 3 h. The gas chromatography and 1HNMR analyses revealed an optimum biodiesel production yield of 99.13 %. This result is attributed in part to a rather high basicity of the aforementioned optimum material. Moreover, this optimum species was shown to endure four consecutive reaction cycles, whereas its activity dropped by about 10 %. Furthermore, the chemical kinetic parameters of the reaction using this catalyst were determined to be; the reaction rate constant of 0.45 h−1 and its respective activation energy of 67.01 kJ/mol. Ultimately, it was demonstrated that neither internal nor external mass transfer limitations existed in the heterogeneous system considered in this research hence, all observed behaviors were solely due to chemical kinetics.

Comparative Chemical Composition and Kinetic Parameter Determination of Four Cold‐Pressed Edible Oils from the Moroccan Desert

Comparative Chemical Composition and Kinetic Parameter Determination of Four Cold‐Pressed Edible Oils from the Moroccan Desert

Experimental and Numerical Studies of Self-Expansible Polyurethane Slurry Diffusion Behavior in a Fracture Considering the Slurry Temperature

Polyurethane grouting material (polymer) has been widely used in rock mass fracture grouting. The previous test of polymer slurry grouting in planar fracture did not consider the influence of temperature; therefore, in this paper, a test of polymer slurry grouting in planar fracture was firstly conducted in order to explore the diffusion characteristics of polymer slurry. The results show that the preheating temperature of polymer slurry has a great influence on the diffusion of slurry in fractures, which should be considered in the research of polymer fracture grouting. In addition, the slurry temperature is related to the chemical reaction of the polymer itself. However, the existing polymer fracture grouting models ignore the influence of temperature and the chemical reaction of the polymer slurry itself, which lack the rationality to reveal the diffusion behavior of the polymer slurry in fracture. Therefore, in this paper, a chemical reaction-fluid dynamic (CF) model was established. In addition, the Particle Swarm Optimization (PSO) algorithm was used to obtain the chemical reaction kinetic parameters of the polymer slurry. Based on the CF model, the diffusion characteristics of the polymer slurry during the fracture diffusion process were calculated. The applicability of the CF model was verified by comparing the experimental data with the calculated results. Finally, the influence of polymer preheating temperature and ambient temperature on slurry fracture grouting behavior was explored by the CF model. The research in this article provides some theoretical reference for the design of grouting parameters in fracture grouting engineering.

The weakening effect of the inhibition of CO2 on the explosion of HCNG with the increase of hydrogen: Experimental and chemical kinetic research

To explore the inhibitory effect of CO2 on HCNG (Hydrogen enriched compressed natural gas) explosion and its chemical kinetic mechanism, the explosion pressure and flame of CO2/HCNG/Air (hydrogen ratio: 0–0.6, CO2 addition: 3 vol%, 6 vol%, and 9 vol%) were tested in a 20 L spherical explosion tank at normal temperature and normal pressure. The experiment results shown that: as the addition of CO2 increases, the inhibition effect on HCNG explosion flame and pressure becomes more obvious. The larger the H2 ratio, the more difficult it is to inhibit HCNG explosion flame and pressure. To explore the chemical kinetics reasons for the above laws, the chemical kinetic parameters (such as free radical formation rate and temperature sensitivity coefficient) of the explosion reaction under the above conditions were calculated by CHEMKIN-PRO. The results indicate that CO2 mainly acts as a stable third body in the reaction system, thereby slowing down the growth of explosion chain reactions. In addition, as the main product of the CH4 oxidation reaction, CO2 has a certain weakening effect on the CH4 oxidation reaction. As the proportion of H2 increases, the elementary reactions such as 3# and 84# that generate ·H radicals are promoted, increasing the concentration of ·H radicals in the reaction system. Therefore, the dominant role of 38# on the temperature rise of the reaction system is enhanced, and the contribution of the CH4 oxidation reaction to the temperature rise of the reaction system is weakened. This is the chemical kinetic reason that CO2 has a weak inhibitory effect on the energy release of the HCNG explosion reaction when the proportion of H2 is large. The research results can provide a theoretical basis for the development of HCNG explosion prevention and control technology.

Influence of equivalence ratio and H2 blended ratio on explosion propagation characteristics of DME/H2 blended gas in closed narrow space

To reveal the explosion risk and propagation law of dimethyl ether (DME)/hydrogen (H2) blended gas, the explosion propagation characteristics of DME/H2 blended gas under different equivalence ratio (Φ) and hydrogen blended ratio (λ) was investigated based on experimental research and theoretical analysis. The results show that the peak overpressure (Pp), the peak pressure rise rate (dP/dt)p and the peak shock wave propagation velocity (Vp) show an increasing and then decreasing trend with the increase of Φ, and reach the maximum at Φ = 1.0. The effect of a little addition of H2 on the explosion hazards of blended gas is small, but when λ > 10%, the explosion hazards increase significantly. The magnitude of increase of Pp, (dP/dt)p and Vp is different with the increase of λ. Compared with the enhancement effect on Pp and (dP/dt)p, the enhancement effect on Vp is more obvious with the continuous blend of H2. Comprehensive analysis of the thermodynamic and chemical kinetic parameters of H2, the chemical kinetic parameters of H2 play a dominant role in the explosion risk of hydrogen-blended gases.

Influence of the Physical Properties of Samples in the Use of NIRS to Predict the Chemical Composition and Gas Production Kinetic Parameters of Corn and Grass Silages

Livestock production is the main economic engine of the Azores. Given the role nutrition plays in animal performance and the context of limited Averages sharing the same letter are noagricultural area of the archipelago, optimising the quality and availability of the fodder used in feeds takes on an important role in increasing the competitiveness and viability of the industry. This work evaluated the potential of NIR spectroscopy to quantify several chemical and biological parameters used to assess silage quality in the specific agroclimatic context of the Azores. Reference values were determined for 400 grass silage and 400 corn silage samples. The corresponding NIR spectra were extracted, and mathematical models capable of correlating these readings with the various parameters were built. The best results were obtained for crude protein, neutral detergent fibre, acid detergent fibre, and crude ash for both fresh and dry samples. For the biological parameters concerning gas production, no satisfactory results were reached. It was concluded that it was feasible to build models capable of accurately predicting these important quality parameters, which demonstrates that NIRS is a viable technique that can be used in the Azores to perform a close and timely monitoring of forage quality and to facilitate the management and optimisation of diets.

Impacts of phosphorus and nitrogen absence on microbial diversity and sulfate removal in anaerobic batch reactors

Sulfate-rich effluents have been successfully treated in anaerobic reactors using sulfate-reducing bacteria (SRB). Many authors have demonstrated that these systems require nitrogen and phosphorous supplementation to achieve high sulfate removal rates. However, the resource ratio theory assumes that some species can be dominant according to the nutritional relations used or even without external nutrient supplementation. Thus, this study evaluated the SRB communities in batch reactors without external nitrogen and phosphorus sources based on most probable number (MPN) quantification, denaturing gradient gel electrophoresis (DGGE) analyses and sequencing. The sulfate and chemical oxygen demand (COD) removal and kinetic parameters were also determined. After 100 days of operation, the sulfate and COD removal achieved 71.8 ± 10% and 86.5 ± 10%, respectively. The SRB population increased from 8.106 to 4 × 1012 MPN 100 mL−1, and the richness of SRB bands was much higher at the end of the experiment compared to the inoculum. In addition, the sequenced bands from SRB-DGGE showed similarities to Desulfacinum infernum, Desulfobulbus sp, Syntrophobacter and Desulfomicrobium aestuarii-related sequences. Therefore, biological treatment of acid mine drainage wastewater was effective in the absence of nutrients, lowering costs and providing high sulfate removal efficiency.

Study of the reaction mechanism based on the formation of the first carbocyclic ring from propargyl and diacetylene

The formation of the first carbon ring is a crucial rate-controlling step in developing polycyclic aromatic hydrocarbons (PAHs). It is vital to investigate the mechanism of the creation of the first carbon ring to inhibit the formation of PAHs. To explore the growth process of the first carbocyclic ring, this work used the average localized ionization energy (ALIE) and electrostatic potential (ESP) to predict the reaction sites. Moreover, the reaction paths and chemical kinetic parameters for the generation of the first carbocyclic ring from propargyl (C3H3) + diacetylene (C4H2) are calculated based on the density functional theory (DFT) method and transition state theory (TST). The results showed that the addition reaction of C3H3 +C4H2 can form five-, six- and seven-membered ring molecules, in which the five-membered ring formation is fastest and the six-membered ring formation is slowest. During the formation of the first carbon ring, the activation energy required for the H transfer and cyclization reactions is large, and the reaction rate is slow, which determines the formation rate of the first carbon ring. The rate of H-transfer reaction on each carbon ring depends on the number of C atoms of the carbon ring, with the five-membered ring being the fastest and the six-membered ring the slowest. This paper improves the reaction kinetics and thermodynamic data of the first carbon ring formation during the combustion of hydrocarbon fuels, which offers a powerful theoretical basis for predicting the generation of PAHs.

Comprehensive influence of uncertainty propagation of chemical kinetic parameters on laminar flame speed prediction: a case study of dimethyl ether

The uncertainties existing in the parameters of chemical kinetic models have a non-negligible influence on the model predictions. It is necessary to conduct a quantitative uncertainty analysis to explore the influence of each parameter on chemical mechanism predictions. To comprehensively consider the effect of the uncertainties of reaction rate parameters, thermodynamic parameters, and transport parameters on model predictions, local sensitivity analysis, local-sensitivity-based uncertainty analysis (LSUA), and random-sampling high dimensional model representation (RS-HDMR) method were coupled to investigate the uncertainty propagation of the chemical kinetic parameters to the calculated laminar flame speed of dimethyl ether under a wide range of conditions using a detailed mechanism. First, the uncertainty analysis was conducted using the local sensitivity analysis and the LSUA method under a wide range of operating conditions to identify the important operating conditions and chemical kinetic parameters. It is found that the prediction uncertainty of laminar flame speed is more obvious under the conditions of high dilution ratio, high pressure, and large equivalence ratio than that under other conditions. According to the results of LSUA, the prediction uncertainty is mainly from the reaction rate coefficients and thermodynamic data. Then, the uncertainty propagation from the significant parameters to the calculated laminar flame speed under important conditions was analysed using the RS-HDMR method. To reduce the huge computational cost of the RS-HDMR method, the backpropagation artificial neural network was employed. The RS-HDMR results indicate that the reaction H + O2 = O + OH has the highest sensitivity coefficient under the whole investigated conditions, which is different from the results using the LSUA method. The non-linear relationship between the rate coefficient and the predicted laminar flame speed is responsible for the discrepancy. Furthermore, it is found that the sensitivity coefficient of the input parameters strongly depends on the operating conditions.