Chemical Kinetic Parameters Research Articles

Langmuir Adsorption Kinetics in Liquid Media: Interface Reaction Model.

Adsorption kinetic equation has been derived assuming that the process follows the behavior of a heterogeneous chemical reaction at the solid–liquid interface. This equation is converted into the Langmuir isotherm at equilibrium and describes well the unsteady-state adsorption process. Based on that, a working equation has been developed, which gives adsorption-rate-constant independent of operating parameters including concentration. Also, a kinetic model expressed as a sum of first- and second-order systems available in the literature has been applied (modified with the interface reaction concept) to determine the adsorption rate constant. Both methods gave similar results. Three dimensionless numbers have been developed to determine and distinguish pseudo-first-order and pseudo-second-order kinetics justified from the viewpoint of chemical kinetics. It is shown that curve-fitting with a high correlation coefficient could validate an empirical kinetic model, but the fitted model parameters could not automatically be related to chemical kinetic parameters if the model itself is not grounded on well-defined chemical kinetics. Finally, it is concluded that the currently applied empirical approach could not provide reliable data for comparison among similar systems, while the Langmuir kinetic equation developed based on the concept of heterogeneous reaction would be a good basis for standardization of the method for adsorption system characterization.

Chemical Kinetics Bayesian Inference Toolbox (CKBIT)

The robust estimation of chemical kinetic parameters and their associated uncertainty is essential in the field of chemistry and catalysis. The Chemical Kinetics Bayesian Inference Toolbox (CKBIT) is a Python software library introduced to enable users to implement advanced Bayesian inference techniques for kinetic parameter estimation and uncertainty quantification. Leveraging functionalities of other open source Python packages and offering simplified implementation through minimal user-required coding and straightforward Excel input files, CKBIT aspires to make the inference method easily accessible for chemical kinetics. CKBIT provides maximum a posteriori, Markov chain Monte Carlo, and variational inference estimation options. Users may apply these functionalities to estimate activation energies, reaction orders, and pre-exponential terms from chemical reaction data from batch reactors, continuous stirred-tank reactors, and plug flow reactors. The availability of prior distribution specification and the implementation of hierarchical modeling in CKBIT provide a heightened level of accuracy in estimates of kinetic parameters and their uncertainties. Program summaryProgram title: CKBITCPC Library link to program files:https://doi.org/10.17632/tnzk2jvffs.1Developer's repository link:https://github.com/VlachosGroup/ckbitCode Ocean capsule:https://codeocean.com/capsule/8389927Licensing provisions: MIT licenseProgramming language: PythonNature of problem: Rigorous estimation and uncertainty quantification of kinetic rate parameters are necessary for chemical researchers to create physical models with explicit levels of certainty. Advanced statistical treatments of Bayesian inference meet this need with a high level of rigor. However, current software available for Bayesian inference is complex and nuanced in its implementation, preventing widespread adoption among researchers.Solution method: We present a Python package with a modular approach to applying different Bayesian inference techniques for kinetic rate parameter estimation and uncertainty quantification. Optimal point estimates can be obtained through maximum a posteriori estimation, while full probability distributions of parameters can be generated through Markov chain Monte Carlo estimation or variational inference. The code is straightforward to use in contrast to current Bayesian inference software, and it interfaces with Excel for ease of data entry.

Foaming parameter identification of polyurethane using FOAMAT® device

AbstractA key problem in the modeling of polyurethane (PU) foaming is the determination of relevant physical parameters for the viscosity, the gas expansion, and the curing rate. Indeed, it is difficult to measure the chemical kinetics parameters as well as the viscosity of industrial PU formulations (polyol–isocyanate–water mixture) because the time scales of gas production and PU crosslinking are very short and hardly compatible with the installation of the sample in characterization devices such as differential scanning calorimetry and parallel plates rheometer. A FOAMAT® system has been developed to get these experimental data but the relationship between measurements and the rheo‐chemical parameters has not been clearly established. In this paper, an analytical model of the foaming process is developed in the cylindrical FOAMAT geometry, which allows identifying the parameters of the curing and gas production kinetics equations, as well as the viscosity. This analytical model is based on a set of simplifying hypotheses which validity is checked using the finite element computation software REM3D dedicated to foaming modeling and applicable for injection‐molding processing.

Torrefaction of Short Rotation Coppice Willow. Characterization, hydrophobicity assessment and kinetics of the process

Short Rotation Coppice Willow (SRCW) is one of the newest sources of renewable energy. Torrefaction enhances the initial poorest characteristics of SRCW, such as hygroscopicity or low heating value compared to traditional fuels, to use it as a fuel. Non-oxidative and oxidative torrefaction of SRCW were compared. Torrefaction were conducted within the range 200–240 °C and torrefied SRCW and released gases were characterized (proximate, ultimate, compositional and heating value analysis as well as hydrophobicity assessment, Py-GC/MS and chemical-kinetics parameters). At optimal torrefaction temperature, mass and energy yields were around 88% and 93%, respectively, moisture was reduced up to 1.22–1.28% and H/C and O/C atomic ratios up to 1.4 and 0.6, respectively. Biomass turns hydrophobic since contact angle increase and the amount of water absorb decrease in contact angle and liquid penetration studies, respectively. The global reaction order was 2 and kinetic constant values were in the range 4.6 10−5 s−1–3.6 10−5 s−1.

Near flammability limits behavior of methane-air mixtures with influence of flammable gases and nitrogen: An experimental and numerical research

The flammability limit is a key parameter used to evaluate the combustion characteristics and explosion risk of flammable gases mixtures. In this work, the flammability limit of a methane with mixed flammable gases was measured in a standard cylindrical equipment, and the effect of inert gas on the flammable limit was studied as well. Moreover, the GRI-Mech3.0 mechanism was employed to obtained the thermodynamic and chemical kinetic parameters by using the PREMIX code. The experimental results show that the addition of gaseous fuel can reduce the flammability limit of methane, rise the explosion risk of methane, and increase the amount of inert gas needed for complete inertization. Thermodynamic and chemical kinetic analyses showed that with the increase in the volume fraction of the mixed gas, the peak flame temperature and the flammability exponent gradually increased when approaching the lower flammability limit. The peak flame temperature and the flammability exponent gradually decreased when approaching the upper flammability limit. Sensitivity analysis indicated that the competition between chain branching reaction R38 and chain termination reaction R35 had an important effect on the lower flammable limit, while that competition effect between R38 and R52 dominated the upper flammability limit. The influence of flammable gas on the flammability limit of methane was mainly determined by changing the thermodynamic characteristic of the mixed gas and the competition between the chain reaction. These results will supplement the corresponding flammability limit database and help to prevent potential explosion hazards.

Modification of chemical-kinetic parameters for 11-air species in re-entry flows

The chemical-kinetic parameters for the two-temperature model for 11-air species are modified to increase the accuracy of the thermochemical nonequilibrium model for high temperature gases in Earth re-entry flows. In the present work, a set of modified chemical-kinetic parameters, for the vibrational relaxation time with high temperature correction, the Arrhenius rate coefficients for dissociation, the vibrational energy removal ratio due to chemical reaction, the equilibrium constant to evaluate the reverse rate coefficients, and collision integrals for high temperature gases are proposed, based on the results of recent state-to-state kinetic calculations and shock-tube experimental data. These modified chemical-kinetic parameters are utilized to reproduce the measured NO, N2, and N2+ VUV and UV spectrum of the high-enthalpy shock-tube experiments performed at the EAST facility, and the existing flight and ground experimental data from BSUV-2, the Mars-entry spacecraft model, RAM C-II, and FIRE-II. The proposed chemical-kinetic parameters more accurately reproduce the measured molecular spectra in the VUV and UV ranges, and the surface heat flux and electron number density on the surface of the re-entry modules, than the previous chemical-kinetic parameters in the Park model, except for the super orbital re-entry speed of the Fire-II experiments. In the Fire-II experimental case, the influence of the modified chemical-kinetic parameters in the present work are less effective because of the fast dissociation of the molecules.

Modelling on Shock-Induced Energy Release Behavior of Reactive Materials considering Mechanical-Thermal-Chemical Coupled Effect

Reactive material (RM) is a new type of energetic material, which is widely used in the military technology fields such as fragmentation warheads and shaped charge warheads. Violent chemical reactions take place in the impact process of reactive materials, and how to realize the macro numerical simulation of shock-induced energy release behavior of reactive materials is one of the most urgent problems to be solved for its future military applications. In this study, a numerical simulation approach and procedure is proposed, which can simulate the shock-induced energy release behavior of reactive materials on a macro scale. Firstly, program implementation of the mechanical-thermal-chemical coupled effect model for RM is realized in the second-development interface of LS-DYNA software. Then, the adaptive simulated annealing algorithm is used to fit the chemical reaction kinetic parameters of RM using the direct ballistics test data. Finally, the simulation calculation of the fragment penetrating upon steel plate is carried out to expand the applicability of the numerical simulation approach proposed in this study. The results show that the numerical simulation approach proposed in this study can reproduce the results of the direct ballistics test more accurately, which assumes practical significance for the engineering application of reactive materials in the military field in the future.

Modeling and experimental investigation on the fuel particle heat-up and devolatilization behavior in a fluidized bed

The proper understanding and description of fuel devolatilization behavior in a fluidized bed (FB) is important to the FB reactor design and modeling. Aiming at this issue, two different mathematical models, isothermal (0D) particle model and one-dimensional (1D) particle model, have been developed. The particle heat transfer is solved simultaneously using an iterative approach with the existing nitrogen containing chemical percolation devolatilization (CPD-NLG) model. Experiments in a special designed FB reactor were conducted to help validate both the temperature solver and modifications to the fast nitrogen release chemical kinetic parameters. The results show that when the bed temperature is higher or coal size become smaller, the final volatiles yield increases and the nitrogen remaining in char decreases. Under all conditions given in the present study, the final nitrogen content of char is always lower than that of parent coal. The yields of some volatile species are also affected by the coal size and bed temperature. In addition, simulation analysis reveals that the deviation between the results of these two models cannot be ignored if the particle size exceeds a specific value (transition size), namely, the large particle is improper to be described as isothermal during heat-up, while this transition size decreases with the increase of bed temperature. A selection principle of these two models is proposed for balancing the calculation precision and computational time. The particle model developed in this work makes it possible to carry out further FB reactor simulations with the devolatilization process more consistent with laboratory data.

Theoretical description of hyperpolarization formation in the SABRE-relay method.

SABRE (Signal Amplification By Reversible Exchange) has become a widely used method for hyper-polarizing nuclear spins, thereby enhancing their Nuclear Magnetic Resonance (NMR) signals by orders of magnitude. In SABRE experiments, the non-equilibrium spin order is transferred from parahydrogen to a substrate in a transient organometallic complex. The applicability of SABRE is expanded by the methodology of SABRE-relay in which polarization can be relayed to a second substrate either by direct chemical exchange of hyperpolarized nuclei or by polarization transfer between two substrates in a second organometallic complex. To understand the mechanism of the polarization transfer and study the transfer efficiency, we propose a theoretical approach to SABRE-relay, which can treat both spin dynamics and chemical kinetics as well as the interplay between them. The approach is based on a set of equations for the spin density matrices of the spin systems involved (i.e., SABRE substrates and complexes), which can be solved numerically. Using this method, we perform a detailed study of polarization formation and analyze in detail the dependence of the attainable polarization level on various chemical kinetic and spin dynamic parameters. We foresee the applications of the present approach for optimizing SABRE-relay experiments with the ultimate goal of achieving maximal NMR signal enhancements for substrates of interest.

Iterative model-based experimental design for efficient uncertainty minimization of chemical mechanisms

The uncertainties of chemical kinetic model parameters induce uncertainties in model predictions. Automatic optimization and uncertainty minimization techniques have been developed to constrain these uncertainties based on sets of experimental target data for quantities of interest. While such methods were frequently used to optimize models for relatively well-studied systems with large numbers of available targets, only few of these experimental data points may be of crucial importance. In addition, for novel fuel candidates such as biofuels and synthetic fuels, the number of available measurements is generally limited. Thus, an important aspect to be explored in this context is the number of experimental data points required to achieve a certain degree of uncertainty reduction, and the determination of optimal experimental conditions for these. To target this question, a model-based experimental design framework based on the criterion of D-optimality is used in the present work to automatically identify these optimal conditions. As an example, the auto-ignition of dimethyl ether is investigated. The majority of experiments with high priority cover the intermediate- and low-temperature regimes, where the employed prior model exhibits the largest prediction uncertainties. It is also found that 90 % of the maximum observed reduction of average prediction uncertainty in ignition delay times can be achieved based on only the ten most informative experiments alone. The results thus demonstrate that few well-selected measurements allow for efficient model uncertainty reduction, and the employed approach provides an effective means of identifying the optimal conditions, which is useful for further experimental investigation. On the other hand, the inclusion of more experiments into the calibration process still provides additional benefit in terms of the posterior uncertainties of a number of important model parameters, which points to the importance of taking such data into account in case of their availability.

Dependence of kinetic sensitivity direction in premixed flames

The sensitivities of turbulent combustion simulations to chemical kinetic parameters can be analyzed to understand the controlling reactions in turbulent flames and to quantify the uncertainties in simulations. However, computing the sensitivity of turbulent combustion simulations to a large number of kinetic parameters is still challenging. A promising approach is to estimate the sensitivity from laminar flames, especially for cases where the flamelet model is applicable. Under these conditions, the underlying hypothesis is that the sensitivity direction of the flamelet profiles is independent of the strain rate and the flame coordinate, which is the progress variable for premixed flames. In the present work, this hypothesis was tested in laminar premixed counterflow flames. We first studied the sensitivity directions of two extreme cases, the near-extinction strained flames and the freely propagating unstretched flames. It was found that the sensitivity directions of the extinction strain rate and the laminar flame speed are aligned with each other for various fuels, equivalence ratios, and pressures. We then studied the dependence of the sensitivity direction of the maximum flame temperature on the strain rate as well as the dependence of the sensitivity direction of the species profiles on the progress variable. It was found that the sensitivity direction of maximum temperature was largely independent of the strain rate. Moreover, the sensitivity directions of the temperature and species profiles were independent of the progress variable, and they were all similar to the sensitivity direction of the extinction strain rate. These findings suggest that there is a universal sensitivity direction for turbulent premixed flames and the direction can be estimated by the sensitivity direction of extinction strain rate. These conclusions will enable efficient sensitivity analysis of turbulent combustion simulations when the hypothesis is valid.

Effect of Heating Rate on Chemical Kinetics of Chicken Manure With Different Gas Agents

Abstract This paper presents the study on the effect of different heating rates on the pyrolysis and gasification process of the chicken manure. The obtained results are shown by the extent of reaction, the kinetics of the reaction, and differential thermal analysis. In total, 24 cases were carried out; eight heating rates with three different gas agents each. The results show that when using nitrogen or carbon dioxide as gas agents, the reactions were endothermic. Consequently, the energy must be supplied in terms of heating to sustain the reaction. Furthermore, the air gasification was exothermic, which means that the reaction can be sustained without external heating, where the self-ignition was observed between 450 °C–600 °C. The thermal degradation of the three main components of the chicken manure was obtained. The pyrolysis process was divided into two regions at 360 °C and the order of reaction of five for both regions. For the gasification process, it was observed that carbon dioxide had the most complicated mechanism with four stages. Finally, it is recommended to use the lowest heating rate to allow a quasi-equilibrium state through slow heating. Consequently, the delay in response or any transient error can be avoided as they are the main reason for measurement errors. These chemical kinetic parameters can be used in the future for the chicken manure simulation using the order of reaction mechanism for solid-state gasification.

Global Warming Potential (GWP) for Methane: Monte Carlo Analysis of the Uncertainties in Global Tropospheric Model Predictions

Estimates of the global warming potential (GWP) of methane rely on the predictions from global chemistry-transport models. These models employ many uncertain input parameters representing the sources and sinks for methane and those for the tropospheric ozone, which is formed as a by-product of the methane sink process. Five thousand quasi-randomly Monte Carlo sampled model runs employing a zonally averaged global model were completed, each with a base case and a pulse case that differed from the base case only in having an additional 149 Tg (1Tg = 109 kg) emission pulse of methane. Each of the five thousand pulse case experiments had a small excess of methane that decayed away throughout the twenty-year model experiment. The radiative forcing consequences of this excess methane, and the excess tropospheric ozone formed from it, were integrated over a 100-year time horizon. The GWP was calculated in each of the five thousand model experiments from the sum of the radiative forcing consequences of methane and tropospheric ozone, by expressing them relative to the radiative forcing consequences of an identical emission pulse of carbon dioxide. The 2-sigma confidence range surrounding the methane atmospheric lifetime estimated in the Monte Carlo analysis was considerably wider than that derived from observations, suggesting that some of the input parameter combinations may have been unrealistic. The rejection of the unrealistic Monte Carlo replicates increased the mean methane GWP and narrowed its 2-sigma confidence interval to 37 ± 10 over a 100-year time horizon for emission pulses of the order of 1 Tg. Multiple linear regression was used to attribute the uncertainty in the output GWPs to each of the 183 uncertain input parameters, which represented emission source sectors, chemical kinetic rate coefficients, dry deposition velocities and biases in temperature and water vapour concentrations. Overall, the only significant contributions to the uncertainty in the methane GWP came from the chemical kinetic parameters representing the CH4 + OH, CH3O2 + HO2, CH3O2 + NO and the terpene + O3 reaction rate coefficients.

Chemical composition, kinetics of degradation, and digestibility of forage of different purpose sorghum cultivars

The aim of the study was to identify suitability of different purpose sorghum cultivars for silage production and for green chopping, at the first and second season, based on the chemical composition and degradation kinetics. The experiment was based on a randomized block design with four replicates, with sowing in the months of November and March, as the first and second season, respectively. The trial was conducted at the Plant Production Sector of the Federal Institute of Education, Science and Technology of Rondonia, Colorado do Oeste campus, and chemical analyses were performed at the Animal Nutrition Laboratory of the Federal University of Mato Grosso, Cuiaba campus. The treatments comprised six sorghum hybrids of different purposes (BRS 308 and BRS 310, grain sorghum; BRS 655 and BRS 610, forage sorghum; BRS 506 and CMSXS 647, sweet sorghum). The chemical composition, digestibility, and kinetic parameters were evaluated. At the first season, there was a higher digestibility (P < 0.0001) for sweet sorghum BRS 506, while for the second season, both grain sorghum BRS 308 and sweet sorghum cultivars BRS 506 and CMSXS 647 presented higher digestibility (P = 0.0005). Considering the nutritional value, all sorghum cultivars have the potential to produce silage, or to be used as green chop, at the first and second season.

Rapid Single Molecular Dynamics from Single Photon Arrivlas

Fluorescence correlation spectroscopy (FCS), is a widely used tool routinely exploited for in vivo and in vitro applications. While FCS provides estimates of dynamical quantities, such as diffusion coefficients, it demands high signal to noise ratios and long time traces, typically in the minute range. In principle, the same information can be extracted from microseconds to seconds long time traces; however, an appropriate analysis method is missing. To overcome these limitations, we adapt novel tools inspired by Bayesian non-parametrics, which starts from the direct analysis of the observed photon counts. With this approach, we are able to analyze time traces, which are too short to be analyzed by existing methods, including FCS. This new way of analysis extends the capability of single molecule fluorescence confocal microscopy approaches. For example, it helps us reduce photo-toxic damage (by virtue of requiring shorter experiments) on living samples but it also allows us to probe processes from single photons which occur on rapid, data acquisition, timescales. Now, at this time scale, we generalize our method above to infer unimolecular chemical kinetic parameters for single molecules occurring over such short experimental durations from single photon arrivals in continuous time. That is, we construct models of dynamics for single molecules from single photons. In addition to kinetics, the proposed method can estimate the time at which a reaction occurs as a single molecule traverses the confocal volume.

Natural Gas-Oxygen Combustion in a Super-Critical Carbon Dioxide Gas Turbine Combustor

The paper presents results for chemical kinetics of combustion process in the combustor of oxy-fuel cycle super-critical carbon dioxide gas turbine based on the Allam thermodynamic cycle. The work shows deviation of the normal flame propagation velocity for the case of transition from the traditional natural gas combustion in the N2 diluent environment to the combustion at super-high pressure up to 300 bar in CO2 diluent. The chemical kinetics parametric study involved the Chemkin code with the GRI-Mesh 3.0 kinetic mechanism. This mechanism provides good correspondence between calculation results and test data. The CO2 and N2 diluents temperature, pressure and contents influence the flame propagation velocity and the chemical kinetics parameters in the two gas turbine types. It is demonstrated that the CO2 diluent slows down chemical reactions stronger than the N2 one. The flame propagation velocity in carbon dioxide is four time smaller than in the N2 one. In the oxy-fuel cycle combustor a pressure increase reduces the flame propagation velocity. Increase of the CO2 content from 60 to 79% reduces the flame propagation velocity for 65% at atmospheric pressure and for 94% at super-critical pressure. An increase of the combustor inlet mixture temperature from 300 to 1100 K at super-critical pressure causes the flame propagation velocity increase for 94%. The flame propagation velocities compatible with the traditional gas turbines may be reached at the CO2 diluent content of the O2 + CO2 mixture in the active combustion zone must be below 50%.

Thermal decomposition, kinetics and combustion parameters determination for two different sizes of rice husk using TGA

The present study concerns the thermal pyrolysis kinetics of sieved rice husk that was classified into two sizes (38–200 μm) and (200–1000 μm) by using Thermo-Gravimetric analysis (TGA) at different heating rate (HR) values under N2. The thermal pyrolysis analysis was presented and kinetic parameters as activation energy (E), frequency factor (A), and order of reaction (n) were determined by using three different kinetic models. The effect of heating rate (HR) and particle sizes on the chemical kinetic parameters were presented and discussed. Direct method gave lower values of E and A compared to the integral method. Results showed that as particle size increases, values of the activation energy (E) and frequency factor (A) nearly increase. The combustion characteristic parameters such as ignition, burnout and peak temperatures and their corresponding times were determined. It found that larger sizes (200–1000 μm) have a relatively lower ignition temperature, higher activation energy and noticeably lower ignition times as compared to the smaller sizes (38–200 μm).

Direct sensitivity analysis for ignition delay times

The sensitivity coefficients of ignition delay time with respect to chemical kinetic rate parameters is traditionally calculated using a brute force approach wherein the number of initial value problems solved is no fewer than the number of rate parameters. By reformulating the underlying initial value problem as a boundary value problem, it is shown that the sensitivity coefficients can be extracted directly, accelerating thus the computational time by at least an order of magnitude. This has far reaching consequences in kinetic model development and optimization, especially when a large number of rate constants are involved.

Synthesis and sorption properties of porous resorcinol–formaldehyde resins prepared by polymerization of the emulsion dispersion phase

Resorcinol–formaldehyde resins for the removal of Cs from liquid media have been synthesized by polymerization of the emulsion dispersion phase. Chemical stability and kinetic parameters of the ion-exchange process in the porous ion exchangers have been estimated using the diffusion coefficient and the exchange half-time. The results of Cs (Cs-133 и Cs-137) removal under static and dynamic conditions are provided. The efficiency of Cs removal from the simulated solution of the evaporator concentrate (EC) containing Cu2+, Co2+, Cr3+, and Ni2+ cations has been estimated. Good prospects of application of porous ion exchangers in the function of materials for Cs removal from highly mineralized alkali media have been demonstrated.

Sensitivities of direct numerical simulations to chemical kinetic uncertainties: spherical flame kernel evolution of a real jet fuel

A systematic computational study is conducted to understand the propagation of uncertain chemical kinetic parameters into turbulent premixed flame simulations. Two snapshots of the cross-section of a spherical flame kernel in homogeneous isotropic turbulence is extracted from a three dimensional direct numerical simulation (DNS) and serve as the initial conditions for a series of subsequent two-dimensional DNS that sample and quantify the impact of chemical kinetic uncertainties on the integrated heat release rates and certain species concentrations. The target configuration features real jet fuel chemistry modeled by a 31-species reduced reaction model. The importance of each reaction is first ranked, by comparing the normalized reaction flux based on a snapshot from the DNS. A two-step process is then taken where initial Monte Carlo screening is performed by perturbing 99 reaction rate constants simultaneously. Following this, a subset of 19 reactions is studied using a larger collection of 2D DNS simulations. As the major quantity of interest, the integrated heat release rate is consistently the most sensitive to reactions R8 (H+O2=O+OH) and R32 (CO+OH=CO2+H). When combined with a consideration of the reaction rate uncertainty, R71 (CH3+OH=CH2*+H2O) consistently impacts the quality of flame prediction most prominently. For the case starting with a strong burning flame, the rate limiting reactions are found to be not significantly different between the turbulent and laminar conditions, although the magnitudes of sensitivity coefficients are amplified for certain reactions under turbulent conditions due to an enlarged thermochemical space. For the case initialized with a near-extinction flame, more upstream and/or competing reactions with R8 and R32 are observed. Another manifestation of the enlarged thermochemical space in turbulent flames is the wider range of influential reactions for integrated mass of CO, in comparison with the laminar condition where the sensitivity is dominated by R32. For H and C2H2, reactions R71, R42 (HCO+O2=CO+HO2) and R40 (HCO+M=CO+H+M) are identified to impact the model predictions for such species as acetylene in the most significant manner.