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Добірка наукової літератури з теми "Chemical kinetics"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 9 листопада 2024

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Статті в журналах з теми "Chemical kinetics"

1

Yablonsky, Gregory, Daniel Branco, Guy Marin, and Denis Constales. "New Invariant Expressions in Chemical Kinetics." Entropy 22, no. 3 (March 24, 2020): 373. http://dx.doi.org/10.3390/e22030373.

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This paper presents a review of our original results obtained during the last decade. These results have been found theoretically for classical mass-action-law models of chemical kinetics and justified experimentally. In contrast with the traditional invariances, they relate to a special battery of kinetic experiments, not a single experiment. Two types of invariances are distinguished and described in detail: thermodynamic invariants, i.e., special combinations of kinetic dependences that yield the equilibrium constants, or simple functions of the equilibrium constants; and “mixed” kinetico-thermodynamic invariances, functions both of equilibrium constants and non-thermodynamic ratios of kinetic coefficients.

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2

Moses, Julianne I. "Chemical kinetics on extrasolar planets." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2014 (April 28, 2014): 20130073. http://dx.doi.org/10.1098/rsta.2013.0073.

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Chemical kinetics plays an important role in controlling the atmospheric composition of all planetary atmospheres, including those of extrasolar planets. For the hottest exoplanets, the composition can closely follow thermochemical-equilibrium predictions, at least in the visible and infrared photosphere at dayside (eclipse) conditions. However, for atmospheric temperatures , and in the uppermost atmosphere at any temperature, chemical kinetics matters. The two key mechanisms by which kinetic processes drive an exoplanet atmosphere out of equilibrium are photochemistry and transport-induced quenching. I review these disequilibrium processes in detail, discuss observational consequences and examine some of the current evidence for kinetic processes on extrasolar planets.

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3

Zhong, Wei, and Zhou Tian. "Application of Genetic Algorithm in Chemical Reaction Kinetics." Applied Mechanics and Materials 79 (July 2011): 71–76. http://dx.doi.org/10.4028/www.scientific.net/amm.79.71.

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In this paper, a summary of Genetic Algorithm methods developed recent years applied in chemical reaction kinetics was presented. The applications of the Genetic Algorithm in reduction of the chemical reaction kinetics, estimation of the chemical kinetic parameters and calculation of the chemical kinetic equations were expounded here. Eventually, the confronted problem and developing trend of the application of Genetic Algorithm methods in chemical kinetics were reviewed.

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4

Fedoseev, V. B., and Е. N. Fedoseeva. "Kinetics of chemical reactions in spray." Kinetika i kataliz 65, no. 2 (September 28, 2024): 107–15. http://dx.doi.org/10.31857/s0453881124020016.

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The number of observations demonstrating a significant effect of droplet sizes on the kinetics of chemical processes has increased with the expansion of the scope of application of spray technology. The equations linking the concentrations of reagents, the volume of droplets, the initial composition of the solution, the composition of the gas medium and the speed of processes are formulated within the framework of formal chemical kinetics. Using the example of second-order reactions (coupling, exchange, condensation, polymerization, polycondensation), it is shown that size kinetic effects occur when chemical processes are accompanied by changes in the droplet sizes in equilibrium with the gas medium. The results of computer simulation of condensation reaction and polycondensation process reproducing size effects are presented. Kinetic curves obtained by modeling the polycondensation process are compared with experimental data.

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5

Udgaonkar, Jayant B., and George P. Hess. "Acetylcholine receptor kinetics: Chemical kinetics." Journal of Membrane Biology 93, no. 2 (June 1986): 93–109. http://dx.doi.org/10.1007/bf01870803.

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6

Borgert, C. J., C. Fuentes, and L. D. Burgoon. "Principles of dose-setting in toxicology studies: the importance of kinetics for ensuring human safety." Archives of Toxicology 95, no. 12 (October 8, 2021): 3651–64. http://dx.doi.org/10.1007/s00204-021-03155-4.

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AbstractRegulatory toxicology seeks to ensure that exposures to chemicals encountered in the environment, in the workplace, or in products pose no significant hazards and produce no harm to humans or other organisms, i.e., that chemicals are used safely. The most practical and direct means of ensuring that hazards and harms are avoided is to identify the doses and conditions under which chemical toxicity does not occur so that chemical concentrations and exposures can be appropriately limited. Modern advancements in pharmacology and toxicology have revealed that the rates and mechanisms by which organisms absorb, distribute, metabolize and eliminate chemicals—i.e., the field of kinetics—often determine the doses and conditions under which hazard, and harm, are absent, i.e., the safe dose range. Since kinetics, like chemical hazard and toxicity, are extensive properties that depend on the amount of the chemical encountered, it is possible to identify the maximum dose under which organisms can efficiently metabolize and eliminate the chemicals to which they are exposed, a dose that has been referred to as the kinetic maximum dose, or KMD. This review explains the rationale that compels regulatory toxicology to embrace the advancements made possible by kinetics, why understanding the kinetic relationship between the blood level produced and the administered dose of a chemical is essential for identifying the safe dose range, and why dose-setting in regulatory toxicology studies should be informed by estimates of the KMD rather than rely on the flawed concept of maximum-tolerated toxic dose, or MTD.

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7

Cruz Camacho, Elkin Alejandro, Juan Andrés Montoya Arguello, and Jesús Alberto Ágreda Bastidas. "CHEMical KINetics SimuLATOR (Chemkinlator): A friendly user interface for chemical kinetics simulations." Revista Colombiana de Química 49, no. 1 (January 1, 2020): 40–47. http://dx.doi.org/10.15446/rev.colomb.quim.v1n49.83298.

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CHEMical KINetics SimuLATOR is a Graphical User Interface for the simulation of reaction mechanisms. The interface allows the user to see and change the parameters of a reaction network within a single window. Chemkinlator comes with built-in support for three types of kinetic simulations: Time Series, which computes the concentration of all species in an interval of time in a defined model; Bifurcation diagrams, which are the result of running several Time Series simulations over gradually different kinetic rate constants; and Flow/Temperature time series, which takes into account the effect of flow in the Continuous-flow well-Stirred Tank Reactor, and the effect of temperature on the rates constants according to the Arrhenius equation. In our research group, Chemkinlator has been the primary tool used to test the predictions made by algorithms that analyze homochirality phenomena. Chemkinlator is written in C++14 and Qt, and it uses the Fortran subroutine DLSODE to solve the differential equations associated with the reaction networks. Chemkinlator is open source software under the Apache 2.0 license and can be downloaded freely from https://gitlab.com/homochirality/chemkinlator.

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8

Bosch, Hans. "Comprehensive chemical kinetics, vol. 23, kinetics and chemical technology." Applied Catalysis 20, no. 1-2 (January 1986): 326–27. http://dx.doi.org/10.1016/0166-9834(86)80038-0.

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9

Derouane, EricG. "Comprehensive chemical kinetics, vol. 23 kinetics and chemical technology." Journal of Molecular Catalysis 39, no. 3 (March 1987): 389–90. http://dx.doi.org/10.1016/0304-5102(87)80086-x.

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10

Tran, Hai Nguyen. "Differences between Chemical Reaction Kinetics and Adsorption Kinetics: Fundamentals and Discussion." Journal of Technical Education Science, no. 70B (June 28, 2022): 33–47. http://dx.doi.org/10.54644/jte.70b.2022.1154.

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Adsorption kinetics is an essential part in adsorption studies. The pseudo-first-order (PFO) and pseudo-second-order (PSO) models are frequently used to model the experimental dataset of time-dependent adsorption. The differential equations (based on reaction rate and rate law) of the PFO and PSO models are similar to those of chemical reactions (i.e., first and second order-kinetic reactions). The adsorption kinetics is illustrated through the plot of qt (the amount of adsorbate adsorbed by adsorbent at time t) vs. time. This plot includes two important regions (kinetic and equilibrium). The adsorption rate constant (k1(PFO) or k2(PSO), respectively) of the PFO or PSO models needs to be calculated from two regions. The appropriate selection of initial adsorbate concentrations for studying adsorption kinetics should be based on adsorption isotherm to ensure that adsorption sites in adsorbent (material) are highly (nearly fully) covered by adsorbate (solute). Only in this case, the rate constant of the adsorption is accurately obtained.

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Дисертації з теми "Chemical kinetics"

1

Heard, Dwayne Ellis. "Laser studies of chemical kinetics." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.258025.

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2

Kononova, Anna. "Memetic computing in chemical kinetics." Thesis, University of Leeds, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531526.

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3

Biasca, Rodger Joseph. "Chemical kinetics of SCRAMJET propulsion." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/35949.

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4

Justi, Rosa da Silva. "Models of teaching of chemical kinetics." Thesis, University of Reading, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388404.

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5

Chen, Tianjiao S. M. Massachusetts Institute of Technology. "Experimental characterization and chemical kinetics study of chemical looping combustion." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87957.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.
Cataloged from PDF version of thesis. "February 2014."
Includes bibliographical references (pages 106-110).
Chemical looping combustion (CLC) is one of the most promising technologies to achieve carbon capture in fossil fuel power generation plants. A novel rotary-bed reactor concept was proposed by Zhao et. al. [1] in 2013. It is a compact gas fueled CLC reactor that could achieve high fuel conversion and carbon separation efficiencies. It is different from the widely applied and tested fluidized-bed reactor that employs metal oxides coated on particle shaped support materials as the reaction median. In the new reactor, the active metal oxidizes are coated on the surfaces of channel shaped structural material in the new reactor. Due to the different reaction mechanism, an alternative experimental platform with the capability of performing reaction kinetic analysis for disk or channel shaped samples was required needed. The sample selection, characterization and preparation methods are discussed, followed by the introduction of the experimental system design and initial calibration and tuning results. Preliminary oxidation kinetic studies are carried out using the real-time gas analysis system to obtain the concentration contours of the effluent gas species. Commercial 13 wt% copper(II) oxide particles prepared through impregnation method are used as the reaction median. The reactant gas used in the oxidation cycles is 8%, 13% and 21% oxygen in argon, operated at 700 - 800 *C; and 10% hydrogen in argon is used for the reducing cycles.
by Tianjiao Chen.
S.M.

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6

Engblom, Stefan. "Numerical Solution Methods in Stochastic Chemical Kinetics." Doctoral thesis, Uppsala universitet, Avdelningen för teknisk databehandling, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9342.

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This study is concerned with the numerical solution of certain stochastic models of chemical reactions. Such descriptions have been shown to be useful tools when studying biochemical processes inside living cells where classical deterministic rate equations fail to reproduce actual behavior. The main contribution of this thesis lies in its theoretical and practical investigation of different methods for obtaining numerical solutions to such descriptions. In a preliminary study, a simple but often quite effective approach to the moment closure problem is examined. A more advanced program is then developed for obtaining a consistent representation of the high dimensional probability density of the solution. The proposed method gains efficiency by utilizing a rapidly converging representation of certain functions defined over the semi-infinite integer lattice. Another contribution of this study, where the focus instead is on the spatially distributed case, is a suggestion for how to obtain a consistent stochastic reaction-diffusion model over an unstructured grid. Here it is also shown how to efficiently collect samples from the resulting model by making use of a hybrid method. In a final study, a time-parallel stochastic simulation algorithm is suggested and analyzed. Efficiency is here achieved by moving parts of the solution phase into the deterministic regime given that a parallel architecture is available. Necessary background material is developed in three chapters in this summary. An introductory chapter on an accessible level motivates the purpose of considering stochastic models in applied physics. In a second chapter the actual stochastic models considered are developed in a multi-faceted way. Finally, the current state-of-the-art in numerical solution methods is summarized and commented upon.

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7

PAUL, DEBDAS. "Efficient Parameter Inference for Stochastic Chemical Kinetics." Thesis, KTH, Beräkningsbiologi, CB, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-146869.

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Parameter inference for stochastic systems is considered as one of the fundamental classical problems in the domain of computational systems biology. The problem becomes challenging and often analytically intractable with the large number of uncertain parameters. In this scenario, Markov Chain Monte Carlo (MCMC) algorithms have been proved to be highly effective. For a stochastic system, the most accurate description of the kinetics is given by the Chemical Master Equation (CME). Unfortunately, analytical solution of CME is often intractable even for considerably small amount of chemically reacting species due to its super exponential state space complexity. As a solution, Stochastic Simulation Algorithm (SSA) using Monte Carlo approach was introduced to simulate the chemical process defined by the CME. SSA is an exact stochastic method to simulate CME but it also suffers from high time complexity due to simulation of every reaction. Therefore computation of likelihood function (based on exact CME) in MCMC becomes expensive which alternately makes the rejection step expensive. In this generic work, we introduce different approximations of CME as a pre-conditioning step to the full MCMC to make rejection cheaper. The goal is to avoid expensive computation of exact CME as far as possible. We show that, with effective pre-conditioning scheme, one can save a considerable amount of exact CME computations maintaining similar convergence characteristics. Additionally, we investigate three different sampling schemes (dense sampling, longer sampling and i.i.d sampling) under which convergence for MCMC using exact CME for parameter estimation can be analyzed. We find that under i.i.d sampling scheme, better convergence can be achieved than that of dense sampling of the same process or sampling the same process for longer time. We verify our theoretical findings for two different processes: linear birth-death and dimerization.Apart from providing a framework for parameter inference using CME, this work also provides us the reasons behind avoiding CME (in general) as a parameter estimation technique for so long years after its formulation

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8

Tomlin, Alison Sarah. "Bifurcation analysis for non-linear chemical kinetics." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.255345.

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9

Shaw, Rebecca Custis Riehl. "Combining combustion simulations with complex chemical kinetics." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648248.

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10

Poole, Anthony John. "Reaction-diffusion structures in nonlinear chemical kinetics." Thesis, University of Leeds, 1998. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.712528.

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Книги з теми "Chemical kinetics"

1

Ancheyta, Jorge. Chemical Reaction Kinetics. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119226666.

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2

Érdi, Péter, and Gábor Lente. Stochastic Chemical Kinetics. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0387-0.

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3

G, Compton R., ed. Comprehensive chemical kinetics. Amsterdam: Elsevier, 1991.

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4

A, Kotomin E., Kuzovkov V. N, Compton R. G, and Hancock G, eds. Comprehensive chemical kinetics. Amsterdam: Elsevier, 1996.

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5

J, Pilling M., ed. Comprehensive chemical kinetics. Amsterdam: Elsevier, 1997.

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6

B, Marin Guy, ed. Chemical engineering kinetics. Amsterdam: Elsevier/Academic Press, 2007.

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7

H, Mauser, Gauglitz G, Compton R. G, and Hancock G, eds. Comprehensive chemical kinetics. Amsterdam: Elsevier, 1998.

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8

1912-, Bamford C. H., Tipper C. F. H, Compton R. G, and Rice Stephen A, eds. Comprehensive chemical kinetics. Amsterdam: Elsevier, 1985.

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9

G, Compton R., and Hamnett A, eds. Comprehensive chemical kinetics. New York: Elsevier, 1989.

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10

G, Compton R., ed. Comprehensive chemical kinetics. Amsterdam: Elsevier, 1989.

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Частини книг з теми "Chemical kinetics"

1

Bergethon, Peter R., and Kevin Hallock. "Kinetics − Chemical Kinetics." In The Physical Basis of Biochemistry, 97–101. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7364-1_24.

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2

Bergethon, Peter R. "Kinetics: Chemical Kinetics." In The Physical Basis of Biochemistry, 480–97. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2963-4_31.

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3

Bergethon, Peter R. "Kinetics – Chemical Kinetics." In The Physical Basis of Biochemistry, 669–712. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6324-6_25.

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4

Yates, Paul C. "Kinetics." In Chemical Calculations, 149–200. 3rd ed. New York: CRC Press, 2023. http://dx.doi.org/10.1201/9781003043218-5.

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5

Teixeira-Dias, José J. C. "Chemical Kinetics." In Molecular Physical Chemistry, 83–111. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-41093-7_2.

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6

Yon-Kahn, Jeannine, and Guy Hervé. "Chemical Kinetics." In Molecular and Cellular Enzymology, 85–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01228-0_5.

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7

Norman, Richard, and James M. Coxon. "Chemical kinetics." In Principles of Organic Synthesis, 52–70. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2166-8_3.

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Warnatz, Jürgen, Ulrich Maas, and Robert W. Dibble. "Chemical Kinetics." In Combustion, 65–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-98027-5_6.

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9

Dreybrodt, Wolfgang. "Chemical Kinetics." In Processes in Karst Systems, 59–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83352-6_4.

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10

Vogt, Jochen. "Chemical Kinetics." In Exam Survival Guide: Physical Chemistry, 119–45. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49810-2_6.

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Тези доповідей конференцій з теми "Chemical kinetics"

1

Hansen, Nils, Craig Taatjes, Judit Zador, Jacqueline Chen, Habib Najm, Leonid Sheps, David Osborn, and Krupa Ramasesha. "Chemical Kinetics at SNL." In Proposed for presentation at the DOE BES Contractor's Meeting Gas Phase Chemical Physics Program held June 1-3, 2022 in ,. US DOE, 2022. http://dx.doi.org/10.2172/2003528.

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2

Basu, Sumit, Yuan Zheng, and Jay P. Gore. "Chemical Kinetics Parameter Estimation for Ammonia Borane Hydrolysis." In ASME 2008 Heat Transfer Summer Conference collocated with the Fluids Engineering, Energy Sustainability, and 3rd Energy Nanotechnology Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/ht2008-56139.

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Onboard hydrogen storage is an enabling factor in the development of fuel cell powered passenger cars. Ammonia borane (AB) hydrolysis is one of the potential technologies for onboard hydrogen storage. In this study, kinetics of catalyzed ammonia borane hydrolysis using ruthenium-supported-on-carbon has been measured. For reacting flows, chemical kinetics determines the rates of heat generation and species production or consumption in the overall energy and mass balances respectively. Kinetic measurements under isothermal conditions provide critical data for the design of hydrolysis reactors. It is, however, not always possible to eliminate the effects of internal diffusion in a heterogeneous chemical reaction. In such cases, the reaction efficiency (η), which depends on the effective liquid phase diffusivity (Deff) in the catalyst medium, should be determined. Determination of intrinsic kinetic parameters using apparent kinetics data is, thus, a challenge. In this study, the change in AB concentration (CAB) with reaction time (t) has been directly measured. It was observed that the AB hydrolysis reaction had orders between zero and one in a temperature range of 26°C to 55°C. A unified Langmuir-Hinshelwood (LH) model has been adopted to describe the reaction kinetics. The intrinsic kinetic parameters (A, Ea, ΔHads, K0) as well as Deff need to be estimated by inverse analysis of the measured CAB vs t data. Conventionally, kinetic parameters are determined using linear fitting. Sometimes, however, it is impossible to converge to a unique value by using the linear fitting approach as there are several values providing regression coefficients greater than 0.99. In this study, the multiple-variable inverse problem has been solved using a nonlinear fitting algorithm based on Powell’s conjugate-gradient error minimization. This algorithm minimizes errors without using derivatives. As a result, the uncertainties in the kinetic parameter estimation have been significantly reduced by the new approach.

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3

Bedoya, Ivan Dario, Francisco Cadavid, Samveg Saxena, Robert Dibble, Salvador Aceves, and Daniel Flowers. "A Sequential Chemical Kinetics-CFD-Chemical Kinetics Methodology to Predict HCCI Combustion and Main Emissions." In SAE 2012 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2012. http://dx.doi.org/10.4271/2012-01-1119.

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4

Sharma, Alisha J., Ryan F. Johnson, David A. Kessler, and Adam Moses. "Deep Learning for Scalable Chemical Kinetics." In AIAA Scitech 2020 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-0181.

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Tsang, Wing. "Chemical Activation Processes in Combustion Kinetics." In 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-1366.

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YING, SHUH-JING, and HUNG NGUYEN. "Reduced chemical kinetics for propane combustion." In 28th Aerospace Sciences Meeting. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1990. http://dx.doi.org/10.2514/6.1990-546.

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de Souza, Kesiany M., and Marcelo J. S. de Lemos. "ADVANCED CHEMICAL KINETICS OF THERMITE REACTIONS." In 8th Thermal and Fluids Engineering Conference (TFEC). Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/tfec2023.cbf.046112.

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8

Christoudias, Theodoros, Timo Kirfel, Astrid Kerkweg, Domenico Taraborrelli, Georges-Emmanuel Moulard, Erwan Raffin, Victor Azizi, Gijs van den Oord, and Ben van Werkhoven. "GPU Optimizations for Atmospheric Chemical Kinetics." In HPC Asia 2021: The International Conference on High Performance Computing in Asia-Pacific Region. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3432261.3439863.

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9

Dadam, Alessandro P., Sandro R. Levandoski, Geraldo R. de Almeida, Walter Pinheiro, and Simone C. N. Araujo. "Corrosion Chemical Kinetics in Galvanized steels." In 2020 IEEE/PES Transmission and Distribution Conference and Exposition (T&D). IEEE, 2020. http://dx.doi.org/10.1109/td39804.2020.9299917.

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10

Armstrong, Michael, Timothy Rose, Marco Mehl, Joseph Zaug, Jonathan Crowhurst, Harry Radousky, Andrea Fabris, and Mark Cappelli. "Plasma Chemical Kinetics in a Steady Flow." In Laser Applications to Chemical, Security and Environmental Analysis. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/lacsea.2016.lth2i.1.

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Звіти організацій з теми "Chemical kinetics"

1

Rowland, F. S. Research in chemical kinetics. Office of Scientific and Technical Information (OSTI), January 1991. http://dx.doi.org/10.2172/5523915.

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2

Olsen, Mitchell, and Willson. L52248 Investigation of Formaldehyde Chemical Kinetics. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), March 2004. http://dx.doi.org/10.55274/r0011246.

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Анотація:

The program is divided into two parts, which are (1) chemical kinetic modeling and (2) plug flow reactor tests. The chemical kinetic modeling focuses on the development of a model that can accurately predict formaldehyde formation and destruction. The most recent version of Chemkin is utilized with various kinetic mechanisms, including GRI-Mech. Numerous kinetic mechanisms are examined in order to select the most accurate one for predicting formaldehyde formation and destruction. The plug flow reactor tests consist of a series of steady state experimental investigations aimed at characterizing formaldehyde. Formaldehyde concentrations in the reactor are measured with an FTIR.

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3

Kee, R., F. Rupley, and J. Miller. Chemkin-II: A Fortran chemical kinetics package for the analysis of gas-phase chemical kinetics. Office of Scientific and Technical Information (OSTI), September 1989. http://dx.doi.org/10.2172/5681118.

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4

Rowland, F. S. Research in chemical kinetics. Annual report. Office of Scientific and Technical Information (OSTI), December 1986. http://dx.doi.org/10.2172/453455.

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5

Law, Chung K. Chemical Kinetics and Aerodynamics of Ignition. Fort Belvoir, VA: Defense Technical Information Center, December 2004. http://dx.doi.org/10.21236/ada429385.

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6

Kee, R. J., F. M. Rupley, E. Meeks, and J. A. Miller. CHEMKIN-III: A FORTRAN chemical kinetics package for the analysis of gas-phase chemical and plasma kinetics. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/481621.

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7

Rowland, F. S. Research in chemical kinetics. Annual report, 1993. Office of Scientific and Technical Information (OSTI), December 1993. http://dx.doi.org/10.2172/656622.

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8

Rowland, F. S. Research in chemical kinetics. Annual report, 1994. Office of Scientific and Technical Information (OSTI), December 1994. http://dx.doi.org/10.2172/656623.

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9

Kashyap, Nabil. Aerospace Engineering / Chemical Kinetics - University of Michigan. Purdue University Libraries, March 2012. http://dx.doi.org/10.5703/1288284314989.

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10

Sardeshmukh, Swanand V., William E. Anderson lMatthew E., and Venkateswaran Sankaran. Prediction of Combustion Instability with Detailed Chemical Kinetics. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada613690.

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