Статті в журналах: "Chemical kinetic modeling"

1

Suleymanov, Yury. "Advancing chemical kinetic modeling." Science 372, no. 6537 (April 1, 2021): 44.2–44. http://dx.doi.org/10.1126/science.372.6537.44-b.

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2

Pitz, W. J., C. K. Westbrook, O. Herbinet, and E. J. Silke. "KS-2: Progress in Chemical Kinetic Modeling for Surrogate Fuels(Keynote Papers)." Proceedings of the International symposium on diagnostics and modeling of combustion in internal combustion engines 2008.7 (2008): 9–15. http://dx.doi.org/10.1299/jmsesdm.2008.7.9.

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3

Boukhalfa, Nora. "Chemical Kinetic Modeling of Methane Combustion." Procedia Engineering 148 (2016): 1130–36. http://dx.doi.org/10.1016/j.proeng.2016.06.561.

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4

ERTEKİN, Özlem. "Example of A Kinetic Mathematical Modeling in Food Engineering." ITM Web of Conferences 22 (2018): 01029. http://dx.doi.org/10.1051/itmconf/20182201029.

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Mathematical modeling of biochemical, chemical reaction processes facilitates understanding. The kinetics of these reaction processes can be analyzed mathematically and kinetics are presented as systems of differential equations. Mathematical model of a reaction kinetic is studied in this study. Bernoulli-Sub equation function method is used in this study. This example can be new model for food engineering applications.

5

Martínez, Haydee, Joaquín Sánchez, José-Manuel Cruz, Guadalupe Ayala, Marco Rivera, and Thomas Buhse. "Modeling of Scale-Dependent Bacterial Growth by Chemical Kinetics Approach." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/820959.

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We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V) of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenicE. coli,E. coli JM83, andSalmonella typhimuriumon one hand andVibrio choleraeon the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.

6

Edeleva, Mariya, Paul H. M. Van Steenberge, Maarten K. Sabbe, and Dagmar R. D’hooge. "Connecting Gas-Phase Computational Chemistry to Condensed Phase Kinetic Modeling: The State-of-the-Art." Polymers 13, no. 18 (September 7, 2021): 3027. http://dx.doi.org/10.3390/polym13183027.

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In recent decades, quantum chemical calculations (QCC) have increased in accuracy, not only providing the ranking of chemical reactivities and energy barriers (e.g., for optimal selectivities) but also delivering more reliable equilibrium and (intrinsic/chemical) rate coefficients. This increased reliability of kinetic parameters is relevant to support the predictive character of kinetic modeling studies that are addressing actual concentration changes during chemical processes, taking into account competitive reactions and mixing heterogeneities. In the present contribution, guidelines are formulated on how to bridge the fields of computational chemistry and chemical kinetics. It is explained how condensed phase systems can be described based on conventional gas phase computational chemistry calculations. Case studies are included on polymerization kinetics, considering free and controlled radical polymerization, ionic polymerization, and polymer degradation. It is also illustrated how QCC can be directly linked to material properties.

7

Escanciano, Itziar A., Mateusz Wojtusik, Jesús Esteban, Miguel Ladero, and Victoria E. Santos. "Modeling the Succinic Acid Bioprocess: A Review." Fermentation 8, no. 8 (July 31, 2022): 368. http://dx.doi.org/10.3390/fermentation8080368.

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Succinic acid has attracted much interest as a key platform chemical that can be obtained in high titers from biomass through sustainable fermentation processes, thus boosting the bioeconomy as a critical production strategy for the future. After several years of development of the production of succinic acid, many studies on lab or pilot scale production have been reported. The relevant experimental data reveal underlying physical and chemical dynamic phenomena. To take advantage of this vast, but disperse, kinetic information, a number of mathematical kinetic models of the unstructured non-segregated type have been proposed in the first place. These relatively simple models feature critical aspects of interest for the design, control, optimization and operation of this key bioprocess. This review includes a detailed description of the phenomena involved in the bioprocesses and how they reflect on the most important and recent models based on macroscopic and metabolic chemical kinetics, and in some cases even coupling mass transport.

8

Westbrook, Charles K. "Chemical kinetic modeling of higher hydrocarbon fuels." AIAA Journal 24, no. 12 (December 1986): 2002–9. http://dx.doi.org/10.2514/3.9559.

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Silke, Emma J., William J. Pitz, Charles K. Westbrook, and Marc Ribaucour. "Detailed Chemical Kinetic Modeling of Cyclohexane Oxidation†." Journal of Physical Chemistry A 111, no. 19 (May 2007): 3761–75. http://dx.doi.org/10.1021/jp067592d.

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Lai, Jason Y. W., Kuang C. Lin, and Angela Violi. "Biodiesel combustion: Advances in chemical kinetic modeling." Progress in Energy and Combustion Science 37, no. 1 (February 2011): 1–14. http://dx.doi.org/10.1016/j.pecs.2010.03.001.

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Wu, Kuo-Chun, Simone Hochgreb, and Michael G. Norris. "Chemical kinetic modeling of exhaust hydrocarbon oxidation." Combustion and Flame 100, no. 1-2 (January 1995): 193–201. http://dx.doi.org/10.1016/0010-2180(94)00078-7.

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12

Freund, H., and W. N. Olmstead. "Detailed chemical kinetic modeling of butylbenzene pyrolysis." International Journal of Chemical Kinetics 21, no. 7 (July 1989): 561–74. http://dx.doi.org/10.1002/kin.550210707.

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13

Louca, Stilianos, Mary I. Scranton, Gordon T. Taylor, Yrene M. Astor, Sean A. Crowe, and Michael Doebeli. "Circumventing kinetics in biogeochemical modeling." Proceedings of the National Academy of Sciences 116, no. 23 (May 16, 2019): 11329–38. http://dx.doi.org/10.1073/pnas.1819883116.

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Microbial metabolism drives biogeochemical fluxes in virtually every ecosystem. Modeling these fluxes is challenged by the incredible diversity of microorganisms, whose kinetic parameters are largely unknown. In poorly mixed systems, such as stagnant water columns or sediments, however, long-term bulk microbial metabolism may become limited by physical transport rates of substrates across space. Here we mathematically show that under these conditions, biogeochemical fluxes are largely predictable based on the system’s transport properties, chemical boundary conditions, and the stoichiometry of metabolic pathways, regardless of the precise kinetics of the resident microorganisms. We formalize these considerations into a predictive modeling framework and demonstrate its use for the Cariaco Basin subeuphotic zone, one of the largest anoxic marine basins worldwide. Using chemical concentration data solely from the upper boundary (depth 180 m) and lower boundary (depth 900 m), but without a priori knowledge of metabolite fluxes, chemical depth profiles, kinetic parameters, or microbial species composition, we predict the concentrations and vertical fluxes of biologically important substances, including oxygen, nitrate, hydrogen sulfide, and ammonium, across the entire considered depth range (180–900 m). Our predictions largely agree with concentration measurements over a period of 14 years (R2= 0.78–0.92) and become particularly accurate during a period where the system was near biogeochemical steady state (years 2007–2009,R2= 0.86–0.95). Our work enables geobiological predictions for a large class of ecosystems without knowledge of kinetic parameters or geochemical depth profiles. Conceptually, our work provides a possible explanation for the decoupling between microbial species composition and bulk metabolic function, observed in various ecosystems.

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Ruiz-Gutiérrez, Gema, Araceli Rodríguez-Romero, Antonio Tovar-Sánchez, and Javier R. Viguri Fuente. "Analysis and Modeling of Sunscreen Ingredients’ Behavior in an Aquatic Environment." Oceans 3, no. 3 (August 2, 2022): 340–63. http://dx.doi.org/10.3390/oceans3030024.

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Sunscreens have become a product based on increasingly complex formulations that include, among many ingredients, a mixture of UV filters to provide optimal sun ultraviolet radiation protection. A significant group of scientific works deals with the impact of UV filters in aquatic media. However, the knowledge of the mechanism and kinetics of the compound’s direct release, fate, and its transformation and interaction with living organisms is necessary to assess its environmental occurrence and behavior and to predict potential and real impacts on the aquatic environment. This review outlines the existing analysis and modeling of the release and behavior of sunscreen’s ingredients in the marine environment, including aquatic organisms. The physical-chemical properties, photodegradation, and release kinetics of particles and chemicals into the water are studied by hydrodynamic and kinetic models. Direct photolysis of chemicals is modeled as pseudo-first-order kinetics, while the indirect pathway by the reaction of sunscreen with reactive oxygen species is described as second-order kinetics. The interaction of UV filters with marine biota is studied mainly by toxicokinetic models, which predict their bio-accumulation in the organisms’ tissues. These models consider the chemicals’ uptake and excretion, as well as their transfer between different internal animal organs, as a first-order kinetic process. The studies analyzed in the present work represent a driver of change for the beauty and personal care industry, in order to seek new ecological alternatives through the application of R&D tactics.

15

Beschkov, V., T. Sapundzhiev, K. Petrov, and E. Vasileva. "Mathematical Modeling for Studying Microbial Processes – Some Examples." Serdica Journal of Computing 4, no. 1 (March 31, 2010): 19–28. http://dx.doi.org/10.55630/sjc.2010.4.19-28.

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Mathematical modeling may have different purposes in chemical and biochemical engineering sciences. One of them is to confirm or to reject kinetic models for certain processes, or to evaluate the importance of some transport phenomena on the net chemical or biochemical reaction rate. In the present paper different microbial processes are considered and modeled for evaluation of kinetic constants for batch and continuous processes accomplished by free and immobilized microbial cells. The practical examples are from the field of wastewater treatment and biosynthesis of products, like enzymes, lactic acid, gluconic acid, etc. By the aid of mathematical modeling the kinetics and the type of inhibition are specified for microbial wastewater denitrification and biodegradation of halogenated hydrocarbons. The importance of free and immobilized cells and their separate contribution to the overall microbial process is also evaluated for some fermentation processes: gluconic acid production, dichloroethane biodegradation, lactic acid fermentation and monochloroacetic acid biodegradation.

16

Rasane, Prasad, Alok Jha, Sawinder Kaur, Vikas Kumar, and Nitya Sharma. "Chemical Kinetic Modeling of Nutricereal based Fermented Baby Food for Shelf Life Prediction." Current Nutrition & Food Science 15, no. 4 (June 28, 2019): 384–93. http://dx.doi.org/10.2174/1573401314666171226151852.

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Background: A nutricereal based fermented baby food was investigated to predict its shelf life using chemical kinetic modeling. An optimized baby food formulation, packaged in metalized polyester packets was stored at accelerated conditions for 180 days and analyzed for Hydroxy Methyl Furfural (HMF), Thiobarbituric Value (TBA), Free Fatty Acid Content (FFA) and sensory characteristics. Objective: The objective of the study was to determine the shelf life of the optimized nutricereal based fermented baby food using chemical kinetic modeling. Methods: Chemical kinetics analysis by investigating the Hydroxymethyl Furfural content, thiobarbituric value (TBA), free fatty acid content (FFA) and sensory characteristics of the optimized baby food. Results: Shelf life model based on chemical and sensory acceptability was derived using Arrhenius equation modeling. Thus, the baby food had a predictive shelf life of 54 weeks when stored at 10°C in metalized polyester based on the chemical (HMF, TBA and FFA) and sensory (overall acceptability) characteristics. A most suitable model based on FFA was developed considering lowest root mean square (RMS) percentages and least deviations in actual and predicted values. Conclusion: Chemcial kinetics could be applied to determine the shelf life of the fermented baby foods. HMF, TBA and FFA play key role in the shelf life of the stored fermented product. A model based on FFA is most suitable to determine the shelf life of the powdered nutricereal based fermented baby food packged in metalized polyster, stored at 10°C.

17

Shenvi, Neil, J. M. Geremia, and Herschel Rabitz. "Efficient chemical kinetic modeling through neural network maps." Journal of Chemical Physics 120, no. 21 (June 2004): 9942–51. http://dx.doi.org/10.1063/1.1718305.

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18

Jin, Hanfeng, Lili Xing, Junyu Hao, Jiuzhong Yang, Yan Zhang, ChuangChuang Cao, Yang Pan, and Aamir Farooq. "A chemical kinetic modeling study of indene pyrolysis." Combustion and Flame 206 (August 2019): 1–20. http://dx.doi.org/10.1016/j.combustflame.2019.04.040.

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ZHANG, Sicong, Wei CHENG, Chengzhi WANG, and Huijun LI. "Computer-aided Chemical Kinetic Modeling in Near Space." Chinese Journal of Space Science 42, no. 1 (2022): 91. http://dx.doi.org/10.11728/cjss2022.01.201019094.

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20

Pandey, D. K., and S. Biswas. "Analysis of the Experimental Data of Acid Hydrolysis in Micelle Assemblies Using Kinetic Model." International Journal of ChemTech Research 13, no. 3 (2020): 195–202. http://dx.doi.org/10.20902/ijctr.2019.130316.

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Acid Hydrolysis of carboxylate ester with hydroxamate ions in micellar media has been discussed in our last research works. In this paper, we used all the obtained kinetic experimental data for correlation and explanation by modeling techniques. We know the different types of modeling techniques available and used in the current times. Michael menten one site total binding constant and one site fite Ki models apply for the explanation of kinetics data. The models were given a good explanation and correlation of these types of kinetic data.

21

Wu, Jun-Lin, Zhi-Hui Li, Ao-Ping Peng, Xing-Cai Pi, and Xin-Yu Jiang. "Utility computable modeling of a Boltzmann model equation for bimolecular chemical reactions and numerical application." Physics of Fluids 34, no. 4 (April 2022): 046111. http://dx.doi.org/10.1063/5.0088440.

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A Boltzmann model equation (kinetic model) involving the chemical reaction of a multicomponent gaseous mixture is derived based on Groppi's work [“A Bhatnagar–Gross–Krook-type approach for chemically reacting gas mixtures,” Phys. Fluids 16, 4273 (2004)], in which the relaxation parameters of elastic collision frequency for rigid elastic spheres are obtained based on the collision term, and the pivotal collision frequency of the chemical reaction is deduced from the chemical reaction rate that is determined by the direct simulation Monte Carlo (DSMC) method. This kinetic model is shown to be conservative, and the H theorem for an endothermic reaction is proven. In the framework of the gas-kinetic unified algorithm, the discrete velocity method, finite volume method, and implicit scheme are applied to solve the proposed kinetic model by introducing a suitable boundary condition at the wall surface. For hypersonic flows around a cylinder, the proposed kinetic model and the corresponding numerical methods are verified for both endothermic and exothermic reactions by comparison of the model's results with results from the DSMC method. The different influences of endothermic and exothermic reactions are also given. Finally, the proposed kinetic model is also used to simulate an exothermic reaction-driven flow in a square cavity.

22

Avramovic, Jelena, Olivera Stamenkovic, Zoran Todorovic, Miodrag Lazic, and Vlada Veljkovic. "Empirical modeling the ultrasound-assisted base-catalyzed sunflower oil methanolysis kinetics." Chemical Industry and Chemical Engineering Quarterly 18, no. 1 (2012): 115–27. http://dx.doi.org/10.2298/ciceq110705053a.

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The ultrasound-assisted sunflower oil methanolysis catalyzed by KOH was studied to define a simple empirical kinetic model useful for reactor design without complex computation. It was assumed that the neutralization of free fatty acids and the saponification reaction were negligible. The methanolysis process rate was observed to be controlled by the mass transfer limitation in the initial heterogeneous regime and by the chemical reaction in the later pseudo-homogeneous regime. The model involving the irreversible second-order kinetics was established and used for simulation of the triacylglycerol conversion and the fatty acid methyl esters formation in the latter regime. A good agreement between the proposed model and the experimental data in the chemically controlled regime was found.

23

Li, Kuijun, Priyadarshi Mahapatra, K. Sham Bhat, David C. Miller, and David S. Mebane. "Multi-scale modeling of an amine sorbent fluidized bed adsorber with dynamic discrepancy reduced modeling." Reaction Chemistry & Engineering 2, no. 4 (2017): 550–60. http://dx.doi.org/10.1039/c7re00040e.

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24

Koss, Abigail R., Manjula R. Canagaratna, Alexander Zaytsev, Jordan E. Krechmer, Martin Breitenlechner, Kevin J. Nihill, Christopher Y. Lim, et al. "Dimensionality-reduction techniques for complex mass spectrometric datasets: application to laboratory atmospheric organic oxidation experiments." Atmospheric Chemistry and Physics 20, no. 2 (January 27, 2020): 1021–41. http://dx.doi.org/10.5194/acp-20-1021-2020.

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Abstract. Oxidation of organic compounds in the atmosphere produces an immensely complex mixture of product species, posing a challenge for both their measurement in laboratory studies and their inclusion in air quality and climate models. Mass spectrometry techniques can measure thousands of these species, giving insight into these chemical processes, but the datasets themselves are highly complex. Data reduction techniques that group compounds in a chemically and kinetically meaningful way provide a route to simplify the chemistry of these systems but have not been systematically investigated. Here we evaluate three approaches to reducing the dimensionality of oxidation systems measured in an environmental chamber: positive matrix factorization (PMF), hierarchical clustering analysis (HCA), and a parameterization to describe kinetics in terms of multigenerational chemistry (gamma kinetics parameterization, GKP). The evaluation is implemented by means of two datasets: synthetic data consisting of a three-generation oxidation system with known rate constants, generation numbers, and chemical pathways; and the measured products of OH-initiated oxidation of a substituted aromatic compound in a chamber experiment. We find that PMF accounts for changes in the average composition of all products during specific periods of time but does not sort compounds into generations or by another reproducible chemical process. HCA, on the other hand, can identify major groups of ions and patterns of behavior and maintains bulk chemical properties like carbon oxidation state that can be useful for modeling. The continuum of kinetic behavior observed in a typical chamber experiment can be parameterized by fitting species' time traces to the GKP, which approximates the chemistry as a linear, first-order kinetic system. The fitted parameters for each species are the number of reaction steps with OH needed to produce the species (the generation) and an effective kinetic rate constant that describes the formation and loss rates of the species. The thousands of species detected in a typical laboratory chamber experiment can be organized into a much smaller number (10–30) of groups, each of which has a characteristic chemical composition and kinetic behavior. This quantitative relationship between chemical and kinetic characteristics, and the significant reduction in the complexity of the system, provides an approach to understanding broad patterns of behavior in oxidation systems and could be exploited for mechanism development and atmospheric chemistry modeling.

25

Oo, Chit Wityi, Masahiro Shioji, Hiroshi Kawanabe, Susan A. Roces, and Nathaniel P. Dugos. "A Skeletal Kinetic Model For Biodiesel Fuels Surrogate Blend Under Diesel-Engine Conditions." ASEAN Journal of Chemical Engineering 15, no. 1 (October 1, 2015): 52. http://dx.doi.org/10.22146/ajche.49693.

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The biodiesel surrogate fuels are realistic kinetic tools to study the combustion of actual biodiesel fuels in diesel engines. The knowledge of fuel chemistry aids in the development of combustion modeling. In order to numerically simulate the diesel combustion, it is necessary to construct a compact reaction model for describing the chemical reaction. This study developed a skeletal kinetic model of methyl decanoate (MD) and n-heptane as a biodiesel surrogate blend for the chemical combustion reactions. The skeletal kinetic model is simply composed of 45 chemical species and 74 reactions based on the full kinetic models which have been developed by Lawrance Livermore National Laboratory (LLNL) and Knowledge-basing Utilities for Complex Reaction Systems (KUCRS) under the diesel like engine conditions. The model in this study is generated by using CHEMKIN and then it is used to produce the ignition delay data and the related chemical species. The model predicted good reasonable agreement for the ignition delays and most of the reaction products at various conditions. The chemical species are well reproduced by this skeletal kinetic model while the good temperature dependency is found under constant pressure conditions 2MPa and 4MPa. The ignition delay time of present model is slightly shorter than the full kinetic model near negative temperature coefficient (NTC) regime. This skeletal model can provide the chemical kinetics to apply in the simulation codes for diesel-engine combustion.

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Miyoshi, Akira. "OS3-1 KUCRS - Detailed Kinetic Mechanism Generator for Versatile Fuel Components and Mixtures(OS3 Application of chemical kinetics to combustion modeling,Organized Session Papers)." Proceedings of the International symposium on diagnostics and modeling of combustion in internal combustion engines 2012.8 (2012): 116–21. http://dx.doi.org/10.1299/jmsesdm.2012.8.116.

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27

Kutlugil’dina, Galiya G. "Kinetic scheme of apple pectin oxidative transformations under the action of the ozone-oxygen mixture." Butlerov Communications 61, no. 2 (February 29, 2020): 79–89. http://dx.doi.org/10.37952/roi-jbc-01/20-61-2-79.

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Mathematical modeling of apple pectin oxidative transformations (AP) under the action of the ozone-oxygen mixture in aqueous solutions (the reaction system "AP + O3 + O2 + H2O") has been carried out. The kinetic scheme of the oxidation process was compiled basing on the well-known ideas of liquid-phase oxidation mechanisms of organic compounds (taking into account the currently known experimental results on AP oxidation). Using the "KhimKinOptima" software package for the proposed scheme, the inverse and direct chemical kinetics problems were solved. The well-known literature data on the rate constants of elementary stages were used. The rate constants of the oxidation key stages have been determined after solving the chemical kinetics inverse problem with the index method of the observed and calculated kinetic data global optimization. It turned out that the rate constants of the individual stages obtained by calculation are in good agreement with the values of the rate constants taken from literary sources. The chemical kinetics direct problem has been solved with the found rate constants and allowed obtaining kinetic curves of all participants in the apple pectin ozonized oxidation. It was found that the kinetic curve of the accumulation of carboxyl groups, obtained experimentally, completely coincided with the theoretical dependence. It has been also shown that the proposed apple pectin oxidative conversion scheme in the "AP + O3 + O2 + H2O" reaction system allows one to explain all the currently available experimental results. The apple pectin ozonized oxidation under another initiator (Н2О2 + FeSO4) has been studied to confirm the kinetic scheme. To do this, 3 new stages has been introduced into the scheme proposed, characterizing the catalytic decomposition of hydrogen peroxide under a transition metal (Fe2+). By solving the chemical kinetics direct problem, the accumulation kinetic curves of the final reaction products were obtained. It has been found that the carboxyl groups accumulation kinetics in the reaction system "AP + O3 + O2 + H2O2 + FeSO4 + H2O" after the supplementary experiment coincided with the theoretical kinetic curve. Thereby, the accuracy of the apple pectin proposed oxidative conversion scheme is confirmed.

28

Gaïl, Sandro, Philippe Dagaut, Gráinne Black, and John M. Simmie. "Kinetics of 1,2-Dimethylbenzene Oxidation and Ignition: Experimental and Detailed Chemical Kinetic Modeling." Combustion Science and Technology 180, no. 10-11 (September 16, 2008): 1748–71. http://dx.doi.org/10.1080/00102200802258270.

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29

Abedi, Shiva, Aligholi Niaei, Najaf Namjou, Darioush Salari, Ali Tarjomannejad, and Behrang Izadkhah. "Experimental and Modeling Study of CO-Selective Catalytic Reduction of NO Over Perovskite-Type Nanocatalysts." Periodica Polytechnica Chemical Engineering 64, no. 1 (May 15, 2019): 46–53. http://dx.doi.org/10.3311/ppch.13767.

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In this work LaFeO3, LaFe0.7Mn0.3O3 and LaMn0.7Fe0.3O3 nanocatalysts with perovskite structures have been synthesized by sol-gel method. The selective catalytic reduction of NO with CO (CO-SCR) using synthesized nanocatalysts was investigated in a plug flow reactor. The kinetics of CO-SCR process was studied and three kinetic models were used to describe the behavior of the system, including power low model (PLM), kinetic model 1 (KM1) and kinetic model 2 (KM2). The KM1 was the best model with correlation coefficients of 0.9924, 0.9911 and 0.9902 and the sum of squared errors of 0.0504, 0.0488 and 0.0397, for LaFeO3, LaFe0.7Mn0.3O3 and LaFe0.3Mn0.7O3 catalysts, respectively. By comparing experimental results with the predicted results of the KM1, it was found that the proposed model can predict the performance of catalysts in the CO-SCR process with considerable precision. The structure and morphology of perovskite-type oxides were characterized by means of X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively.

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Ghobadi Nejad, Zahra, Soheila Yaghmaei, Nazanin Moghadam, and Bahareh Sadeghein. "Some Investigations on Protease Enzyme Production Kinetics UsingBacillus licheniformisBBRC 100053 and Effects of Inhibitors on Protease Activity." International Journal of Chemical Engineering 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/394860.

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Due to great commercial application of protease, it is necessary to study kinetic characterization of this enzyme in order to improve design of enzymatic reactors. In this study, mathematical modeling of protease enzyme production kinetics which is derived fromBacillus licheniformisBBRC 100053 was studied (at 37°C, pH 10 after 73 h in stationary phase, and 150 rpm). The aim of the present paper was to determine the best kinetic model and kinetic parameters for production of protease and calculatingKi(inhibition constant) of different inhibitors to find the most effective one. The kinetic parametersKm(Michaelis-Menten constant) andVm(maximum rate) were calculated 0.626 mM and 0.0523 mM/min. According to the experimental results, using DFP (diisopropyl fluorophosphate) and PMSF (phenylmethanesulfonyl fluoride) as inhibitors almost 50% of the enzyme activity could be inhibited when their concentrations were 0.525 and 0.541 mM, respectively.Kifor DFP and PMSF were 0.46 and 0.56 mM, respectively. Kinetic analysis showed that the Lineweaver-Burk model was the best fitting model for protease production kinetics DFP was more effective than PMSF and both of them should be covered in the group of noncompetitive inhibitors.

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Dubnikova, Faina, and Assa Lifshitz. "Isomerization of Indole. Quantum Chemical Calculations and Kinetic Modeling." Journal of Physical Chemistry A 105, no. 14 (April 2001): 3605–14. http://dx.doi.org/10.1021/jp004038+.

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Dubnikova, Faina, and Assa Lifshitz. "Isomerization of Pyrrole. Quantum Chemical Calculations and Kinetic Modeling." Journal of Physical Chemistry A 102, no. 52 (December 1998): 10880–88. http://dx.doi.org/10.1021/jp983251r.

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Slavinskaya, N. A., U. Riedel, V. E. Messerle, and A. B. Ustimenko. "Chemical Kinetic Modeling in Coal Gasification Processes: an Overview." Eurasian Chemico-Technological Journal 15, no. 1 (December 24, 2012): 1. http://dx.doi.org/10.18321/ectj134.

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<p>Coal is the fuel most able to cover world deficiencies in oil and natural gas. This motivates the development of new and more effective technologies for coal conversion into other fuels. Such technologies are focused on coal gasification with production of syngas or gaseous hydrocarbon fuels, as well as on direct coal liquefaction with production of liquid fuels. The benefits of plasma application in these technologies is based on the high selectivity of the plasma chemical processes, the high efficiency of conversion of different types of coal including those of low quality, relative simplicity of the process control, and significant reduction in the production of ashes, sulphur, and nitrogen oxides. In the coal gasifier, two-phase turbulent flow is coupled with heating and evaporation of coal particles, devolatilization of volatile material, the char combustion (heterogeneous/porous oxidation) or gasification, the gas phase reaction/oxidation (homogeneous oxidation) of gaseous products from coal particles. The present work reviews literature data concerning reaction kinetic modelling in coal gasification. Current state of related kinetic models for heterogeneous/homogeneous oxidation of coal particles, included plasma assisted, is reviewed.</p>

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Metcalfe, W. K., S. Dooley, and F. L. Dryer. "Comprehensive Detailed Chemical Kinetic Modeling Study of Toluene Oxidation." Energy & Fuels 25, no. 11 (November 17, 2011): 4915–36. http://dx.doi.org/10.1021/ef200900q.

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CATHONNET, M. "Chemical Kinetic Modeling of Combustion from 1969 to 2019." Combustion Science and Technology 98, no. 4-6 (July 1994): 265–79. http://dx.doi.org/10.1080/00102209408935412.

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Benjamin, Kenneth M., and Phillip E. Savage. "Detailed Chemical Kinetic Modeling of Methylamine in Supercritical Water." Industrial & Engineering Chemistry Research 44, no. 26 (December 2005): 9785–93. http://dx.doi.org/10.1021/ie050926l.

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Atangana, Ernestine. "New insight kinetic modeling: Models above classical chemical mechanic." Chaos, Solitons & Fractals 128 (November 2019): 16–24. http://dx.doi.org/10.1016/j.chaos.2019.07.013.

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Andrae, J. C. G. "Comprehensive chemical kinetic modeling of toluene reference fuels oxidation." Fuel 107 (May 2013): 740–48. http://dx.doi.org/10.1016/j.fuel.2013.01.070.

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Smith, C. Michael, and Philipp E. Savage. "Reactions of polycyclic alkylaromatics—VI. Detailed chemical kinetic modeling." Chemical Engineering Science 49, no. 2 (1994): 259–70. http://dx.doi.org/10.1016/0009-2509(94)80043-x.

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Berkemeier, Thomas, Matteo Krüger, Aryeh Feinberg, Marcel Müller, Ulrich Pöschl, and Ulrich K. Krieger. "Accelerating models for multiphase chemical kinetics through machine learning with polynomial chaos expansion and neural networks." Geoscientific Model Development 16, no. 7 (April 14, 2023): 2037–54. http://dx.doi.org/10.5194/gmd-16-2037-2023.

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Abstract. The heterogeneous chemistry of atmospheric aerosols involves multiphase chemical kinetics that can be described by kinetic multi-layer models (KMs) that explicitly resolve mass transport and chemical reactions. However, KMs are computationally too expensive to be used as sub-modules in large-scale atmospheric models, and the computational costs also limit their utility in inverse-modeling approaches commonly used to infer aerosol kinetic parameters from laboratory studies. In this study, we show how machine learning methods can generate inexpensive surrogate models for the kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB) to predict reaction times in multiphase chemical systems. We apply and compare two common and openly available methods for the generation of surrogate models, polynomial chaos expansion (PCE) with UQLab and neural networks (NNs) through the Python package Keras. We show that the PCE method is well suited to determining global sensitivity indices of the KMs, and we demonstrate how inverse-modeling applications can be enabled or accelerated with NN-suggested sampling. These qualities make them suitable supporting tools for laboratory work in the interpretation of data and the design of future experiments. Overall, the KM surrogate models investigated in this study are fast, accurate, and robust, which suggests their applicability as sub-modules in large-scale atmospheric models.

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Palmisano, Giovanni, Vittorio Loddo, and Vincenzo Augugliaro. "Two-Dimensional Modeling of an Externally Irradiated Slurry Photoreactor." International Journal of Chemical Reactor Engineering 11, no. 2 (June 25, 2013): 675–85. http://dx.doi.org/10.1515/ijcre-2012-0049.

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Abstract A batch cylindrical photocatalytic reactor, externally irradiated by 1–6 UV fluorescent lamps and containing a stirred slurry of polycrystalline TiO2, was modeled by coupling a modified Langmuir–Hinshelwood kinetics together with a two-dimensional light intensity field. The radiation field has been determined on the main assumptions of diffuse radiation, isotropic scattering and negligible backward reflected photon flow. The model has been applied to the photocatalytic oxidation of organic substrates which do not undergo homogeneous photochemical degradation. The model is characterized by the following four parameters: the kinetic constants of substrate adsorption, desorption and degradation and the exponent of the power law expressing the kinetics dependence on the light intensity. The model constants may be determined by applying a simple least-squares best fitting procedure.

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Simu, Sebastian, Adriana Ledeţi, Elena-Alina Moacă, Cornelia Păcurariu, Cristina Dehelean, Dan Navolan, and Ionuţ Ledeţi. "Thermal Degradation Process of Ethinylestradiol—Kinetic Study." Processes 10, no. 8 (August 2, 2022): 1518. http://dx.doi.org/10.3390/pr10081518.

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The present study reports the results obtained after the analysis of the thermal stability and decomposition kinetics of widely used synthetic derivative of estradiol, ethinylestradiol (EE), as a pure active pharmaceutical ingredient. As investigational tools, Fourier transformed infrared spectroscopy (FTIR), thermal analysis, and decomposition kinetics modeling of EE were employed. The kinetic study was realized using three kinetic methods, namely Kissinger, Friedman, and Flynn-Wall-Ozawa. The results of the kinetic study are in good agreement, suggesting that the main decomposition process of EE that takes place in the 175–375 °C temperature range is a single-step process, invariable during the modification of heating rate of the sample.

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Menshutina, Natalia V., Igor V. Lebedev, Evgeniy A. Lebedev, Ratmir R. Dashkin, Mikhail V. Shishanov, and Maxim L. Burdeyniy. "STUDY AND MODELING 4,4'-DIAMINODIPHENYLMETHANE SYNTHESIS." IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENII KHIMIYA KHIMICHESKAYA TEKHNOLOGIYA 64, no. 4 (April 11, 2021): 100–103. http://dx.doi.org/10.6060/ivkkt.20216404.6314.

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The presented work is devoted to reactions of obtaining 4,4´-diaminodiphenylmethane in the presence of a catalyst. The work describes the importance of studying 4,4´-diaminodiphenylmethane obtaining process and possibility of cellular automata approach in modelling chemical reactions. Cellular automata model which allows to predict the kinetic curves of the studied 4,4´-diaminodiphenylmethane-obtaining reaction. Model reflects two processes that are observed in the system under study - the movement of reagents under the stirring and the reaction in the presence of a catalyst. The suggested model does not use complex calculations for operation and can be implemented using high-performance parallel computing, which will speed up calculations and reduce the requirements for computing resources. The developed model was used to carry out computational experiments under various conditions. Since the model contains a number of empirical parameters, first computational experiments were carried out, which made it possible to establish the relationship between the model parameters and real values. Then, computational experiments were carried out to predict the kinetic curves of the studied reactions and were compared with the corresponding experimental data. The suggested model is suitable for predicting 4,4´-diaminodiphenylmethane-obtaining reaction kinetics. Also, model can be the part of complex multiscale modeling from the molecule level to the level of the entire apparatus.

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Niu, Qigui, Shilong He, Yanlong Zhang, Yu Zhang, Min Yang, and Yu-You Li. "Bio-kinetics evaluation and batch modeling of the anammox mixed culture in UASB and EGSB reactors: batch performance comparison and kinetic model assessment." RSC Advances 6, no. 5 (2016): 3487–500. http://dx.doi.org/10.1039/c5ra14648h.

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To predict the process performance and evaluate the MSAA of anammox biomass, a number of kinetic models were conducted both for UASB-anammox biomass and EGSB-anammox. All of the kinetics simulation resluts were compared to assess the kinetic models.

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Simon, Cory M. "The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics." PeerJ Physical Chemistry 2 (September 18, 2020): e14. http://dx.doi.org/10.7717/peerj-pchem.14.

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Mathematical models of the dynamics of infectious disease transmission are used to forecast epidemics and assess mitigation strategies. In this article, we highlight the analogy between the dynamics of disease transmission and chemical reaction kinetics while providing an exposition on the classic Susceptible–Infectious–Removed (SIR) epidemic model. Particularly, the SIR model resembles a dynamic model of a batch reactor carrying out an autocatalytic reaction with catalyst deactivation. This analogy between disease transmission and chemical reaction enables the exchange of ideas between epidemic and chemical kinetic modeling communities.

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Obradovic, Bojana. "Guidelines for general adsorption kinetics modeling." Chemical Industry 74, no. 1 (2020): 65–70. http://dx.doi.org/10.2298/hemind200201006o.

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Adsorption processes are widely used in different technological areas and industry sectors, thus continuously attracting attention in the scientific research and publications. Design and scale-up of these processes are essentially based on the knowledge and understanding of the adsorption kinetics and mechanism. Adsorption kinetics is usually modeled by using several well-known models including the pseudo-first and pseudo-second order models, the Elovich equation, and the intra-particle diffusion based models. However, in the scientific literature there are a significant number of cases with the inappropriate use of these models, utilization of erroneous expressions, and incorrect interpretation of the obtained results. This paper is especially focused on applications of the pseudo-second order, intra-particle diffusion and the Weber-Morris models, which are illustrated with typical examples. Finally, general recommendations for selection of the appropriate kinetic model and model assumptions, data regression analysis, and evaluation and presentation of the obtained results are outlined.

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Ismagilova, A. S., Z. A. Khamidullina, and S. I. Spivak. "Development and automation of algorithm for determining basis of nonlinear parameter functions of kinetic constants." Kataliz v promyshlennosti 19, no. 4 (July 11, 2019): 252–57. http://dx.doi.org/10.18412/1816-0387-2019-4-252-257.

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Mathematical modeling of catalytic processes is necessary for the complete and accurate description, as well as for controlling the quality and physicochemical studied of catalysts. In the paper, theoretical issues of industrial catalysis are discussed. The work is devoted to theoretical graph analysis of informativity of kinetic parameters of the model of a complex chemical reaction. The aim is the development and automation of algorithm for determining basis of nonlinear parameter functions in solving inverse problems of chemical kinetics in order to define the number and form of independent combinations of rate constants of elementary stages. A program package for analysis of informativity of kinetic parameters of the mathematical model of a complex catalytic reaction is developed and described. The obtained functional relations between the kinetic parameters can be useful for experimentalists in physicochemical interpretation and analysis of mechanisms of chemical reactions. In other words, the proposed method allows independent combinations of kinetic constants to be distinguished that results in shortening the number of the model parameters and, as a consequence, enhance the accuracy of the mathematical model. The mechanism of hydrogen oxidation over a platinum catalyst is given as an example of the use of the software.

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Martoprawiro, Muhamad, George B. Bacskay, and John C. Mackie. "Ab Initio Quantum Chemical and Kinetic Modeling Study of the Pyrolysis Kinetics of Pyrrole." Journal of Physical Chemistry A 103, no. 20 (May 1999): 3923–34. http://dx.doi.org/10.1021/jp984358h.

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Rankin, Stephen E., Christopher W. Macosko, and Alon V. McCormick. "Sol-gel polycondensation kinetic modeling: Methylethoxysilanes." AIChE Journal 44, no. 5 (May 1998): 1141–56. http://dx.doi.org/10.1002/aic.690440512.

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Fardhyanti, Dewi Selvia, Megawati, Haniif Prasetiawan, Noniek Nabuasa, and Mohammad Arik Ardianta. "Chemical Kinetics Modeling on Bio-Oil Production from Pyrolysis of Sugarcane Bagasse." Materials Science Forum 1034 (June 15, 2021): 199–205. http://dx.doi.org/10.4028/www.scientific.net/msf.1034.199.

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Biomass is a source of alternative energy that is environmentally friendly and very promising as one of the sources of renewable energy at present. The best candidate for the biomass waste for pyrolysis raw material is sugarcane bagasse. The sugarcane bagasse is a fibrous residue that is produced after crushing sugarcane for its extraction. Sugarcane bagasse is very potential to produce bio-oil through a pyrolysis process. The advantage of utilizing sugarcane bagasse is to reduce the amount of waste volume. Pyrolysis is a simple thermochemical conversion that transforms biomass with the near absence of absence of oxygen to produce fuel. Experiments were carried out on the fixed bed reactor. The analysis was carried out over a temperature range of 300-500 °C under atmospheric conditions. Products that are usually obtained from the pyrolysis process are bio-oil, char, and gas. Product analysis was performed using Gas Chromatography (GC) and Mass Spectrometry (MS) analysis. This research is aimed to study the kinetics of the sugarcane bagasse pyrolysis process to produce bio-oil. Three different models were proposed for the kinetic study and it was found that model III gave the best prediction on the calculation of pyrolysis process. From the calculation results, kinetic parameters which include activation energy (Ea) and the k factor (A) at a temperature of 300 °C is 2.4730 kJ/mol and 0.000335 s-1, at a temperature of 400 °C is 3, 2718 kJ/mol and 0.000563 s-1, and at a temperature of 500 °C is 4.8942 kJ/mol and 0.0009 s-1.

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