979 resultados para Chemical kinetics.
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Self-segregation and compartimentalisation are observed experimentally to occur spontaneously on live membranes as well as reconstructed model membranes. It is believed that many of these processes are caused or supported by anomalous diffusive behaviours of biomolecules on membranes due to the complex and heterogeneous nature of these environments. These phenomena are on the one hand of great interest in biology, since they may be an important way for biological systems to selectively localize receptors, regulate signaling or modulate kinetics; and on the other, they provide an inspiration for engineering designs that mimick natural systems. We present an interactive software package we are developing for the purpose of simulating such processes numerically using a fundamental Monte Carlo approach. This program includes the ability to simulate kinetics and mass transport in the presence of either mobile or immobile obstacles and other relevant structures such as liquid-ordered lipid microdomains. We also present preliminary simulation results regarding the selective spatial localization and chemical kinetics modulating power of immobile obstacles on the membrane, obtained using the program.
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In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E coli, and conclude with a discussion on the significance of this work. (C) 2004 Elsevier Ltd. All rights reserved.
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More than 70 molecules of varied nature have been identified in the envelopes of carbon-rich stars through their spectral fingerprints in the microwave or far infrared regions. Many of them are carbon chain molecules and radicals, and a significant number are unique to the circumstellar medium. The determination of relevant laboratory kinetics data is critical to keep up with the development of the high spectral and spatial resolution observations and of the refinement of chemical models. Neutralneutral reactions of the CN radical with unsaturated hydrocarbons could be a dominant route in the formation of cyanopolyynes, even at low temperatures and deserve a detailed laboratory investigation. The approach we have developed aims to bridge the temperature gap between resistively heated flow tubes and shock tubes. The present kinetic measurements are obtained using a new reactor combining a high-enthalpy source with a flow tube and a pulsed laser photolysislaser-induced fluorescence system to probe the undergoing chemical reactions. The high-enthalpy flow tube has been used to measure the rate constant of the reaction of the CN radical with propane (C3H8), propene (C3H6), allene (C3H4), 1,3-butadiene (1,3-C4H6), and 1-butyne (C4H6) over a temperature range extending from 300 to 1200 K. All studied reactions of CN with unsaturated hydrocarbons are rapid, with rate coefficients greater than 10-10 cm3 center dot molecule-1 center dot s-1 and exhibit slight negative temperature dependence above room temperature. (c) 2012 Wiley Periodicals, Inc. Int J Chem Kinet 44: 753766, 2012
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This paper presents computational work on the biogas early phase combustion in spark ignition (SI) engines using detailed chemical kinetics. Specifically, the early phase combustion is studied to assess the effect of various ignition parameters such as spark plug location, spark energy, and number of spark plugs. An integrated version of the KIVA-3V and CHEMKIN codes was developed and used for the simulations utilizing detailed kinetics involving 325 reactions and 53 species The results show that location of the spark plug and local flow field play an important role. A central plug configuration, which is associated with higher local flow velocities in the vicinity of the spark plug, showed faster initial combustion. Although a dual plug configuration shows the highest rate of fuel consumption, it is comparable to the rate exhibited by the central plug case. The radical species important in the initiation of combustion are identified, and their concentrations are monitored during the early phase of combustion. The concentration of these radicals is also observed to correlate very well with the above-mentioned trend.Thus, the role of these radicals in promoting faster combustion has been clearly established. It is also observed that the minimum ignition energy required to initiate a self-sustained flame depends on the flow field condition in the vicinity of the spark plug.Increasing the methane content in the biogas has shown improved combustion.
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This paper deals with the thermo-physical changes that a droplet undergoes when it is radiatively heated in a levitated environment. The heat and mass transport model has been developed along with chemical kinetics within a cerium nitrate droplet. The chemical transformation of cerium nitrate to ceria during the process is predicted using Kramers' reaction mechanism which justifies the formation of ceria at a very low temperature as observed in experiments. The rate equation modeled by Kramers is modified suitably to be applicable within the framework of a droplet, and predicts experimental results well in both bulk form of cerium nitrate and in aqueous cerium nitrate droplet. The dependence of dissociation reaction rate on droplet size is determined and the transient mass concentration of unreacted cerium nitrate is reported. The model is validated with experiments both for liquid phase vaporization and chemical reaction. Vaporization and chemical conversion are simulated for different ambient conditions. The competitive effects of sensible heating rate and the rate of vaporization with diffusion of cerium nitrate is seen to play a key role in determining the mass fraction of ceria formed within the droplet. Spatially resolved modeling of the droplet enables the understanding of the conversion of chemical species in more detail.
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The present study provides an extensive and detailed numerical analysis of NO chemical kinetics in low calorific value H-2/CO syngas flames utilizing predictions by five chemical kinetic mechanisms available out of which four deal with H-2/CO while the fifth mechanism (GRI 3.0) additionally accounts for hydrocarbon chemistry. Comparison of predicted axial NO profiles in premixed flat flames with measurements at 1 bar, 3.05 bar and 9.15 bar shows considerably large quantitative differences among the various mechanisms. However, at each pressure, the quantitative reaction path diagrams show similar NO formation pathways for most of the mechanisms. Interestingly, in counterflow diffusion flames, the quantitative reaction path diagrams and sensitivity analyses using the various mechanisms reveal major differences in the NO formation pathways and reaction rates of important reactions. The NNH and N2O intermediate pathways are found to be the major contributors for NO formation in all the reaction mechanisms except GRI 3.0 in syngas diffusion flames. The GRI 3.0 mechanism is observed to predict prompt NO pathway as the major contributing pathway to NO formation. This is attributed to prediction of a large concentration of CH radical by the GRI 3.0 as opposed to a relatively negligible value predicted by all other mechanisms. Also, the back-conversion of NNH into N2O at lower pressures (2-4 bar) was uniquely observed for one of the five mechanisms. The net reaction rates and peak flame temperatures are used to correlate and explain the differences observed in the peak NO] at different pressures. This study identifies key reactions needing assessment and also highlights the need for experimental data in syngas diffusion flames in order to assess and optimize H-2/CO and nitrogen chemistry. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.
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A kinetic model has been developed for the prediction of the concentration gelds in an rf plasma reactor. A sample calculation for a SiCl4/H2 system is then performed. The model considers the mixing processes along with the kinetics of seven reactions involving the decomposition of these reactants. The results obtained are compared to those assuming chemical equilibrium. The predictions indicate that an equilibrium assumption will result in lower predicted temperature fields in the reactor. Furthermore, for the chemical system considered here, while differences exist between the concentration fields obtained by the two models, the differences are not substantial.
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A new method for quantitative analysis of lactide has been developed by applying chemical kinetics to a HPLC system. The most important advance is its practical approach to the quantification of analytes that are unstable in the HPLC mobile phase. In HPLC analysis, anhydrous mobile phases cannot separate lactide from impurities, and only mixtures of water and organic solvent can achieve effective separation. By selecting conditions for testing and studying the kinetics of lactide hydrolysis, extensive experiments revealed that lactide degradation can be treated as a pseudo-first-order reaction under the given HPLC conditions, and lactide content or purity can be quantitatively determined. This method is practical for measuring the purity of the intermediate lactide in polylactic acid (PLA) production and the lactide content in PLA.
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The kinetic study of the coupled enzymatic reaction involving monomeric yeast hexokinase PII (HK) and yeast glucose-6-phosphate dehydrogenase (G-6-PDH) yields a Michaelis constant of 0.15 ± 0.01 mM for D-glucose. At pH 8.7 HK is present in monomeric form. The addition of polyethylene glycol (PEG), to the reaction mixture increased the affinity of HK for glucose, independent ofMW of the PEG from 2000 to 10000. The osmotic stress exerted by PEG can be used to measure the change in number of water molecules that accompany enzyme conformational changes (Rand, et al., 1993). Results indicate that the G-6-PDH is not osmotically sensitive and thus, the change in the number of PEG-inaccessible water molecules (ANw) measured in the coupled reaction is only the difference between the glucose-bound and glucosefree conformations of HK. ANw ~ 450 with PEGs of MW > 2000 under conditions for both binding (Reid and Rand, 1997) and kinetic assays. The contribution water may play in the binding of ATP (Km = 0.24 + 0.02 mM) has also been examined. It was found that in this case ANw = (for osmotic pressures < 2.8x10* dynes/cm^), suggesting no additional numbers of waters are displaced when ATP binds to HK. Osmotic pressure experiments were also performed with dimeric HK. It was determined that both the monomeric and dimeric forms of HK give the same ANw under low pressures. If this large ANw is due to conformational flexibility, it would appear that the flexibility is not reduced upon dimerization ofthe enzyme.
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"July 18, 1958."
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At head of title: Combustion Dynamics Division, Air Force Office of Scientific Research, ARDC, Washington, D. C., File no. AF 18(600)-1332.
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In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge–Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work.
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Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein.
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One of the fundamental motivations underlying computational cell biology is to gain insight into the complicated dynamical processes taking place, for example, on the plasma membrane or in the cytosol of a cell. These processes are often so complicated that purely temporal mathematical models cannot adequately capture the complex chemical kinetics and transport processes of, for example, proteins or vesicles. On the other hand, spatial models such as Monte Carlo approaches can have very large computational overheads. This chapter gives an overview of the state of the art in the development of stochastic simulation techniques for the spatial modelling of dynamic processes in a living cell.