Initial product distributions from pyrolysis of normal and branched paraffins

Ranzi, E.; Dente, Mario; Pierucci, Sauro; Biardi, G.

doi:10.1021/i100009a023

Cited by 122 publications

(110 citation statements)

References 5 publications

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“…The reactive nature of the radical intermediates results in huge reaction networks typically containing hundreds of species and thousands of elementary reactions. [1][2][3] The construction of these reaction networks evolved from manually constructed reduced networks to the automated generation of extensive networks using advanced algorithms for the selection of the relevant reactions. [4][5][6][7][8][9][10][11][12][13][14][15][16] Sensitivity analyses are then valuable tools for tracking to which thermodynamic and/or kinetic model parameters the simulated product yields are most sensitive.…”

Section: Introductionmentioning

confidence: 99%

Carbon‐Centered Radical Addition and β‐Scission Reactions: Modeling of Activation Energies and Pre‐exponential Factors

et al. 2008

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A consistent set of group additive values DeltaGAV degrees for 46 groups is derived, allowing the calculation of rate coefficients for hydrocarbon radical additions and beta-scission reactions. A database of 51 rate coefficients based on CBS-QB3 calculations with corrections for hindered internal rotation was used as training set. The results of this computational method agree well with experimentally observed rate coefficients with a mean factor of deviation of 3, as benchmarked on a set of nine reactions. The temperature dependence on the resulting DeltaGAV degrees s in the broad range of 300-1300 K is limited to +/-4.5 kJ mol(-1) on activation energies and to +/-0.4 on logA (A: pre-exponential factor) for 90 % of the groups. Validation of the DeltaGAV degrees s was performed for a test set of 13 reactions. In the absence of severe steric hindrance and resonance effects in the transition state, the rate coefficients predicted by group additivity are within a factor of 3 of the CBS-QB3 ab initio rate coefficients for more than 90 % of the reactions in the test set. It can thus be expected that in most cases the GA method performs even better than standard DFT calculations for which a deviation factor of 10 is generally considered to be acceptable.

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Section: Introductionmentioning

confidence: 99%

Carbon‐Centered Radical Addition and β‐Scission Reactions: Modeling of Activation Energies and Pre‐exponential Factors

et al. 2008

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“…The term nopt in equation (2) corrects for the number of optically active isomers as the partition functions q pertain to a single enantiomer. The activation barrier at 0 K is determined with the CBS-QB3 complete basis set method of Montgomery et al [52] All ab initio calculations have been performed using the Gaussian 03 computational package.…”

Section: Rate Coefficientsmentioning

confidence: 99%

“…For radical chemistry, on which many of the world largest scale chemical processes are based, the reactive nature of the radical intermediates results in huge reaction networks typically involving hundreds of species and thousands of elementary reactions. [2][3][4] Currently, most elementary reaction networks are automatically generated using advanced algorithms for the selection of the relevant reactions. [5][6][7][8][9][10][11] Sensitivity studies on these reaction networks point out that the main part of the uncertainty on the product yields stems from inaccurate knowledge of kinetic data.…”

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confidence: 99%

Hydrogen Radical Additions to Unsaturated Hydrocarbons and the Reverse β‐Scission Reactions: Modeling of Activation Energies and Pre‐Exponential Factors

et al. 2010

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The group additivity method for Arrhenius parameters is applied to hydrogen addition to alkenes and alkynes and the reverse β-scission reactions, an important reaction family in thermal processes based on radical chemistry. A consistent set of group additive values for 33 groups is derived to calculate the activation energy and preexponential factor for a broad range of H-addition reactions. The group additive values are determined from CBS-QB3 ab initio calculated rate coefficients. A mean factor of deviation between the CBS-QB3 and the experimental rate coefficients for 7 reactions of only 2 in the range 300-1000 K is found. Tunneling coefficients for these reactions were found to be significant below 400 K and a correlation accounting for tunneling is presented. Application of the obtained group additive values to predict the kinetics for a set of 11 additions and β scissions yields rate coefficients within a factor 3.5 from the CBS-QB3 results except for 2 β scissions with severe steric effects. The mean factor of deviation with experimental rate coefficients is 2.0, showing that the group additive method with tunneling corrections can accurately predict the kinetics, at least as accurate as the most commonly used density functional methods. The constructed group additive model can hence be applied to predict the kinetics of hydrogen radical additions to a broad range of unsaturated compounds. IntroductionThe addition of hydrogen radicals to alkenes and its reverse β scission, are important elementary steps in radical processes such as polymerization, pyrolysis, steam cracking, partial oxidation and combustion.[1] Therefore, the reaction family of hydrogen addition/β scission forms an indispensable part of any radical reaction network.A reliable reactor optimization requires an accurate kinetic model based on elementary reactions. For radical chemistry, on which many of the world largest scale chemical processes are based, the reactive nature of the radical intermediates results in huge reaction networks typically involving hundreds of species and thousands of elementary reactions. [2][3][4] Currently, most elementary reaction networks are automatically generated using advanced algorithms for the selection of the relevant reactions. [5][6][7][8][9][10][11] Sensitivity studies on these reaction networks point out that the main part of the uncertainty on the product yields stems from inaccurate knowledge of kinetic data. [12,13] Therefore, accurate kinetic data are essential to obtain reliable process simulations. Moreover, if rate-based network construction algorithms are applied, [14] accurate rate data are even more important as inaccuracies can result in the construction of an incomplete network that is not capable of grasping the underlying chemistry of the process.A quantitative description of radical processes thus requires that rate parameters be known for all of the different reactions comprising the reaction network. However, it is very difficult to measure kinetic parameters for individual radical r...

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“…These models account in detail for the radical nature of thermal cracking (Ranzi et al (1983), In the following, these radical mechanisms will be briefly presented. The necessity for a reduction in the number of parameters will be discussed.…”

Section: Lumped and Molecular Modelsmentioning

confidence: 99%

Kinetic Modeling of Complex Processes. Thermal Cracking and Catalytic Hydrocracking

Froment

1992

Chemical Reactor Technology for Environmentally Safe Reactors and Products

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ABSTRACT. A fundamental approach is outlined for the kinetic modeling of complex processes like thermal cracking or catalytic hydrocracking of mixtures of hydrocarbons. The reaction networks are written in terms of radical mechanisms in the first case and of carbenium ion mechanisms in the second case. Since the elementary steps of the networks pertain to a relatively small number of classes, the number of rate coefficients is kept within tractable limits. The reaction networks are generated by computer through Boolean relation matrices. The number of continuity equations is limited by the elimination of radicals or carbenium ions through the pseudo-steady-state approximation.

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Initial product distributions from pyrolysis of normal and branched paraffins

Cited by 122 publications

References 5 publications

Carbon‐Centered Radical Addition and β‐Scission Reactions: Modeling of Activation Energies and Pre‐exponential Factors

Carbon‐Centered Radical Addition and β‐Scission Reactions: Modeling of Activation Energies and Pre‐exponential Factors

Hydrogen Radical Additions to Unsaturated Hydrocarbons and the Reverse β‐Scission Reactions: Modeling of Activation Energies and Pre‐Exponential Factors

Kinetic Modeling of Complex Processes. Thermal Cracking and Catalytic Hydrocracking

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