Group additive values for the gas phase standard enthalpy of formation of hydrocarbons and hydrocarbon radicals

A complete and consistent set of 95 Benson group additive values (GAV) for the standard enthalpy of formation of hydrocarbons and hydrocarbon radicals at 298 K and 1 bar is derived from an extensive and accurate database of 233 ab initio standard enthalpies of formation, calculated at the CBS-QB3 level of theory. The accuracy of the database was further improved by adding newly determined bond additive corrections (BAC) to the CBS-QB3 enthalpies. The mean absolute deviation (MAD) for a training set of 51 hydrocarbons is better than 2 kJ mol(-1). GAVs for 16 hydrocarbon groups, i.e., C(C(d))(3)(C), C-(C(d))(4), C-(C(t))(C(d))(C)(2), C-(C(t))(C(d))(2)(C), C-(C(t))(C(d))(3), C-(C(t))(2)(C)(2), C-(C(t))(2)(C(d))(C), C-(C(t))(2)(C(d))(2), C-(C(t))(3)(C), C-(C(t))(3)(C(d)), C-(C(t))(4), C-(C(b))(C(d))(C)(H), C-(C(b))(C(t))(H)(2), C-(C(b))(C(t))(C)(H), C-(C(b))(C(t))(C)(2), C(d)-(C(b))(C(t)), for 25 hydrocarbon radical groups, and several ring strain corrections (RSC) are determined for the first time. The new parameters significantly extend the applicability of Benson's group additivity method. The extensive database allowed an evaluation of previously proposed methods to account for non-next-nearest neighbor interactions (NNI). Here, a novel consistent scheme is proposed to account for NNIs in radicals. In addition, hydrogen bond increments (HBI) are determined for the calculation of radical standard enthalpies of formation. In particular for resonance stabilized radicals, the HBI method provides an improvement over Benson's group additivity method.     

Supplier-customer interaction in quality control

We develop a game theoretic model of joint quality control in a single sourcing environment which integrates supplier and customer decisions. In this model, both parties behave strategically and take each other's incentives into account when deciding on their respective sampling plans. The specific sampling plans considered are of the single sample fraction defective with rectifying inspection type. A method to find the optimal sampling plans for both supplier and customer in two different informational setups is constructed. The resulting models lead to examination of Stackelberg and Nash equilibria. Numerical examples of such equilibria are presented, indicating how optimal strategies depend on the parameters of the problem.     

Computational Fluid Dynamic Design of Jet Stirred Reactors for Measuring Intrinsic Kinetics of Gas‐Phase and Gas‐Solid Reactions

Nonreactive and reactive computational fluid dynamic simulations were applied to optimize the design of a laboratory scale jet stirred reactor for measuring intrinsic kinetics of gas‐phase and gas‐solid reactions, i.e. kinetics determined by chemical steps only and not by heat or mass transfer. In the past these reactors were designed and tested based on empirical design criteria and residence time distribution experiments. This work shows that these do not always capture important local effects that are vital for kinetic studies. First the degree of macro–mixing was evaluated for three different geometries (down case, 45° case and 90° case) by performing in silico residence time distribution experiments at 900 K, showing that with these type of experiments only minor differences are observed. However, the ethane steam cracking simulations revealed major differences, with the 45° case being the most uniform in terms of temperature and the 90° case being by far the worst. The species nonuniformity in all geometries was acceptable and was in some cases even partly masked by important shortcut streams such as those observed in the 90° case. The existing gradients on the substrate surface are sufficiently small to be neglected in modeling efforts. As temperature is the major parameter determining the rate of the surface reactions, the 45° case is suggested as the best geometry for measuring intrinsic kinetics.     

Detailed experimental and kinetic modeling study of 3-carene pyrolysis

3-Carene is an important potential biofuel with properties similar to the jet-propellant JP-10. Its thermal decomposition and combustion behavior is to date unknown, which is essential to assess its quality as a fuel. A combined experimental and kinetic modeling study has been conducted to understand the initial decomposition of 3-carene. The pyrolysis of 3-carene was investigated in a jet-stirred quartz reactor at atmospheric pressure, at temperatures varying from 650 to 1050 K, covering the complete conversion range. The decomposition of 3-carene was observed to start around 800 K, and it is almost complete at 970 K. Online gas chromatography shows that primarily aromatics are generated which suggests that 3-carene is not a good fuel candidate. The potential energy surface for the initial decomposition pathways determined by KinBot shows that a hydrogen elimination reaction dominates, giving primarily cara-2,4-diene. Next to this molecular pathway, radical pathways lead to aromatics via ring opening. The kinetic model was automatically generated with Genesys and consists of 2565 species and 9331 reactions. New quantum chemical calculations at the CBS-QB3 level of theory were needed to calculate rate coefficients and thermodynamic properties relevant for the primary decomposition of 3-carene. Both the conversion of 3-carene and the yields of the primary products (ie, benzene and hydrogen gas) are well predicted with this kinetic model. Rate of production analyses shows that the dominant pathways to convert 3-carene are hydrogen elimination reaction and radical chemistry.     

QUANTIS: Data quality assessment tool by clustering analysis

Automatically generated kinetic networks are ideally validated against a large set of accurate, reproducible, and easy-to-model experimental data. However, although this might seem simple, it proves to be quite challenging. QUANTIS, a publicly available Python package, is specifically developed to evaluate both the precision and accuracy of experimental data and to ensure a uniform, quick processing, and storage strategy that enables automated comparison of developed kinetic models. The precision is investigated with two clustering techniques, PCA and t-SNE, whereas the accuracy is probed with checks for the conservation laws. First, the developed tool processes, evaluates, and stores experimental yield data automatically. All data belonging to a given experiment, both unprocessed and processed, are stored in the form of an HDF5 container. The demonstration of QUANTIS on three different pyrolysis cases showed that it can help in identifying and overcoming instabilities in experimental datasets, reduce mass and molar balance closure discrepancies, and, by evaluating the visualized correlation matrices, increase understanding in the underlying reaction pathways. Inclusion of all experimental data in the HDF5 file makes it possible to automate simulating the experiment with CHEMKIN. Because of the employed InChI string identifiers for molecules, it is possible to automate the comparison experiment/simulation. QUANTIS and the concepts demonstrated therein is a potentially useful tool for data quality assessment, kinetic model validation, and refinement.     

Kinetic Modeling of α‐Hydrogen Abstractions from Unsaturated and Saturated Oxygenate Compounds by Carbon‐Centered Radicals

Hydrogen abstractions are important elementary reactions in a variety of reacting media at high temperatures in which oxygenates and hydrocarbon radicals are present. Accurate kinetic data are obtained from CBS‐QB3 ab initio (AI) calculations by using conventional transition‐state theory within the high‐pressure limit, including corrections for hindered rotation and tunneling. From the obtained results, a group‐additive (GA) model is developed that allows the Arrhenius parameters and rate coefficients for abstraction of the α‐hydrogen from a wide range of oxygenate compounds to be predicted at temperatures ranging from 300 to 1500 K. From a training set of 60 hydrogen abstractions from oxygenates by carbon‐centered radicals, 15 GA values (ΔGAV^os) are obtained for both the forward and reverse reactions. Among them, four ΔGAV^os refer to primary contributions, and the remaining 11 ΔGAV^os refer to secondary ones. The accuracy of the model is further improved by introducing seven corrections for cross‐resonance stabilization of the transition state from an additional set of 43 reactions. The determined ΔGAV^os are validated upon a test set of AI data for 17 reactions. The mean absolute deviation of the pre‐exponential factors (log A) and activation energies (E_a) for the forward reaction at 300 K are 0.238 log(m³ mol^?1 s^?1) and 1.5 kJ mol^?1, respectively, whereas the mean factor of deviation <ρ> between the GA‐predicted and the AI‐calculated rate coefficients is 1.6. In comparison with a compilation of 33 experimental rate coefficients, the <ρ> between the GA‐predicted values and these experimental values is only 2.2. Hence, the constructed GA model can be reliably used in the prediction of the kinetics of α‐hydrogen‐abstraction reactions between a broad range of oxygenates and oxygenate radicals.     

A Theoretical Exploration of the Potential of ICAR ATRP for One‐ and Two‐Pot Synthesis of Well‐Defined Diblock Copolymers

Kinetic Monte Carlo simulations are performed to investigate the capability of ICAR ATRP for the synthesis of well‐defined poly(isobornyl acrylate‐b‐styrene) block(‐like) copolymers using one‐pot semi‐batch and two‐pot batch procedures. The block copolymer quality is quantified via a block deviation (〈BD〉) value. For 〈BD〉 values lower than 0.30, the quality is defined as good and for well‐chosen polymerization conditions the formation of homopolymer chains upon addition of the second monomer can be suppressed. A better block quality is obtained when isobornyl acrylate is polymerized first. For lower Cu levels a one‐pot semi‐batch procedure allows a much faster ATRP and better control over the polymer properties than a two‐pot batch procedure.

     

Co-ordinating Two Searchers for an Object Hidden on an Interval

Two unit-speed searchers starting at 0 seek a stationary target hidden according to a known bounded symmetric distribution. The objective is to minimize the expected time for the searchers to return to 0 after one of them has found the target. We find a general optimality condition and use it to solve the problem when the target has a uniform, triangular, or truncated, exponential distribution. The problem has applications to parallel processing and to the optimal choice of drilling depths in the search for an underground mineral.