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Stochastic mechanistic models for gradient copolymerisation systems were developed based on a kinetic Monte Carlo algorithm. Due to the discrete nature of the simulations, chains were tracked as binary strings allowing for the storage of the complete sequence of each polymer chain, allowing for an unprecedented level of detail. Models were developed that simulated styrene/4-acetoxystyrene semi-batch gradient copolymer syntheses, and explicit sequence information was determined using simulation results. The chemical composition distribution was mapped for the copolymers, which is capable of providing a visual description of both the size and overall composition distributions of the copolymer and a qualitative description of the chain architecture. This methodology was expanded to track the explicit sequences of each chain that was used to determine the number and weight fraction sequence length distributions. Simulation results show that tail end compositional tapering was never fully achieved. Case studies were conducted to determine the major factors affecting tail end tapering, including increasing the initial batch fraction and varying the 4-acetoxystyrene flow rate. While an increase in initial batch fraction increases 4-acetoxystyrene significantly, head end tapering is lost, while a large increase in flow rate is not capable of fully tapering the tail end. [ABSTRACT FROM AUTHOR]

Abstract: Reaction progress kinetic analysis of the proline-mediated intermolecular aldol reaction shows that the rate depends on the concentrations of both the donor ketone1 and the electrophilic aldehyde 2, implying that enamine formation cannot be rate-determining. The observed kinetics and deuterium isotope effects are consistent with formation of the product iminium species as the rate-determining step. [Copyright &y& Elsevier]

Small gold nanoparticles (AuNPs) have recently shown potential to act as a catalyst for oxidation reactions mediated by free radicals, with their role postulated to be facilitating hydrogen abstraction by gold superoxo species and/or activation of hydroperoxides. Cyclooctene oxidation using molecular oxygen as the oxidant at 373 K showed high selectivity to the epoxide product, cyclooctene oxide, with either tert-butyl hydroperoxide as an initiator or in the presence of small AuNPs (5-8 atoms). While previous studies have investigated the mechanism leading to high epoxide selectivity using density functional theory, a full microkinetic model was developed in this work using automated network generation to determine the relative contributions of elementary reactions and the role of AuNPs. A cycle of radical addition of peroxy and alkoxy radicals with subsequent epoxidation reactions can justify the observed activity and selectivity to epoxide at multiple temperatures and initiator concentrations. The alcohol, ketone, and hydroperoxide minor products are formed when the peroxy and alkoxy radicals perform hydrogen abstraction or β-scission. The overall selectivity is determined by the competition between the addition and hydrogen abstraction reactions. With the underlying homogeneous reaction model validated, the effect of the AuNPs was determined through an expanded model that includes cycles for both hydrogen abstraction by superoxo gold species and hydroperoxide decomposition via species derived from AuNPs. The model suggests that hydrogen abstraction by the superoxo gold species dominates at short times compared to homogeneous initiation, increasing the activity during the induction period and reducing the time before radical chain oxidation commences. On the time scale of an hour, hydroperoxide decomposition is significantly catalyzed by the presence of gold species, increasing the overall rate of chain propagation. [ABSTRACT FROM AUTHOR]

The modeling of the molecular weight distribution of polymers is critical in polymerization modeling. Moment-based models and kinetic Monte Carlo are two methods used to calculate the number and weight average molecular weight during simulation of polymerization. While these two methods are commonly considered to yield equivalent results in the molecular weight distribution, we show that there can be significant differences between these two methods when copolymerization of multiple monomers is modeled. In particular, clear differences in results exist for low molecular weight polymers where the molar mass of one monomer is two or more times greater than the others. Detailed analysis is provided for the cause of the difference, and we demonstrate the importance of tracking the exact number of each type of monomer in every polymer chain when calculating the moments of molecular weight. [ABSTRACT FROM AUTHOR]

Kinetic Monte Carlo (KMC) has become a well-established technique for simulating the kinetics of free radical polymerization, both to generate polymer molecular weight distributions and, more recently, to track the explicit monomer sequence in every chain. However, KMC simulations require a minimal number of molecules in order to accurately describe monomer conversion and macromolecular quantities, which can render them computationally prohibitive. In this work, we propose a novel approach for accelerating KMC simulations through scaling relationships that allow the number of molecules simulated to be reduced. Using the concept of the minimal number of molecules and an explicit expression we derived for copolymerization, we propose a factor that is used to scale the reaction rate constants which results in an acceleration of KMC simulations by a factor of ~100. Furthermore, we demonstrate the limits of this scaling approach, revealing the absolute lower bound for the number of molecules used in KMC simulations of free radical polymerization and the associated population size of dead chains formed. We illustrate this approach using examples of acrylate copolymerization, but this approach is sufficiently general that it can be applied to a wide variety of free radical polymerization systems and even other free radical chemistries. [ABSTRACT FROM AUTHOR]

Review: 86 refs. [ABSTRACT FROM AUTHOR]

A computationalframework based on continuous distribution kineticswas constructed to solve the mechanistic model that was developedfor fast pyrolysis of glucose-based carbohydrates in the first partof this study [Zhou et al. Ind. Eng. Chem. Res.2014, 53. DOI 10.1021/ie502259w]. Comparing modeling results with experimental yieldsfrom fast pyrolysis over a wide range of reaction conditions validatesthe model. Agreement between model yields of final pyrolysis productswith experimental data of fast pyrolysis of cellulose at temperaturesranging from 400 to 600 °C and maltohexaose, cellobiose, andglucose at 500 °C showed that the mechanistic model was robustand extendable. In comparison to our previous model [Vinu,R.; Broadbelt, L. J. Energy Environ. Sci.2012, 5, 9808–9826], the mechanistic model presentedin this work incorporating new findings from experiments and theoreticalcalculations showed enhanced performance in capturing experimentalyields of major products such as levoglucosan-pyranose, char, H2O, CO2, CO, and especially glycolaldehyde and 5-hydroxymethylfurfural.The model was also able to well match the yields of pyrolysis productsthat our previous model did not include, such as levoglucosan-furanose,methyl glyoxal, and minor products with yields of less than 1 wt %like levoglucosenone, acetone, dihydroxyacetone, and propenal. Themechanistic model showed its versatility in providing insights thatwere difficult to obtain from experiments, including a time scaleof 4–5 s for complete thermoconversion of cellulose at 500°C. Analysis of the contributions of competing reaction pathwaysshowed that decomposition of cellulosic chains played a more importantrole in the formation of levoglucosan and glycolaldehyde than in thatof other pyrolysis products. [ABSTRACT FROM AUTHOR]

Abstract: Experiments and microkinetic modeling were used to investigate the reaction mechanism of cis-cyclooctene oxidation with H2O2 on heterogeneous manganese 1,4,7-trimethyl-1,4,7-triazacyclononane (Mn–tmtacn) catalysts. A mechanism based on literature reports and model discrimination was identified that captured experimental data well, including data at reaction conditions that were not used for parameter estimation. H2O2 activation on the heterogeneous catalytic complex was identified as the rate-determining step (RDS), and a simple analytical rate expression was derived using the RDS and the pseudo-steady-state approximation for all intermediates. Predicted reaction orders for cis-cyclooctene, water, H2O2, catalyst, and diol and epoxide products are also consistent with experimental observations and can be rationalized according to the derived rate expression. In addition, the ratio of productive to unproductive H2O2 use is analyzed, and catalyst deactivation is found to be an important step in the reaction mechanism that is highly sensitive to temperature. [Copyright &y& Elsevier]

Abstract: Experiments and microkinetic modeling were used to investigate the kinetics of styrene epoxidation catalyzed by (porphyrin)Mn using iodosylbenzene. While the kinetics follow the general form of Michaelis–Menten rate expressions as proposed in the literature, these simplified rate forms cannot capture all the details of the kinetics simultaneously, most notably catalyst deactivation. In contrast, a microkinetic model based on elementary steps, including deactivation via μ-oxo dimer formation and irreversible degradation, is able to capture experimental data over all reaction times and for different (porphyrin)Mn. Experimentally, we show that encapsulation of (porphyrin)Mn in a supramolecular cavity known as a molecular square significantly reduces catalyst deactivation, which is in agreement with previous experimental studies. Microkinetic modeling also captured the kinetics of this system. Net rate analysis revealed that production of epoxide was primarily due to encapsulated catalysts, and the model was able to quantify the difference in the concentration of deactivated catalyst with and without encapsulation. [Copyright &y& Elsevier]