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Bio-oil produced from biomass fast pyrolysis often requires catalytic upgrading to remove oxygen and acidic species over zeolite catalysts. The elementary reactions in the mechanism for this process involve carbenium and oxonium ions. In order to develop a detailed kinetic model for the catalytic upgrading of biomass, rate constants are required for these elementary reactions. The parameters in the Arrhenius equation can be related to thermodynamic properties through structure–reactivity relationships, such as the Evans–Polanyi relationship. For this relationship, enthalpies of formation of each species are required, which can be reasonably estimated using group additivity. However, the literature previously lacked group additivity values for oxygenates, oxonium ions, and oxygen-containing carbenium ions. In this work, 71 group additivity values for these types of groups were regressed, 65 of which had not been reported previously and six of which were newly estimated based on regression in the context of...

Thin films (∼115 μm thick) of milled wood lignin from hybrid poplar and acid-washed hybrid poplar were pyrolyzed at 500 °C and ∼55 °C/s at five pressures (4, 250, 500, 750, and 1000 mbar) to determine the impact of secondary liquid intermediate reactions on the product distribution. For both milled wood lignin extracted from poplar and acid-washed hybrid poplar wood, pressure had a significant effect on the product distribution for thin film pyrolysis between 4 and 1000 mbar. For lignin, lowering the pressure from 1000 mbar to 4 mbar reduced the char yield from 36 to 23% and enhanced production of large cluster pyrolytic lignin. However, the pressure did not dramatically impact the gas yield (CO2, CO, methane, H2, ethane, propane, and butane), nor did it significantly impact the release of monomeric phenolic compounds. ICR-MS shows limited changes in the composition of lignin oligomers. The increase in the production of large lignin oligomers observed by UV fluorescence and the reduction of char yield wit...

The economic viability of the biofuel industry has been plagued in part by the incomplete valorization of lignin, which is currently being burned for process heat. One of the roadblocks to effectively converting lignin into usable fuels and chemicals is that the structure of lignin has yet to be entirely understood owing to its polydispersity, complexity, and hyper-branched topology. Libraries of structural representations of lignin accounting for these facets have recently been proposed for wheatstraw, an herbaceous biomass, based on a stochastic generation method that creates lignin molecules that collectively conform to properties measured experimentally. We have extended this stochastic method to accommodate more complexity and any type of biomass, i.e., softwood, hardwood, or herbaceous. The unique mechanistic details for several of the new lignin bond types are essential in deciding rules for bond formation in the algorithm. Further, we present two successful methods of decreasing the degrees of fre...

Advances in computational modeling tools have allowed for the construction of detailed chemical models of oxidation processes to enhance the understanding of mechanisms and answer questions of interest in diverse fields such as DNA damage, lubricant oxidation, food chemistry, and art conservation. The construction of detailed kinetic models is facilitated by the use of kinetic correlations, such as Evans–Polanyi relationships, where the activation energy, EA, is related linearly to the heat of reaction, ΔHR: EA = E0 + α ΔHR. In this work, we present an Evans–Polanyi relationship based on properties determined from hybrid G4 quantum chemical calculations for an epoxidation reaction of peroxy species. We explore a broader chemical space at a higher level of theory than previous reports, and as a result, the importance of several key structural features, such as alkylhydroperoxy functional groups, that can strongly influence the trends observed was revealed. We suggest a subdivision of the reaction family in...

The homogeneous partial oxidation of 1,3-propanediol using oxygen at relatively mild conditions (430 K) has been observed to result in high selectivity to acrolein at low to moderate conversion with minor formation of formaldehyde and acetaldehyde (Diaz, E. ChemSusChem 2010, 3, 1063−1070, DOI: 10.1002/cssc.201000142). In this work, various competing mechanistic postulates for the selective conversion of 1,3-propanediol to acrolein were tested quantitatively using mechanistic modeling. Specifically, mechanisms based on free-radical chemistry and concerted pathways, both of which have been postulated in the literature, were evaluated. Automated mechanism generation was used to comprehensively create detailed reaction mechanisms based on reaction families relevant to free-radical or concerted chemistries. A mechanism based on free-radical reactions alone was unable to account for the rate of conversion and high selectivity to acrolein that were observed experimentally. Concerted pathways based on both unimol...

Kinetic Monte Carlo (KMC) has been widely used in the simulation of polymeric reactions. The power of KMC is highlighted by its ability to keep track of the length and sequence of every radical or polymer chain, while it is computationally more expensive than deterministic kinetic models. This paper introduces an acceleration method that significantly reduces the computational cost of KMC simulations, while keeping the same features as the full kinetic Monte Carlo simulations. Case studies are used to demonstrate the general applicability of this method to free radical copolymerization. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4013–4021, 2017

Current methods for processing lignocellulosic biomass fail to take full advantage of the phenolic chemicals available in lignin, the third most common polymer on the planet. The complexity of the lignin polymer structure, the lack of knowledge of the mechanisms by which it breaks down, and the difficulties in predicting and controlling the reaction product distribution make improvement in processing methods challenging. The use of model compounds, which contain only a few key features of the native polymer, allow the reactivity of the overall polymer to be investigated more simply by isolating key elements. In our previous work, we examined the mechanism of acidolysis for two α-O-4 lignin model compounds, benzylphenyl ether (BPE) and 1-(phenoxyethyl)benzene (PEB). In the present work, we examine the rate-limiting step of this mechanism, a nucleophilic attack on the α-carbon commensurate with protonation of the ether oxygen, for other α-O-4 model compounds that contain features more reminiscent of native ...

Modern biological tools generate a wealth of data on metabolite and protein concentrations that can be used to help inform new strain designs. However, learning from these data to predict how a cell will respond to genetic changes, a key need for engineering, remains challenging. A promising technique for leveraging omics measurements in metabolic modeling involves the construction of kinetic descriptions of the enzymatic reactions that occur within a cell. Parameterizing these models from biological data can be computationally difficult, since methods must also quantify the uncertainty in model parameters resulting from the observed data. While the field of Bayesian inference offers a wide range of methods for efficiently estimating distributions in parameter uncertainty, such techniques are poorly suited to traditional kinetic models due to their complex rate laws and resulting nonlinear dynamics. In this paper, we employ linear-logarithmic kinetics to simplify the calculation of steady-state flux distributions and enable efficient sampling and inference methods. We demonstrate that detailed information on the posterior distribution of parameters can be obtained efficiently at a variety of problem scales, including nearly genome-scale kinetic models trained on multiomics datasets. These results allow modern Bayesian machine learning tools to be leveraged in understanding biological data and in developing new, efficient strain designs., Author Summary Genetic engineering of microbes is a promising strategy to enable more efficient and environmentally friendly production routes for chemicals and materials traditionally produced from petroleum. While the tools to both edit microbial genomes and measure the resulting changes to cellular physiology are growing increasingly efficient, our ability to predict which genetic interventions will have the greatest likelihood of achieving the desired phenotype is still lacking. In particular, computational methods are needed that are able to efficiently ingest the increasing amount of data generated from large biological datasets to guide subsequent rounds of experiments. This study presents an efficient algorithm coupled to modern computational tools that permits a closer integration of modeling in the design, build, test, and learn cycle of genetic engineering.

Reliably producing a competent oocyte entails a deeper comprehension of ovarian follicle maturation, a very complex process that includes meiotic maturation of the female gamete, the oocyte, together with the mitotic divisions of the hormone-producing somatic cells. In this report, we investigate murine ovarian folliculogenesis in vivo using publicly available time-series microarrays from primordial to antral stage follicles. Manually curated protein interaction networks were employed to identify autocrine and paracrine signaling between the oocyte and the somatic cells (granulosa and theca cells) at multiple stages of follicle development. We established plausible protein-binding interactions between expressed genes that encode secreted factors and expressed genes that encode cellular receptors. Some computationally identified signaling interactions are well established, such as the paracrine signaling from the oocyte to the somatic cells through the oocyte-secreted growth factor Gdf9, while others are novel connections in term of ovarian folliculogenesis, such as the possible paracrine connection from somatic-secreted factor Ntn3 to the oocyte receptor Neo1. Additionally, we identified several of the likely transcription factors that might control the dynamic transcriptome during ovarian follicle development, noting that the YAP/TAZ signaling pathway is very active in vivo. This novel dynamic model of signaling and regulation can be employed to generate testable hypotheses regarding follicle development that could be validated experimentally, guiding the improvement of culture media to enhance in vitro ovarian follicle maturation and possibly novel therapeutic targets for reproductive diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s43032-019-00075-8) contains supplementary material, which is available to authorized users.

SUMMARYReliably producing a competent oocyte entails a deeper comprehension of ovarian follicle maturation, a very complex process that includes meiotic maturation of the female gamete, the oocyte, together with the mitotic divisions of the hormone-producing somatic cells. In this report, we investigate mice ovarian folliculogenesis in vivo using publically available time-series microarrays from primordial to antral stage follicles. Manually curated protein interaction networks were employed to identify autocrine and paracrine signaling between the oocyte and the somatic cells (granulosa and theca cells) and the oocyte and cumulus and mural cells at multiple stages of follicle development. We established protein binding interactions between expressed genes that encoded secreted factors and expressed genes that encoded cellular receptors. Some of computationally identified signaling interactions are well established, such as the paracrine signaling from the oocyte to the somatic cells through the secreted oocyte growth factor Gdf9; while others are novel connections in term of ovarian folliculogenesis, such as the possible paracrine connection from somatic secreted factor Ntn3 to the oocyte receptor Neo1. Additionally, we identify several of the likely transcription factors that might control the dynamic transcriptome during ovarian follicle development, noting that the YAP/TAP signaling is very active in vivo. This novel dynamic model of signaling and regulation can be employed to generate testable hypotheses regarding follicle development, guide the improvement of culture media to enhance in vitro ovarian follicle maturation and possibly as novel therapeutic targets for reproductive diseases.

Biobased chemicals will inevitably be an important part of a sustainable organic chemical industry. Current efforts in biobased chemicals are largely driven by opportunistic chemical product targets requiring complete technology development from feedstock to final product for a specific molecule. To enhance the development of biobased chemicals, it is important to create strategies that can be more systematic and can leverage advancements across multiple final products. Discussed here is the concept of bioprivileged molecules, which are chemical intermediates that have the potential to be efficiently converted into a range of product molecules that can both directly replace existing petrochemicals and are novel molecules that impart enhanced performance properties in end-use applications.

This chapter provides a robust and computationally inexpensive DFT protocol to accurately estimate reaction rate parameters for free-radical polymerization (FRP). The protocol is applied to a series of small molecules and excellent agreement is achieved with experimental data in gas and condensed phases. It is also shown that including the contributions from multiple reaction pathways is extremely important. In gas phase, the raw (CP)M06-2X/6-311+G(3df,2p)//B3LYP/6-31+G(d,p) calculations are sufficient to provide the desired accuracy. In condensed phase with a low dielectric constant, the best overall rate parameters are obtained using gas-phase calculations. However, the agreement is fortuitous only due to under-prediction of the Arrhenius parameters. A direct implicit solvation model and thermodynamic cycle calculations deliver an accurate activation energy but suffer from a low pre-exponential factor. We recommend that a two-parameter entropy scaling model be utilized to reach the targeted accuracy of the overall rate coefficient and the individual Arrhenius parameters.

This review summarizes computational modeling literature concerning linseed oil autoxidation in the context of oil paint. After discussing the chemical structure and composition of linseed oil, an overview is given of polymer properties of the material and the experimental techniques used to infer these properties. The review proceeds with the survey of existing computational modeling techniques used to investigate the drying process of linseed oil.

Fast pyrolysis is a promising thermochemical technology that breaks down renewable and abundant lignocellulosic biomass into a primary liquid product (bio-oil) in seconds. The bio-oil can then be potentially catalytically upgraded into transportation fuels and multiple commodity chemicals. Hemicellulose is one of the three major components of lignocellulosic biomass and is characterized as a group of cell wall polysaccharides that are neither cellulose nor pectin. The composition and structural features of hemicellulose (mixture of different heterogeneous polysaccharides) and different specific hemicellulose polysaccharides are reviewed. Particular focus is then given to reviewing the status of hemicellulose pyrolysis in terms of experimental investigations, reaction mechanisms, and kinetic modeling. For each aspect, recent results, challenges, and future prospects are addressed.

Efforts to derive value-added chemicals from lignin are hindered in part because of its great structural complexity and heterogeneity. Lignin is a polydisperse, random copolymer with varying proportions of monomers and interunit linkage types, forming a hyperbranched topology. Structural models comprising a single macromolecular representation have been proposed for specific biomass sources; these representations, although consistent with experimental observations, are not unique. Alternative models consisting of populations of representations whose average properties match experiment have also been proposed. Expanding on this latter approach, we have developed a stochastic method of generating libraries of diverse and complex structural representations of lignin that is generally applicable to any biomass source. For demonstration purposes, the method is applied to create libraries of wheat straw lignin, a representative herbaceous lignin. The libraries are statistically validated through the χ2 goodness...

The crosspropagation of 1-ethylcyclopentyl methacrylate (ECPMA) and methyl methacrylate (MMA) has been studied using a combination of quantum chemistry calculations and experiment. Our computational work utilizes a trimer-to-tetramer reaction model, coupled with an ONIOM (B3LYP/6-31G(2df,p): B3LYP/6-31G(d)) method for geometry optimization and an M06-2X/6-311+G(2df,p) method plus SMD solvation model for single point energy calculations. The results show several trends: the identity of the ultimate unit of a trimer radical affects not only the preferred conformation of the region where the reaction takes place, but also the reactivity of the radical; the addition of an ECPMA monomer to the radicals is generally favored compared to an MMA monomer; the pen-penultimate unit of a trimer radical shows a nonnegligible entropic effect; the penultimate unit effect is implicit for the ECPMA–MMA copolymer system. Finally, terminal model reactivity ratios fitted based on the explicit rate coefficients calculated from the quantum chemical results are compared with those from experimental measurements. The computations not only agree qualitatively with experimentally derived results in terms of the selectivity of ECPMA–MMA crosspropagation, but also give reasonable quantitative predictions of reactivity ratios.

Multiple aspects of the local extracellular environment profoundly affect cell phenotype and function. Physical and chemical cues in the environment trigger intracellular signaling cascades that ultimately activate transcription factors (TFs) – powerful regulators of the cell phenotype. TRACER (TRanscriptional Activity CEll aRrays) was employed for large-scale, dynamic quantification of TF activity in human fibroblasts cultured on hydrogels with a controlled elastic modulus and integrin ligand density. We identified three groups of TFs: responders to alterations in ligand density alone, substrate stiffness or both. Dynamic networks of regulatory TFs were constructed computationally and revealed distinct TF activity levels, directionality (i.e., activation or inhibition), and dynamics for adhesive and mechanical cues. Moreover, TRACER networks predicted conserved hubs of TF activity across multiple cell types, which are significantly altered in clinical fibrotic tissues. Our approach captures the distinct and overlapping effects of adhesive and mechanical stimuli, identifying conserved signaling mechanisms in normal and disease states.

Sodium ions, one of the natural inorganic constituents in lignocellulosic biomass, significantly alter pyrolysis behavior and resulting chemical speciation. Here, experiments were conducted using a micropyrolyzer to investigate the catalytic effects of NaCl on fast pyrolysis of glucose-based carbohydrates (glucose, cellobiose, maltohexaose, and cellulose), and on a major product of cellulose pyrolysis, levoglucosan (LVG). A mechanistic model that addressed the significant catalytic effects of NaCl on the product distribution was developed. The model incorporated interactions of Na+ with cellulosic chains and low molecular weight species, reactions mediated by Na+ including dehydration, cyclic/Grob fragmentation, ring-opening/closing, isomerization, and char formation, and a degradation network of LVG in the presence of Na+. Rate coefficients of elementary steps were specified based on Arrhenius parameters. The mechanistic model for cellulose included 768 reactions of 222 species, which included 252 reactions of 150 species comprising the mechanistic model of glucose decomposition in the presence of NaCl. © 2015 American Institute of Chemical Engineers AIChE J, 62: 766–777, 2016

A mechanistic model considering the significant catalytic effects of Na+ on fast pyrolysis of glucose-based carbohydrates was developed in Part 1 of this study. A computational framework based on continuous distribution kinetics and mass action kinetics was constructed to solve the mechanistic model. Agreement between model yields of various pyrolysis products with experimental data from fast pyrolysis of glucose-based carbohydrates dosed with NaCl ranging from 0–0.34 mmol/g at 500 °C validated the model and demonstrated the robustness and extendibility of the mechanistic model. The model was able to capture the yields of major and minor products as well as their trends across NaCl concentrations. Modeling results showed that Na+ accelerated the rate of decomposition and reduced the time for complete thermoconversion of carbohydrates. The sharp reduction in the yield of levoglucosan (LVG) from fast pyrolysis of cellulose in the presence of NaCl was mainly caused by reduced decomposition of cellulose chains via end-chain initiation and depropagation due to Na+ favoring competing dehydration reactions. Analysis of the contributions of reaction pathways showed that the decomposition of LVG made a minor contribution to its yield reduction and contributed less than 0.5% to the final yield of glycolaldehyde from fast pyrolysis of glucose-based carbohydrates in the presence of NaCl. © 2015 American Institute of Chemical Engineers AIChE J, 62: 778–791, 2016

The glass transition temperature (Tg) of a polystyrene (PS) nanolayer is shown to be strongly tuned by the presence of neighboring immiscible polymer layers over a 100 °C range spanning temperatures above and below the bulk PS Tg. Fluorescence spectroscopy is used to measure the glass transition temperature (Tg) of the ultrathin dye-labeled PS layers at specific regions within multilayer films of immiscible polymers. The Tg of a 14-nm-thick PS layer is 45 °C atop poly(n-butyl methacrylate) and 144 °C atop poly(4-vinyl pyridine). Additionally, the Tg of an 11- to 14-nm thick PS layer is shown to be the same as that reported by a near-infinitely-dilute PS blend component [Evans and Torkelson Macromolecules 2012, 45, 8319] with the same neighboring polymer, which indicates a common physical origin of Tg perturbations in both systems. The magnitude of Tg-confinement effects depends not only on the Tg of the neighboring domain but is also strongly correlated with neighboring domain fragility, a fundamental property of glass formers which provides a link between medium-range structural order and dynamics.

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 simula...

Chemicals with aldehyde moieties are useful in the synthesis of polymerization reagents, pharmaceuticals, pesticides, flavors, and fragrances because of their high reactivity. However, chemical synthesis of aldehydes from carboxylic acids has unfavorable thermodynamics and limited specificity. Enzymatically catalyzed reductive bioaldehyde synthesis is an attractive route that overcomes unfavorable thermodynamics by ATP hydrolysis in ambient, aqueous conditions. Carboxylic acid reductases (Cars) are particularly attractive, as only one enzyme is required. We sought to increase the knowledge base of permitted substrates for four Cars. Additionally, the Lys2 enzyme family was found to be mechanistically the same as Cars and two isozymes were also tested. Our results show that Cars prefer molecules where the carboxylic acid is the only polar/charged group. Using this data and other published data, we develop a support vector classifier (SVC) for predicting Car reactivity and make predictions on all carboxylic acid metabolites in iAF1260 and Model SEED.

The study of metagenomic samples is crucial for understanding microbial communities in ecosystems. In this study, genomic samples of the “El Coquito” acidic hot spring, located at the Nevados Natural National Park in Colombia, were analysed to evaluate the relationship between its metabolic functionality, and metabolic flows distribution considering the thermodynamic restrictions and the biogeochemical cycles through a flux balance analysis. The metabolic functionality of the metagenome was established by assigning reactions and enzymes to the metabolic routes. On one hand, we found that relevant metabolic groups contribute in a different fashion depending on the objective function of the ecosystem from the amount of metabolic reactions perspective. On the other hand, from the contribution to the total metabolic flow point of view, it seems the metabolic distribution plasticity conserves, as there exists several common groups that significantly contribute to the total metabolic flux of the system. Nevertheless, this plasticity is not maintained for all objective functions due to the differences between the nitrogen and the rest of the cycles, clearly demonstrating that the microbial adaptation capability to the ecosystem is materialized in the distribution of the metabolic flows instead of the frequency of appearance of the same reactions.

Elucidating the curing and aging mechanisms of alkyd and other oil-based paints is valuable for the fields of conservation and bio-based coatings. Recent research has demonstrated the limitations of artificial aging in predicting the actual properties of paints that are hundreds of years old. Kinetic modeling offers pathways to develop a realistic and dynamic description of the composition of these oil-based paint coatings and facilitates the exploration of the effects of various environmental conditions on their long-term chemical stability. This work presents the construction of a kinetic Monte Carlo framework from elementary steps for the cobalt-catalyzed autoxidative curing of an ethyl linoleate model system up to the formation of single cross-links. Kinetic correlations for reaction families of similar chemistry are employed to reduce the number of parameters required to calculate rate constants in Arrhenius form. The model, developed from mechanisms proposed in the literature, shows good agreement with experiment for the formation of primary products in the early stages of curing. The model has also revealed that the mechanisms proposed in the literature for the formation of secondary products, such as volatile aldehydes, are still not well established, and alternative routes are under evaluation.

Lignocellulosic biomass offers a vast, renewable resource for the sustainable production of fuels and chemicals. To date, a commonly employed approach to depolymerize the polysaccharides in plant cell walls employs mineral acids, and upgrading strategies for the resulting sugars are under intense development. Although the behavior of cellulose and hemicellulose is reasonably well characterized, a more thorough understanding of lignin depolymerization mechanisms in acid environments is necessary to predict the fate of lignin under such conditions and ultimately to potentially make lignin a viable feedstock. To this end, dilute acid hydrolysis experiments were performed on two lignin model compounds containing the α-O-4 ether linkage at two temperatures concomitant with dilute acid pretreatment. Both primary and secondary products were tracked over time, giving insight into the reaction kinetics. The only difference between the two model compounds was the presence or absence of a methyl group on the α-carbo...

Historical models for cellulose pyrolysis and mathematical approaches to kinetic analysis are reviewed with the objective of identifying the correct global chemical kinetic models and parameters for cellulose pyrolysis. In most recent experiments, cellulose pyrolysis clearly has sigmoidal reaction character, which is consistent with one of a sequential, nucleation–growth, or random-scission global model. The apparent activation energy of ∼47 kcal/mol is consistent with mechanistic modeling if one allows catalytic acceleration of the concerted initiation reaction. There is a possibility that part of the sigmoidal character is due to adsorption effects at low pyrolysis temperatures, but further work is required to resolve this issue. Reasons are given for why fitting data at a single heating rate to a first-order reaction model gives incorrect results.

Density functional theory (DFT) calculations were used to study the mechanism of CO2 hydrolysis by Co-(1,4,7,10-tetrazacyclododecane), also referred to as cobalt-cyclen, and evaluate the associated thermodynamic and kinetic parameters. A microkinetic model was then built based on the kinetics and thermodynamics derived from first principles. The intrinsic reaction rate constant was calculated to be 10572 M−1 s−1, three times larger than that of zinc-cyclen. The high activity was ascribed to a very large pKa value of 13.3. The monodentate structure of a key intermediate along the reaction coordinate, [Cyclen-Co-HCO3]+, was more stable than the bidentate isomer, due to a hydrogen bond formed between bicarbonate and the ligand. The reaction rate constant decreased significantly over 0–12 ms, which was attributed to the fast decrease of the concentration of the catalytic form, Co OH−. The conversion of CO2 at 1000 ms as a function of pH was calculated to compare the relative activity of zinc-cyclen and cobalt-cyclen, and zinc-cyclen was found to be a much better catalyst. Through calculating the ratio of the net rate to the forward rate of each elementary reaction, the rate-limiting step of the catalytic cycle was identified as the adsorption of CO2, which was the same as that for zinc-cyclen, though the product-releasing step was regarded as more difficult in cobalt-cyclen, compared to zinc-cyclen.

Fluorinated Fe-porphyrins, especially [tetrakis(pentafluorophenyl)porphyrinato]iron(III) chloride (tetrakis(pentafluorophenyl)porphyrinato = TPFPP) (TPFPP)FeCl (Fepor-2a), were found to be highly efficient for catalyzing the double epoxidation of divinylbenzene (DVB) to divinylbenzene dioxide (DVBDO), a novel component of epoxy resin formulation. The electronic properties of the catalysts are highly dependent on the substituents on the phenyl groups of these metalloporphyrins. The electron-rich fluorinated Fe-porphyrins are more selective toward epoxidation but are more vulnerable toward decomposition in H2O2. On the other hand, the electron deficient Fe-porphyrins are more stable, yet more Lewis acidic, which facilitates the formation of byproducts such as epoxide ring opening and overoxidation.

Motivation: The urgent need for efficient and sustainable biological production of fuels and high-value chemicals has elicited a wave of in silico techniques for identifying promising novel pathways to these compounds in large putative metabolic networks. To date, these approaches have primarily used general graph search algorithms, which are prohibitively slow as putative metabolic networks may exceed 1 million compounds. To alleviate this limitation, we report two methods—SimIndex (SI) and SimZyme—which use chemical similarity of 2D chemical fingerprints to efficiently navigate large metabolic networks and propose enzymatic connections between the constituent nodes. We also report a Byers–Waterman type pathway search algorithm for further paring down pertinent networks. Results: Benchmarking tests run with SI show it can reduce the number of nodes visited in searching a putative network by 100-fold with a computational time improvement of up to 105-fold. Subsequent Byers–Waterman search application further reduces the number of nodes searched by up to 100-fold, while SimZyme demonstrates ∼90% accuracy in matching query substrates with enzymes. Using these modules, we have designed and annotated an alternative to the methylerythritol phosphate pathway to produce isopentenyl pyrophosphate with more favorable thermodynamics than the native pathway. These algorithms will have a significant impact on our ability to use large metabolic networks that lack annotation of promiscuous reactions. Availability and implementation: Python files will be available for download at http://tyolab.northwestern.edu/tools/. Contact: k-tyo@northwestern.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Modeling of acid-catalyzed hydrocarbon conversion processes at the mechanistic level requires rate coefficients for a large number of reactions. The computational demand of finding activation energy barriers for each reaction is substantially reduced by employing structure–reactivity correlations such as the Evans–Polanyi relationship that correlates activation energy with the enthalpy of reaction. However, there are many species for which the enthalpies of formation are unknown. Therefore, group additivity methods to specify enthalpies of formation for each species involved in the reaction network are valuable. Quantum mechanical (QM) calculations and isodesmic reactions were used to calculate enthalpies of formation for a number of acyclic and cyclic carbenium ions, including allylic carbenium ions. These values compare favorably with experimental values, establishing Gaussian-4 as an accurate QM method for these calculations. Using these values, Benson-type group additivity values for enthalpies of for...

Biomass pyrolysis is a promising technology for the production of renewable fuels and chemicals from nonfood biomass. Given the potential of pyrolysis as a viable, cost-effective biomass deconstruction method, there is active interest in understanding the chemical transformations at the heart of the technology. It has long been known that the presence of alkali- and alkaline-earth-metal ions in biomass, such as Na+, significantly alters product yields of biomass pyrolysis, but the mechanism behind this effect has not been elucidated. In this work, we employ density functional theory (DFT) to reveal the stereoelectronic basis of the effect of sodium ions on several key glucose thermal decomposition reactions, such as the formation of levoglucosan and 5-hydroxymethylfurfural (5-HMF). β-d-Glucose is of interest for pyrolysis, as it is the monomer of cellulose and a key intermediate in cellulose pyrolysis. α-d-Glucose is included in this study, as the two anomers can readily interconvert under pyrolysis condi...

Developing reliable, predictive kinetic models of metabolism is a difficult, yet necessary, priority toward understanding and deliberately altering cellular behavior. Constraint-based modeling has enabled the fields of metabolic engineering and systems biology to make great strides in interrogating cellular metabolism but does not provide sufficient insight into regulation or kinetic limitations of metabolic pathways. Moreover, the growth-optimized assumptions that constraint-based models often rely on do not hold when studying stationary or persistor cell populations. However, developing kinetic models provides many unique challenges, as many of the kinetic parameters and rate laws governing individual enzymes are unknown. Ensemble modeling (EM) was developed to circumnavigate this challenge and effectively sample the large kinetic parameter solution space using consistent experimental datasets. Unfortunately, EM, in its base form, requires long solve times to complete and often leads to unstable kinetic model predictions. Furthermore, these limitations scale prohibitively with increasing model size. As larger metabolic models are developed with increasing genetic information and experimental validation, the demand to incorporate kinetic information increases. Therefore, in this work, we have begun to tackle the challenges of EM by introducing additional steps to the existing method framework specifically through reducing computation time and optimizing parameter sampling. We first reduce the structural complexity of the network by removing dependent species, and second, we sample locally stable parameter sets to reflect realistic biological states of cells. Lastly, we presort the screening data to eliminate the most incorrect predictions in the earliest screening stages, saving further calculations in later stages. Our complementary improvements to this EM framework are easily incorporated into concurrent EM efforts and broaden the application opportunities and accessibility of kinetic modeling across the field.

In this work, we carried out a comprehensive density functional theory (DFT) study on the basis of a trimer-to-tetramer radical reaction model to assess a cost-effective approach to perform the calculation of kinetic and thermodynamic properties of methyl methacrylate (MMA) free-radical homopolymerization. By comparing results from several different functionals (PBE, M06-2X, wB97XD, KMLYP, and MPW1B95), in conjunction with a series of basis sets (6-31G(d,p), 6-31+G(d,p), 6-31G(2df,p), 6-311G(d,p), 6-311+G(d,p), 6-311+G(2df,p), 6-311+G(2df,2p)), we show that calculations using M06-2X/6-311+G(2df,p)//B3LYP/6-31G(2df,p) provide an activation energy of 5.25 kcal mol(-1) for the homopropagation step, which is within 1 kcal mol(-1) of the experimental value. However, this method predicts a heat of polymerization of 17.37 kcal mol(-1) that is larger than the experimental value by 3.5 kcal mol(-1). MPW1B95/6-311+G(2df,p) on the B3LYP/6-31G(2df,p) geometries produces a heat of polymerization value within 1 kcal mol(-1) of experimental data, yet overestimates the activation energy by 3 kcal mol(-1). In addition, we evaluated the performance of ONIOM MO:MO calculations on the geometry optimization of species comprising our MMA polymerization model and found that ONIOM(B3LYP/6-31G(2df,p):B3LYP/6-31G(d)) is capable of producing geometries in very good agreement with the full B3LYP/6-31G(2df,p) calculations. Subsequent calculations of energies using M06-2X/6-311+G(2df,p) based on the ONIOM geometries provided an activation energy value comparable to that based on the full B3LYP/6-31G(2df,p) geometries.

Density functional theory (DFT) calculations were used to study the mechanism of CO2 hydrolysis by Zn-(1,5,9-triazacyclododecane) and Zn-cyclam and evaluate the associated thermodynamic and kinetic parameters. Microkinetic models were then built based on the kinetics and thermodynamics derived from first principles. Both catalysts showed very similar behavior to Zn-cyclen, which we have reported previously, but with multiple distinctions. The intrinsic reaction rate constants for Zn-(1,5,9-triazacyclododecane) and Zn-cyclam were calculated to be 2693 and 4623 M−1 s−1, respectively, which is in reasonable agreement with experimental values reported or estimated. The CO2 adsorption step was found to be a rate-limiting step for all three catalysts. Zn-cyclam has the lowest barrier for this step due to the highest pKa or nucleophilicity of the Zn-OH− form, and, therefore, the highest intrinsic activity. However, the observed reaction rate constant also depends on the availability of the catalyst. The decrease in the observed reaction rate constant over 0–12 ms was ascribed to the decrease in the concentration of the catalytic form, Zn-OH−, which was primarily converted to Zn-HCO3−. The reaction rate constant of Zn-cyclam dropped much faster than those of Zn-cyclen and Zn-(1,5,9-triazacyclododecane) due to lower energy of the Zn-HCO3− form. The conversion of CO2 at 1000 ms as a function of pH was calculated to compare the relative activity of these catalysts, and Zn-cyclen was found to be the best catalyst.

It is challenging to track explicit copolymer sequences and related measures using continuum kinetic models. We developed a generalized framework based on kinetic Monte Carlo (KMC) to model free radical polymerization of any number of monomers to obtain the explicit sequence and its distribution. The KMC framework was applied to copolymerization of butyl acrylate/methyl methacrylate (BA/MMA) and methyl acrylate/methyl methacrylate (MA/MMA), and the simulation output was compared with experimental results. Sequence characteristics that were not accessible via experiments were then predicted. Explicit monomer sequence information was used to construct operating diagrams to design a representative copolymer recipe with a specific sequence target as a function of molecular weight and monomer conversion.

Fast pyrolysis of lignocellulosic biomass, utilizing moderate temperatures ranging from 400 to 600 °C, produces a primary liquid product (pyrolytic bio-oil), which is potentially compatible with existing petroleum-based infrastructure and can be catalytically upgraded to fuels and chemicals. In this work, experiments were conducted with a micropyrolyzer coupled to a gas chromatography–mass spectrometry/flame ionization detector system to investigate fast pyrolysis of neat cellulose and other glucose-based carbohydrates. A detailed mechanistic model building on our previous work was developed for fast pyrolysis of neat glucose-based carbohydrates by integrating updated findings obtained through experiments and theoretical calculations. The model described the decomposition of cellulosic polymer chains, reactions of intermediates, and formation of a range of low molecular weight compounds at the mechanistic level and specified each elementary reaction step in terms of Arrhenius parameters. The mechanistic m...

A computational framework based on continuous distribution kinetics was constructed to solve the mechanistic model that was developed for fast pyrolysis of glucose-based carbohydrates in the first part of this study [Zhou et al. Ind. Eng. Chem. Res. 2014, 53. DOI 10.1021/ie502259w]. Comparing modeling results with experimental yields from fast pyrolysis over a wide range of reaction conditions validates the model. Agreement between model yields of final pyrolysis products with experimental data of fast pyrolysis of cellulose at temperatures ranging from 400 to 600 °C and maltohexaose, cellobiose, and glucose at 500 °C showed that the mechanistic model was robust and extendable. In comparison to our previous model [Vinu, R.; Broadbelt, L. J. Energy Environ. Sci. 2012, 5, 9808–9826], the mechanistic model presented in this work incorporating new findings from experiments and theoretical calculations showed enhanced performance in capturing experimental yields of major products such as levoglucosan-pyranose,...

Density functional theory (DFT) calculations were used to study the mechanism of CO2 hydrolysis by Zn-(1,4,7,10-tetraazacyclododecane), also referred to as zinc–cyclen, and evaluate the associated thermodynamic and kinetic parameters. A microkinetic model was then built based on the kinetics and thermodynamics derived from first principles. The model describes the sigmoidal dependence of the observed reaction rate constant on pH, which is similar to behavior observed for CO2 hydrolysis catalysts in nature, i.e., human carbonic anhydrase. The inflection point is identical to the pKa value of the zinc–cyclen complex, in good agreement with previous results. The overall reaction rate constant was calculated to be 3055 M−1 s−1, which is in excellent agreement with the range of experimental values reported (2691.5–3300 M−1 s−1). Importantly, though, the microkinetic model quantifies how the reaction rate and the associated overall rate constant varies as a function of time, underscoring that observed overall rate constants are a function of the species’ concentrations used to extract them, which may not be the initial conditions. The decrease in initial reaction rate over 0–12 ms was ascribed to the decrease in the concentration of the catalytic form, Zn-OH−, which was primarily converted to Zn-HCO3−. Through calculating the ratio of the net rate to the forward rate of each elementary reaction, the rate-limiting step of the catalytic cycle was identified as the adsorption of CO2. To aid in the interpretation of the complex microkinetic model, an analytical rate expression was derived based on a simplified potential energy surface comprised of three major regions: the adsorption of CO2, the release of HCO3− via displacement by water, and the deprotonation of Zn-H2O. Analysis showed quantitatively how the observed reaction rate constant depends not only on how fast a CO2 molecule is captured but also on how deep the Zn-HCO3− sits.

A novel computational framework that enables reactive flow simulation without using an a priori reaction mechanism is proposed in this work. The proposed computational framework is based on the integration of automated mechanism generation and on-the-fly reduction based on element flux analysis. Stepwise implementation of the integrated framework is developed to perform reactive flow simulations. The computational framework starts the simulation without any prior knowledge of the mechanism with only fuel and air as the initial species and performs the stepwise mechanism generation and on-the-fly reduction iteratively to obtain the entire simulation results. In each local computation step, a mechanism is generated automatically starting with the reduced mechanism at the end of the previous step, and flux-based on-the-fly reduction is applied to the generated mechanism to obtain reactive flow simulation results for the current step. The reduced mechanism at the end of the current step is then used as the st...

As biomass pyrolysis is a promising technology for producing renewable fuels, mechanistic descriptions of biomass thermal decomposition are of increasing interest. While previous studies have demonstrated that glucose is a key primary intermediate and have elucidated many important elementary mechanisms in its pyrolysis, key questions remain. For example, there are several proposed mechanisms for evolution of an important product and platform chemical, 5-hydroxymethylfurfural (5-HMF), but evaluation with different methodologies has hindered comparison. We evaluated a host of elementary mechanisms using a consistent quantum mechanics (QM) level of theory and reveal a mechanistic understanding of this important pyrolysis pathway. We also describe a novel route as a target for catalyst design, as it holds the promise of a more selective pathway to 5-HMF from glucose. We further demonstrate the effect of conformational and structural isomerization on dehydration reactivity. Additionally, we combined QM and ex...

Glycoside hydrolases (GHs) distort carbohydrate ring geometry along particular "catalytic itineraries" during the cleavage of glycosidic bonds, illustrating the relationship between substrate conformation and reactivity. Previous theoretical studies of thermodynamics of isolated monosaccharides offer insights into the catalytic itineraries of particular sugars. However, kinetic accessibility of carbohydrate puckering conformations and the role of exocyclic groups have not yet been thoroughly addressed. Here we present the first complete library of low-energy local minima and puckering interconversion transition states for five biologically relevant pyranose sugars: β-xylose, β-mannose, α-glucose, β-glucose, and β-N-acetylglucosamine. These were obtained by a thorough theoretical investigation each of the 38 IUPAC designated puckering geometries and all possible conformations of the exocyclic groups. These calculations demonstrate that exocyclic groups must be explicitly considered when examining these interconversion pathways. Furthermore, these data enable evaluation of previous hypotheses of why enzymes perturb ring geometries from the low-energy equatorial chair ((4)C1) conformation. They show that the relative thermodynamics alone do not universally correlate with GH catalytic itineraries. For some sugars, particular puckers offer both catalytically favorable electronic structure properties, such as anomeric carbon partial charge, and low kinetic barriers to achieve a given puckering conformation. However, different factors correlate with catalytic itineraries for other sugars; for β-N-acetylglucosamine, the key N-acetyl arm confounds the puckering landscape and appears to be the crucial factor. Overall, this study reveals a more comprehensive understanding of why particular puckering geometries are favored in carbohydrate catalysis concomitant with the complexity of glycobiology.

Tissue development and disease progression are multi-stage processes controlled by an evolving set of key regulatory factors, and identifying these factors necessitates a dynamic analysis spanning relevant time scales. Current omics approaches depend on incomplete biological databases to identify critical cellular processes. Herein, we present TRACER (TRanscriptional Activity CEll aRrays), which was employed to quantify the dynamic activity of numerous transcription factor (TFs) simultaneously in 3D and networks for TRACER (NTRACER), a computational algorithm that allows for cellular rewiring to establish dynamic regulatory networks based on activity of TF reporter constructs. We identified major hubs at various stages of culture associated with normal and abnormal tissue growth (i.e., ELK-1 and E2F1, respectively) and the mechanism of action for a targeted therapeutic, lapatinib, through GATA-1, which were confirmed in human ErbB2 positive breast cancer patients and human ErbB2 positive breast cancer cell lines that were either sensitive or resistant to lapatinib.

The three-point model and molecular simulation are used to understand the enantioselective adsorption of a homologous series of chiral compounds on a common chiral selector that is incorporated on a solid surface. We demonstrate how the enantioselectivity of homologous chiral compounds may go down, go up, remain the same, or even reverse. Conditions that lead to consistent enantioselectivity for homologous chiral compounds are also proposed.

In vitro follicle growth has emerged as a technology that can provide new information about folliculogenesis and serve as part of a suite of methods currently under development to assist women whose fertility is threatened by cancer treatments. Though it has been shown that in vitro-grown follicles secrete peptide and steroid hormones, much of the follicular transcriptome remains unknown. Thus, microarray analysis was performed to characterize the transcriptome and secretome of in vitro-grown follicles. One prominently regulated gene product was cartilage oligomeric matrix protein (Comp): its mRNA was upregulated during the final 4 days of culture (P < 0.05) and COMP protein could be detected in medium from individual follicles. COMP expression localized to mural granulosa cells of large antral follicles both in vitro and in vivo, with maximal expression immediately preceding ovulation in cycling and chorionic gonadotropin-primed female mice. COMP was co-expressed with two known markers of follicle maturation, inhibin β(A) and gremlin, and was expressed only in TUNEL-negative follicles. In addition to other gene products identified in the microarray, COMP has potential utility as a marker of follicle maturation.

Pyrolysis is a promising thermochemical technique to convert polymers such as waste plastics and lignocellulosic biomass to liquid products that are valuable either directly as or are potentially upgraded to liquid fuels and fine chemical intermediates. Mechanistically, polymer pyrolysis involves a complex set of free radical, concerted, and/or ionic reactions that occur via numerous competing pathways. Engineering these pathways to produce the required molecules warrant a thorough understanding of kinetics of the reactions under different conditions. In this critical review, after emphasizing the need for resource and energy recovery from polymers, the elementary reactions involved in the pyrolysis of polyolefins to various products are discussed along with an elucidation of detailed kinetic modeling. The reactions involved in oxidative pyrolysis of polymers are also discussed with polystyrene autoxidation as an example case. The influence of catalysts such as zeolites in altering the product distribution from pyrolysis of synthetic polymers is discussed. As lignocellulosic biomass is more complex in structure compared to synthetic polymers, the challenges and methodology involved in modeling the degradation of its basic constituents, viz. cellulose, hemicellulose, and lignin, to various organics are discussed. After elucidating the influence of various concerted reactions involved in cellulose pyrolysis on product yields, the effect of catalysts on biomass fast pyrolysis and bio-oil upgradation are discussed. The review concludes with a note on advantages of copyrolysis of synthetic polymers and biomass to enhance the quality of bio-oil that can be easily converted to biofuel with minimal upgradation.

Live-cell assays to measure cellular function performed within 3D cultures have the potential to elucidate the underlying processes behind disease progression and tissue formation. Cells cultured in 3D interact and remodel their microenvironment and can develop into complex structures. We have developed a transcription factor (TF) activity array that uses bioluminescence imaging (BLI) of lentiviral delivered luminescent reporter constructs that allows for the non-invasive imaging of TF activity in both 2D and 3D culture. Imaging can be applied repeatedly throughout culture to capture dynamic TF activity, though appropriate normalization is necessary. We investigated in-well normalization using Gaussia or Renilla luciferase, and external well normalization using firefly luciferase. Gaussia and Renilla luciferase were each unable to provide consistent normalization for long-term measurement of TF activity. However, external well normalization provided low variability and accounted for changes in cellular dynamics. Using external normalization, dynamic TF activities were quantified for five TFs. The array captured expected changes in TF activity to stimuli, however the array also provided dynamic profiles within 2D and 3D that have not been previously characterized. The development of the technology to dynamically track TF activity within cells cultured in both 2D and 3D can provide greater understanding of complex cellular processes.