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At least 991 records · Page 55

Spatiotemporal 4D Whole-cell Modeling of a Minimal Autotroph Reveals Central Carbon Metabolism Regulated Locally by Protein Megacomplexes via Post-translational Modifications under Light Disturbance

Photosynthetic microorganisms rely on multiple pathways in central carbon metabolism to adapt to fluctuating light and energy availability across diel cycles. Mechanistic insight into the regulatory dynamics of this adaptation requires integrating processes spanning disparate timescales, from rapid redox-dependent post-translational modifications (PTMs) to slower changes in protein expression and metabolic pathway usage. To address this complexity beyond genome-based inference and traditional modeling, we develop a whole-cell four-dimensional (3D + time) model of the marine cyanobacterium Prochlorococcus marinus MED4 that explicitly represents the spatial organization of enzymatic and molecular processes in central carbon metabolism under light perturbation. We employ a perturbation-based research design to experimentally generate time-series, multi-omics measurements that provide molecular descriptors and cryo-ET derived 3D segmented volumes as constraints for this dynamic 4D framework. The integration of experiments and modeling across defined light regimes enables quantitative validation of system-level responses and forecasting under distinct light disturbances. We test the hypothesis that light-dependent redox PTMs regulating the structural assembly of a protein megacomplex, the “dark complex,” modulate metabolic flux at a conserved regulatory node of the Calvin–Benson cycle (CBC) in cyanobacteria. Our model shows that subcellular spatial organization buffers rapid light-induced changes in thylakoid reaction rates, which are followed by redox-PTM-mediated sequestration or release of CBC enzymes in the dark complex, ultimately impacting carbon fixation dynamics within carboxysomes. Comparison with an equivalently parameterized well-mixed stochastic model demonstrates that post-translational regulation not only buffers transcriptional noise and diffusion-driven fluctuations but also stabilizes phenotypic outcomes, underscoring the importance of spatial heterogeneity in phenotypic robustness. This ability to probe adaptive, spatiotemporally resolved mechanisms in photosynthetic machinery and central carbon metabolism addresses a critical gap in genotype-to-phenotype inference and expands modeling and design capabilities for understudied or genetically intractable autotrophs such as P. marinus MED4.

Johnson, Connah G.↗

A simplified CFD approach for modeling mass transport in catalytic open-cell foams

A simplified macroscopic CFD approach is presented to model mass transport including chemical reactions in washcoated open-cell foams. The foam is treated as a porous medium. Species conversion during chemical reactions is modeled using appropriate source terms based on reaction rate expressions and modified to account for the mass transport resistances occurring at the fluid-washcoat interfaces and within the washcoat layers. As example, the catalytic CO oxidation over platinum is studied. The simulation results show good agreement with experimental data from literature. A parametric study on washcoat parameters, such as thickness, tortuosity, porosity, and size, is carried out. Increasing the washcoat thickness from 5 to 100 µm or decreasing the tortuosity to porosity ratio from 5 to 20 decreases the CO conversion by 10 %. The proposed model is found to be reliable and has the advantage of lower computational cost, making it a suitable tool for foam-based catalytic reactor design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the integration of molecular dynamics, data science, and experiments for studying solvent effects on catalysis

Computational workflows that combine molecular dynamics (MD) simulations and emerging data-centric (DC) methods can accelerate the screening and analysis of solvent systems experimentally and computationally. Here, MD simulations provide atomic positions and velocities of reactant, solvent, and catalyst materials that can be manipulated into data representations that in turn can be used by DC techniques to conduct predictive modeling, feature extraction, and experimental design. For liquid-phase catalytic applications, emerging DC techniques such as Convolutional and Graph Neural Networks (CNN/GNN), Topological Data Analysis (TDA), and Active Learning (AL) can leverage MD and experimental data to quickly predict solvent effects on reaction outcomes. For instance, in recent studies, 3D solvent environments obtained with MD have been exploited by CNNs to predict experimental reaction rates for homogeneous acid-catalyzed lignocellulosic processes. In this perspective, we discuss basic principles of DC methods and how these can be combined with MD to enable high-throughput screening of solvent selection for diverse catalysis applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cloud based tool for analysis of chemical kinetic mechanisms

The size and complexity of chemical kinetic models used to simulate combustion of hydrocarbon fuels continue to increase with our improved understanding of the underlying physical mechanisms, along with the improved ability to utilize such models as the result of increased computational power and efficiency. As mechanisms grow beyond thousands of species and tens of thousands of reactions, it becomes increasingly difficult to manually check for errors and physical inconsistencies. In this work, we present several automated methods to check for such issues in the specification of chemical reaction models. First, we demonstrate how discontinuities in thermodynamic data can cause simulation difficulties manifested as long wall-clock times and convergence failures. To correct this type of problem, we describe an automated method for refitting thermodynamic parameters. We also outline several methods to check the timescales of reaction rate coefficients to ensure physical consistency. All the methods are made available through a web-based tool (https://combustiontools.llnl.gov) intended to aid mechanism developers and users to improve the accuracy and performance of fuel models used by the combustion community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗

Theoretically Informed Kinetics (ThInK): Establishing a modern C 0 -C 3 mechanism for combustion modeling

In contrast to the adage “Models are to be used, not believed”, combustion kinetics models have been intended to be predictive in nature. Theoretical chemical kinetics is now understood to provide a firm foundation for the reaction parameters, thereby facilitating predictive simulations of chemical reactivity, even in regimes that are poorly characterized by chemical kinetic and/or combustion experiments. In this study, we describe a theory-informed kinetics model (ThInK) for small molecule combustion chemistry (H 2 and C 1 – C 3 species) that is based on the prodigious use of theoretical predictions for reaction rate coefficients, thermochemistry, and transport parameters. The distinct features of this kinetics model, which was developed over the course of several decades, are illustrated through simulations of flame propagation and auto-ignition.

Energy transfer↗

Opportunities and challenges in process modeling and simulation of electrochemical systems

Electrochemical technologies have garnered intense interest in both academic research and industrial applications due to their potential to increase energy efficiency and reduce carbon footprint. However, electrochemical process fundamentals have been absent from the chemical process simulators available to millions of chemical engineers worldwide. To expedite process research and development of electrochemical technologies in the chemical industry, it is imperative that essential electrochemical process fundamentals be incorporated into process simulators to support modeling and simulation of electrochemical processes. Here, this study examines three process fundamentals key to the research and development of electrochemical processes: electrochemical reaction kinetics, electrolyte thermodynamics, and heat and mass transfer. It further illustrates application of these process fundamentals with a case study modeling an electrochemical process for the conversion of acrylonitrile to adiponitrile. The modeling example highlights the roles of applied voltage on reaction rates, and electron flow rates on the performance of electrochemical processes. It suggests that the applied voltage and electron flow rates are two unique concepts that should be included in simulators for electrochemical processes.

09 BIOMASS FUELS↗

Direct Discontinuous Galerkin methods for the reacting multi-component flow equations

The Direct Discontinuous Galerkin (DDG (Liu and Yan, 2008)) method and a counterpart with Interface Correction (DDGIC (Danis and Yan, 2022)) are extended to compute diffusion terms that arise when solving the compressible multi-component flow equations in thermochemical nonequilibrium. Thermodynamic properties, transport properties, chemical reaction rates, and energy exchange terms are computed using Mutation++ (Scoggins et al., 2020). The DG method is applied on unstructured grids, where the accuracy and convergence rates can be sensitive to the numerical method chosen for parabolic terms. A method for determining the homogeneity tensor of the flow equations required for DDGIC is shown. The convergence properties of the DDG methods are studied and compared to the Interior Penalty (IP) method. A number of numerical experiments are conducted to assess the accuracy and performance of the method. The numerical results and convergence studies indicate that DDG and DDGIC provide accurate solutions and perform well for general flows in thermochemical nonequilibrium.

Diffusion↗

Mechanism of $\mathrm{E}$-bridge formation by various $\mathrm{PAH}$ molecules: A theoretical study

Potential energy surfaces (PES) for dimerization of acepyrene-pyrene, aceanthracene-anthracene, and acenaphthalene-naphthalene were computed by the G3(MP2,CC) and ONIOM2(G3(MP2,CC):B3LYP/6-31G(d)) methods. Close agreement of relative energies of corresponding species along reaction paths for different reactions was found suggesting that the PES for E-bridge formation depends weakly on the number of rings in the interacting monomers. Our results indicate that the reaction rate is controlled by the dynamics of the initial collision, which may depend on the monomer size. The ONIOM approach is proposed as an accurate tool for calculations of PES in large PAH systems being more reliable than various DFT methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pyrolysis of bio-derived dioxolane fuels: A ReaxFF molecular dynamics study

Alkyl-substituted 1,3-dioxolanes, including 4,5-dimethyl-2-pentan-3-yl-1,3-dioxolane (Fuel 1), 4,5-dimethyl-2-pentyl-1,3-dioxolane (Fuel 2), and 2-(heptan-3-yl)-4,5-dimethyl-1,3-dioxolane (Fuel 3), have been recently suggested as potential biodiesels. In this paper, we investigate the initial pyrolysis of the alkyl-substituted 1,3-dioxolanes at high temperatures using ReaxFF molecular dynamics (MD) simulations. We analyze the decomposition rate, reaction mechanism, and product distribution in the pyrolysis of the three alkyl 1,3-dioxlanes. The three fuels primarily decompose to 4,5-dimethyl-1,3-dioxolane radical and hydrocarbons derived from the alkyl side-chains. The further decomposition of 4,5-dimethyl-1,3-dioxolane radical primarily leads to 2-C 4 H 8 and CO 2 within a few decomposition steps. The hydrocarbon product distribution is significantly affected by the molecular structure of the alkyl side-chain, which would have a strong influence on the sooting tendency of these fuels. The ReaxFF simulations predict that the order of sooting tendency would be Fuel 3 > Fuel 1 > Fuel 2, which agrees with the measured sooting tendency trend. Based on the pyrolysis mechanism identified by ReaxFF, we propose a new alkyl dioxolane, 4-hexyl-5-methyl-1,3-dioxolane (Fuel 4), which might produce even less soot, by modifying the molecular structure of Fuel 2. Our ReaxFF simulation shows that Fuel 4 produce much less C 4 H 8 , an effective non-aromatic soot precursor, than Fuel 2. Moreover, more carbon atoms are bonded to each oxygen atom in Fuel 4 than Fuel 2, which would help reduce soot yield by removing more carbon atoms from the soot-producing pool of species. The major decomposition pathways identified in this work can be used to develop chemical kinetic models for 1,3-dioxolane based compounds, as biodiesel components, applicable to combustion engine simulations. We also demonstrate that the chemical kinetic insight offered by ReaxFF simulations can be used to design new fuel molecules with more desired properties.

09 BIOMASS FUELS↗

The effects of turbulence on the flame structure and NO formation of ammonia turbulent premixed combustion at various equivalence ratios

Ammonia is carbon-free and is regarded as a potential fuel to address global warming issues. Here, in this work, three-dimensional direct numerical simulations (DNS) of ammonia/air turbulent premixed flames were performed to explore the influence of turbulence and equivalence ratio on the flame structure and NO formation characteristics. Two equivalence ratios were considered, i.e. Φ=0.9 and Φ=1.1. The general flame structures were presented and species distributions were examined. The NO mass fraction was found to be the highest in the product for the lean case and in the reaction zone for the rich case. The conditional mean values of species mass fractions and reaction rates were compared with those of the unstrained and strained laminar premixed flames to explore how well the laminar flame structures can approach those of the turbulent flame. The budget analysis of the species transport equations showed that turbulent diffusion plays an important role in species transport. The turbulent diffusivity D T was estimated using the gradient hypothesis based on the DNS data. Various laminar flame simulations with different diffusivities were carried out. It was shown that the conditional means of the DNS agree well with those of the laminar flames including D T in the transport property calculation. The global and local NO formation characteristics were investigated. It was found that the mean NO production conditioned on the progress variable is lower compared with the corresponding laminar flame in the rich case. However, the relative contributions from various NO pathways are rarely affected by turbulence. The NO mass fraction is higher in negative curvature regions compared with positive curvature regions of the flame surface for the rich case, which is due to the preferential diffusion of H 2 and other radicals and the enhanced NO pathways in negatively curved regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genetic algorithm optimization of a chemical kinetic mechanism for propane at engine relevant conditions

Propane has demonstrated significant potential for reductions in greenhouse gas and pollutant emissions in medium- and heavy-duty engine applications, but further improvements require accurate, compact, and scalable chemical kinetic mechanisms to design the next generation of propane fueled engines, particularly at the boosted operating conditions necessary to meet the power density demand of medium- and heavy-duty applications. In this work, six key chemical reactions were identified in a reduced mechanism with 70 species and 352 reactions through a sensitivity analysis performed at conditions typical of thermodynamic trajectories observed in a high compression ratio, long stroke engine operated on propane from throttled to boosted operating conditions. While the original mechanism was validated against rapid compression machine (RCM) data, it was found to overpredict experimental autoignition tendencies in 2-zone, 0-D SI engine simulations performed in Chemkin Pro. Subsequently, a genetic algorithm approach was used to optimize the six reaction rate parameters within established uncertainty bounds by performing RCM simulations and comparing to two independent sets of literature ignition delay times for propane, thus generating two new kinetic mechanisms. The first optimization achieved a mean absolute percent error (MPE) reduction in 2nd stage ignition delay of 61.4% in seven generations, while the second optimization utilized a newer experimental RCM dataset, and achieved MPE reduction of 56.7% in seven generations, and further marginal improvement to 57.8% reduction in 34 generations. Finally, the two mechanisms were then evaluated again in the 2-zone 0-D SI engine model in Chemkin Pro comparing typical mean and knocking cycle trajectories, and it was found that the second optimized mechanism provided better prediction of knock onset at the representative conditions evaluated in this work, particularly for higher load operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Skeletal reaction models for methane combustion

A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). Here, the sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic assessment of pulp mill-derived lime mud calcination in high CO 2 atmosphere

The chemical pulping of biomass involves the recycling of calcium through the calcination of lime mud, which is mostly comprised of calcium carbonate (CaCO 3 ). Lime mud decomposes under elevated temperatures to generate calcium oxide (CaO) and carbon dioxide (CO 2 ), the kinetics of which are strongly influenced by the CO 2 partial pressure and temperature. Oxy-fuel combustion and electrified lime kilns for lime mud calcination are intriguing methods to decarbonize this highly polluting operation within the biomass pulping industry. However, the high CO 2 concentration in oxy-fuel and electrified calcination processes alters the kinetics and overall reactivity of lime mud. For the first time, a model-fitting method is used to determine the kinetic parameters for lime mud calcination under a wide range of temperatures (550 °C–1250 °C) and under different concentrations of CO2 (0 %, 15 %, 50 %, and 90 %). A kinetic model is developed that accurately predicts the reaction rates as a function of temperature and CO 2 concentration. The apparent activation of energy for lime mud calcination is elevated under a high CO 2 environment. Relative to inert gas (N 2 , Ar), the temperature window for calcination is much smaller under high CO 2 environments. The presence of Na in lime mud does not seem to affect calcination under a high CO 2 environment. Finally, particle size variation does not have a significant effect on calcination under a high CO 2 environment.

09 BIOMASS FUELS↗

On the viability of stimulated hydrogen generation from iron-rich formations

Hydrogen-based technologies present a promising solution for the global energy transition. In addition to electrolytic production, subsurface geological formations provide a potential natural source of hydrogen. Iron-rich ultramafic rocks, in particular, are favorable for hydrogen generation through natural processes such as serpentinization. Naturally occurring reactions and migration can be enhanced through various types of stimulation, including thermal, hydraulic, and chemical treatment. Through numerical simulations, we analyzed the complex interplay of factors influencing the production and migration within the subsurface, emphasizing the importance of different stimulation techniques, catalysts, and conditions. Our findings indicate that key parameters, such as damage zone permeability and width, significantly impact producible hydrogen mass. Our results indicate that a combination of large damage zone widths, high permeability, and a stimulated reaction rate of 1 × 10 -9 can yield economically viable production rates of up to 1 kg s -1 at the wellhead. Moreover, the availability of ferrous iron, rather than the serpentinization rate itself, has been identified as the primary limiting factor in achieving economically sustainable hydrogen production. In conclusion, while an unstimulated rock volume of 0.165 km 3 yields only 45t of hydrogen in two years, various stimulation techniques can increase production to 18500t.

08 - HYDROGEN↗

In-situ microstructure observation of oxidized SiC layer in surrogate TRISO fuel particles under krypton ion irradiation

In accidental scenarios of high temperature gas-cooled reactors, both oxidation of and irradiation to the SiC layer in tri-structural-isotropic (TRISO) fuel particles can change the microstructure and integrity of the fuel elements. Here, in the present study, microstructure and defect evolution in the oxidized SiC layer of surrogate TRISO fuel particles under 1.2 MeV krypton ion irradiation was observed by in-situ transmission electron microscopy. The SiC layers oxidized in water vapor at 1200 °C were irradiated azt room temperature and 800 °C and at damage levels of 0.28–11.2 dpa, respectively. SiC and SiO 2 were found to still be in their crystal structures at the damage level of 11.2 dpa at 800 °C, while SiC was observed to have been amorphized at only 0.56 dpa irradiation at room temperature. The defect number density at 800 °C was an order of magnitude lower than that in the sample irradiated at room temperature. Also, crystalline SiO 2 had higher radiation resistance compared to SiC. A defect reaction rate theory was utilized to understand the fundamental defect evolution process and irradiation resistance difference.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The interplay between surface facet and reconstruction on isopropanol conversion over SrTiO 3 nanocrystals

Strontium titanate (SrTiO 3 ) is an extensively investigated perovskite for various applications due to its optical, electrical and chemical properties. To gain an in-depth understanding of the active sites involved in heterogeneous catalysis over the broadly used SrTiO 3 (STO), we studied a model reaction, isopropanol conversion, on three differently shape-controlled nanocrystals: cube, truncated cube and dodecahedra. SEM, XRD and XPS confirmed the morphology, phase and composition of STO shapes. Low energy ion scattering (LEIS) revealed the occurrence of surface reconstruction over STO shapes during O 2 pretreatment at different temperatures. Based on the catalytic activities, scanning transmission electron microscopy images and density functional theory calculations, the step sites on STO derived from surface reconstruction were proposed to be the active sites for isopropanol conversion. This was further confirmed by steady state isotopic kinetic analysis (SSITKA) which demonstrated similar intrinsic turnover frequencies (TOFs) for the differently reconstructed STO shapes. It is concluded that the crystal facets impose an indirect effect on the catalysis of STO via controlling the degrees of surface reconstruction: the less stable STO (1 1 0) facet (dodecahedra) leads to more step sites after reconstruction and hence higher overall reaction rate than the more stable (1 0 0) facet (cube). This work highlights the important interplay between the crystal facet and surface reconstruction in controlling the nature and density of active sties and thus catalysis over complex oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reprint of "Selective conversion of CO into ethanol on Cu(511) surface reconstructed from Cu(pc): Operando studies by electrochemical scanning tunneling microscopy, mass spectrometry, quartz crystal nanobalance, and infrared spectroscopy"

A polycrystalline copper, surface-terminated by a well-defined (511)-oriented facet, was electrochemically generated by a series of step-wise surface reconstruction and iterations of mild oxidative-reductive processes in 0.1 M KOH. The electrochemical reduction of CO on the resultant stepped surface was investigated by four surface-sensitive operando methodologies: electrochemical scanning tunneling microscopy (STM), electrochemical quartz crystal nanobalance (EQCN), differential electrochemical mass spectrometry (DEMS), and polarization-modulation infrared spectroscopy (PMIRS). The stepped surface catalyzed the facile conversion of CO into ethanol, the exclusive alcohol product at a low overpotential of -1.06 V (SHE) or - 0.3 V (RHE). Additionally, the chemisorption of CO was found to be a necessary prelude to ethanol production; i.e. the surface coverages, rather than solution concentrations, of CO and its surface-bound intermediates primarily dictate the reaction rates (current densities). Contrary to the expected predominance of undercoordinated step-site reactivity over the coordination chemistry of vicinal surfaces, vibrational spectroscopic evidence reveals the involvement of terrace-bound CO adsorbates during the multi-atomic transformations associated with the production of ethanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗