Reaction Model Research Articles

An Algorithm for Creating a Synaptic Cleft Digital Phantom Suitable for Further Numerical Modeling

One of the most significant applications of mathematical numerical methods in biology is the theoretical description of the convectional reaction–diffusion of chemical compounds. Initial biological objects must be appropriately mimicked by digital domains that are suitable for further use in computational modeling. In the present study, an algorithm for the creation of a digital phantom describing a local part of nervous tissue—namely, a synaptic contact—is established. All essential elements of the synapse are determined using a set of consistent Boolean operations within the COMSOL Multiphysics software 6.1. The formalization of the algorithm involves a sequence of procedures and logical operations applied to a combination of 3D Voronoi diagrams, an experimentally defined inner synapse area, and a simple ellipsoid under different sets of biological parameters. The obtained digital phantom is universal and may be applied to different types of neuronal synapses. The clear separation of the designed domains reveals that the boundary’s conditions and internal flux dysconnectivity functions can be set up explicitly. Digital domains corresponding to the parts of a synapse are appropriate for further application of the derived numeric meshes, with various capacities of the included elements. Thus, the obtained digital phantom can be effectively used for further modeling of the convectional reaction–diffusion of chemical compounds in nervous tissue.

First-principles thermodynamical modeling of molecular reactions on α-U(001) and α-UH3(001) surfaces and their influence on hydrogen activation

Density functional theory calculations coupled with thermodynamic analysis have been performed to investigate the reactions of hydrogen and impurity gases including O2, CO2, CO, N2 on α-U(001) and α-UH3(001) surfaces. Binding strength of adsorbates on α-UH3 is calculated to be weaker than α-U, suggesting enhanced poisoning-resistant properties of U-hydride compared to its metallic state. Surface phase diagrams of U under binary H2-O2, H2-N2 and H2-CO gaseous environments show that while N and C elements prefer to stay in their hydrogenated states on the hydride surface, isolated O atoms favorably interact with both α-U(001) and α-UH3(001), indicating the heavily poisoning effect of impurities containing oxygen. Global optimization of partially oxidized α-U(001) slabs induces surface geometry reconstruction and the activity of oxidized surfaces toward hydrogen adsorption can be linearly correlated with local electronic and atomic properties of the adsorption site.

Statistical adiabatic channel model for termolecular reactions.

In this work, we present a statistical adiabatic channel model for termolecular reactions, A + B + C → Products. Our approach relies on hyperspherical coordinates, where the adiabatic channels are readily defined in the hyper-radius after averaging the hyperangular degrees of freedom. In this way, we find a general expression for termolecular rate constants. We focus on ion-neutral association reactions to test our approach's accuracy and predictive power, finding a good agreement between theory and experiment, especially in those reactions' temperature dependence.

Illuminating tandem reactions characterized by temporal separation of catalytic activities via DFT calculations: A case study of Ni-catalyzed alkyne semi-hydrogenation

The concept of “temporal separation of catalytic activities” outlines a scenario where multiple transformations within a catalytic tandem reaction proceed sequentially over time without mutual interference. After presenting several examples of such reactions, we specifically focus on an example of the Ni-catalyzed alkyne semi-hydrogenation as a significant case study. By performing density functional theory (DFT) calculations, we illuminate the unique dynamic character of the reaction that the intermediate remains dormant until the reactant exhausted. The insights gained from the present calculations have led us to propose a comprehensive energy landscape model for the catalytic tandem reactions with temporal separation of catalytic activities, which offers a logical explanation for the temporal dormancy of the intermediate. This class of reactions is expected to be highly valuable as it presents the opportunity to fine-tune individual reaction steps, thereby introducing fresh concepts for precise control of reactions in one-pot chemistry.

Shelf life and storage stability of cold plasma treated kiwifruit juice: kinetic models

ABSTRACT This study examined the quality changes and shelf life of cold plasma (Cold plasma-optimized, S2: 30 kV/5 mm/6.7 min and Cold plasma-extreme, S3: 30 kV/2 mm/10 min) and thermally-treated (S4: 90°C/5 min) kiwifruit juice packed in glass and polyethylene terephthalate bottles stored at 5, 15, and 25°C. Cold plasma and thermally treated juice samples were analyzed for peroxidase activity, microbial enumeration, bioactive compounds degradation, and sensory quality for up to 120 days. The residual activity of peroxidase enzyme in S2 sample after cold plasma treatment was 23.85%, decreasing with increase in storage time and temperature. After cold plasma and thermal treatment, the aerobic mesophiles and yeasts and molds count were below detectable limits in kiwifruit juice. Aerobic mesophiles and yeasts & molds emerged in S2, S3, and S4 samples stored at 5°C after 70, 70, and 90 days, respectively. The total color change increased with increase in storage time and temperature, whereas ascorbic acid, total phenolic content, total antioxidant capacity, and overall acceptability decreased. The shelf life of S2 in glass bottles was 100, 80, and 60 days at 5, 15, and 25°C based on total color change ≥ 12, ascorbic acid loss ≥ 50%, microbial count ≥ 6 Log CFU/mL, or overall acceptability < 5. Quality indices, including total color change, overall sensory acceptability, and ascorbic acid, were modeled, and zero-order model performed better than first and second-order reaction models. Furthermore, Arrhenius, Eyring, and Ball models were employed to model temperature-dependent reaction rates, and the Ball model performed better. So, the zero-order reaction and Ball model were combined to predict kiwifruit juice’s shelf life.

Exploring the Mechanisms and Kinetic Modeling of Phenol Amination Using Pd and Rh‐Based Catalysts

AbstractProducing biomass‐derived chemicals to substitute their petrochemical counterparts has long been an aspiration of the green chemistry research community. However, synthesizing secondary amines from biomass precursors presents several challenges related to catalyst nature and the mechanistic understanding of reaction systems. Here, we unravel the mechanistic and kinetic implications of the reductive amination of phenol with cyclohexylamine over Pd/C and Rh/C. A competitive Langmuir‐Hinshelwood reaction model well interpreted the kinetic data, suggesting that support‐metal interfaces serve as active sites for H2, ─NH2 and ═NH activation. The apparent activation energies for imine hydrogenation were 87.6 kJ mol−1 (Pd/C) and 34.5 kJ mol−1 (Rh/C), while ΔHads and ΔSads values confirmed the physicochemical consistency of the model. Moreover, the catalysts demonstrated their high stability to operate for several catalytic cycles, with minor activity losses due to metal leaching and partial sintering of Pd nanoparticles. Despite phenol reductive amination following similar mechanisms on Rh/C and Pd/C, they show differences in selectivity because the hydrogenation of imine is more efficient on Rh0 than on Pd0. This is the first mechanism‐oriented kinetic study for phenol reductive amination; thus, it provides valuable information for process design and scale‐up.

Sub-Ambient Performance of Potassium Sarcosinate for Direct Air Capture Applications: CO2 Flux and Viscosity Measurements

Absorption based direct air capture (DAC) technologies have garnered significant interest in recent years due to their scalability, competitive regeneration energy requirements, and low susceptibility to degradation. One of the key advantages of DAC lies in its flexible siting options and the potential to utilize low-value land. However, most of the research in this field has been focused on ambient climate zones (T > 20 °C), overlooking sub-ambient (−30 °C < T < 20 °C) regions, which comprise approximately 70 % of the Earth’s surface. To fully realize the potential of DAC, it is essential to understand how DAC solvents perform in these sub-ambient conditions before any large-scale deployment can be considered. Among DAC solvents of interest, potassium sarcosinate (K-SAR) has emerged as a promising candidate due to its high CO2 capacity, fast uptake kinetics, compatibility with contactor packing materials, low volatility, good thermal and oxidative stability, and competitive regeneration energy requirements compared to current industry standards. This paper characterizes the CO2 flux and viscosity of K-SAR at sub-ambient conditions and explores the potential of using ethylene glycol and triethylene glycol as additives to prevent solvent freezing in DAC applications. For 1 M K-SAR, the CO2 flux ranges between 1.3 × 10-5 and 8.0 × 10-5 mol m−2 s−1 across a temperature range of −5 °C to 45 °C. Ethylene glycol is shown to effectively suppress the freezing point of K-SAR below −30 °C with volumetric loadings of the additive as low as 0.1. A reaction model was developed to predict the CO2 flux for 1 M K-SAR at different temperatures, demonstrating good agreement between experimental and theoretical fluxes.

Bio-inspired synthesis of Cm-Ag/NiO nanocomposites: Enhanced photocatalytic degradation of textile dyes

This study successfully syntheses Cm-Ag/NiO nanocomposites (NCs) using an eco-friendly approach with Cucumis maderaspatanus L. leaf extract, highlighting a promising avenue for sustainable nanomaterial development. The nanocomposites were calcined at temperatures ranging from 300 to 700 °C to optimize their bandgap, achieving a value of 2.94 eV as determined by UV-Tauc plots. Characterization techniques revealed a face-centered cubic structure via X-ray diffraction, while transmission electron microscopy (TEM) showed uniformly spherical NCs with an average particle size of 7.1 nm. X-ray photoelectron spectroscopy (XPS) confirmed the elemental composition and oxidation states, while thermogravimetric analysis (TGA) and zeta potential measurements indicated robust thermal and colloidal stability. Photocatalytic experiments demonstrated degradation efficiencies of 83.16 % for the textile dye BB41 and 90.19 % for ROM2R under optimized conditions, with degradation kinetics following a first-order reaction model. Additionally, degradation products were identified via LC-MS, and toxicity was evaluated using ECOSAR software, shedding light on the environmental implications of our photocatalytic process. These findings establish Cm-Ag/NiO NCs as highly effective photocatalysts and sustainable solutions for addressing dye pollution in wastewater treatment, paving the way for innovative applications in environmental remediation.

Deeper insights into the devolatilization mechanism of biomass fixed-bed gasification under various atmospheres

In recent years, biomass oxy-fuel gasification has prompted increased interest for its ability to produce a gas with low tar content and to assist in carbon reduction. It is noteworthy that the type of atmosphere is a crucial factor influencing the devolatilization process in biomass gasification and the specific mechanisms by which an oxy-fuel atmosphere influences the devolatilization process remain inadequately explored. This work aimed to investigate the effect of various reaction atmospheres on devolatilization behavior, reaction kinetics, intermediate product formation, and biochar functional groups (BFGs) evolution. In comparison to an inert atmosphere, the oxy-fuel atmosphere facilitated the release of volatiles, and enhanced energy self-sustainability within the devolatilization system. The presence of O2 and CO2 promoted the generation of potential anhydrosugars while suppressing the formation of phenolic compounds. The synergistic effect present in the oxy-fuel atmosphere augments the exothermic effect and promotes the release of volatile and alkane gases during the devolatilization process. Furthermore, as oxygen concentrations increased in the reaction atmosphere, the sequential response of BFGs primarily followed the order: C-O → aromatic ring → C-OH/C–H/COO– → C=O. Moreover, advanced characterization analyses revealed that the oxy-fuel environment was more effective in promoting the aromatization and pore structure of biochar than an inert atmosphere. Collectively, these findings have substantial implications for reaction modeling in biomass fixed-bed gasification under real gas atmospheres and guide future research on tar control strategies.

A Machine Learning Model for Predicting the Propagation Rate Coefficient in Free-Radical Polymerization.

The propagation rate coefficient (kp) is one of the most crucial kinetic parameters in free-radical polymerization (FRP) as it directly governs the rate of polymerization and the resulting molecular weight distribution. The kp in FRP can typically be obtained through experimental measurements or quantum chemical calculations, both of which can be time consuming and resource intensive. Herein, we developed a machine learning model based solely on the structural features of monomers involved in FRP, utilizing molecular embedding and a Lasso regression algorithm to predict kp more efficiently and accurately. The result shows that the model achieves a mean absolute percentage error (MAPE) of only 5.49% in the predictions for four new monomers, which indicates that the model exhibits strong generalization capabilities and provides reliable and robust predictions. In addition, this model can accurately predict the influence of the ester side chain length of (meth)acrylates on kp, aligning well with established scientific knowledge. This approach offers a straightforward and practical model for other researchers to rapidly obtain accurate kp values by employing monomer structural information. The model is sufficiently general to apply to a wide range of (meth)acrylate and butadiene FRP monomers, thereby supporting kinetic modeling of polymerization reactions.

Synergistic Pd(OAc)2/CuI-catalyzed alkynylation of β-lactam derivative via Sonogashira coupling

Herein, a novel approach of bimetallic Pd(OAc)2/CuI-catalyzed alkynylation of 3-chloroazetidin-2-one (β-lactam derivative) with terminal alkyne via tandem C–C bond activation/Sonogashira-type cross-coupling reaction is developed. This synthesis encompasses a sequence of inert Csp3–X/Csp–H functionalization processes involving the coupling of the C(sp3) adjacent to the 3-chloroazetidin-2-one with the C(sp) of a terminal alkyne. The final analogs are synthesized by means of the indole-benzothiazole Schiff base formation, cyclization of the Schiff base to generate the β-lactam derivative, and Sonogashira coupling to afford a C(sp3)–C(sp) bond. In addition, indole, benzothiazole, and azetidine-2-one have been identified to be highly efficient heterocyclic scaffolds with a range of pharmacological benefits. It encouraged us to discover a hybrid compound that had each of these moieties. Cooperation between two different metals is essential for the successful implementation of this approach. Specifically, the interaction between the Pd and Cu centers in the transmetallation step is depicted through a plausible mechanistic route. The reaction conditions have been optimized by varying catalyst and ligand loadings, bases, temperatures, and solvents. The reaction is highly efficient, yielding alkynylated products in up to 84 % yield with a wide range of substrates and functional group tolerance, thereby serving as a functional model for the Sonogashira coupling reaction.

Numerical simulation of co-firing LRC and ammonia in Pangkalan Susu 3 & 4 coal-fired steam power plant (CFSPP) capacity 210 megawatts

The effort to reduce CO2 and NOx emissions plays a crucial role in mitigating climate change, improving air quality, complying with environmental regulations, and promoting clean technology innovation. Ammonia, as an emission-free fuel, shows significant potential as a co-firing agent with Coal in coal-fired steam power plants (CFSPP). Previous studies have demonstrated promising results in emission reduction through ammonia co-firing. This research presents a numerical analysis based on Computational Fluid Dynamics (CFD) to investigate the co-firing of ammonia with low-calorific Coal (LRC) in the CFSPP Pangkalan Susu Units 3 and 4, with a capacity of 210 MW. The study employs fluid flow modelling and chemical reaction analysis using the Discrete Phase Model (DPM) to provide accurate predictions of temperature distribution and pollutant concentrations in pulverized coal boilers. Cofiring simulations were conducted with ammonia additions of 5 % and 15 % on a calorific basis. Injection experiments from each burner (A-D) were performed to identify the optimal injection location. The simulation results indicate changes in combustion characteristics, particularly in temperature distribution. The main finding reveals a temperature decrease when ammonia is added as a co-firing material, attributed to the higher H2O content, which leads to increased moisture losses. In terms of efficiency, co-firing showed a decline compared to the baseline combustion of 100 % LRC coal due to the more significant moisture losses. The highest reduction in CO2 emissions was observed when 15 % ammonia was injected from burner B in case #6, with a mass fraction value of 0.171 at the boiler outlet. Similarly, the most significant reduction in NOx emissions occurred with a 15 % ammonia co-firing from burner B, yielding a mass fraction value of 8.81E-04 at the boiler outlet. This co-firing technology is expected to enhance decarbonization efforts and optimize the use of renewable energy in the future.

Digital model of biochemical reactions in lactic acid bacterial fermentation of simple glucose and biowaste substrates

As concerns about the environmental impacts of biowaste disposal increase, lactic acid bacterial fermentation is becoming increasingly popular. Current academic research is aimed at the process optimization by developing digital bioreactors. The primary focus is to develop a digital model mimicking the biochemical reactions. In the light of this, this paper intended to build a digital model of biochemical reactions during the fermentation process of both glucose and biowaste substrates, including white pasta and organic municipal waste. For this purpose, near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were used to collect spectral information during the fermentation process. Next, the samples were analyzed by High Pressure Liquid Chromatography (HPLC) to measure their glucose, fructose, arabinose, xylose, disaccharide, lactic acid, and acetic acid contents. The results showed that learning algorithms trained on MIR spectra accurately estimated the biochemical reactions for both glucose and biowaste substrates. For the glucose substrate, the results showed R-squared of 0.97 and RMSE of 4.69 g/L for glucose, and R-squared of 0.98 and RMSE of 2.74 g/L for lactic acid. In the case of biowaste substrate, estimations included glucose (R-squared = 0.97, RMSE = 4.69 g/L), fructose (R-squared = 0.88, RMSE = 1.47 g/L), arabinose (R-squared = 0.98, RMSE = 0.55 g/L), xylose (R-squared = 0.93, RMSE = 1.11 g/L), disaccharide (R-squared = 0.90, RMSE = 0.55 g/L), total sugar (R-squared = 0.98, RMSE = 3.79 g/L), lactic acid (R-squared = 0.98, RMSE = 2.74 g/L), and acetic acid (R-squared = 0.97, RMSE = 0.36 g/L). Regarding NIR spectral data, the predictive models were accurate when the substrate was glucose, however, they failed to accurately estimate the chemical reactions in the case of biowaste substrate. The findings of this study can be used to fulfill the requirements for a continuous fermentation process with the objective of maximizing lactic acid production.

Sustainable degradation of AZO dyes using green synthesized lead nanoparticles and solar energy

This study explores the green synthesis of lead nanoparticles and their application in degrading the AZO dye Nicoracine under solar irradiation. UV-Visible spectroscopy confirmed nanoparticle formation with a peak at 248 nm, indicating SPR. FTIR revealed functional groups from plant extracts aiding stabilization. XRD analysis showed a crystalline structure, while SEM and AFM indicated irregular shape and rough surface. The nanoparticles exhibited significant catalytic activity, enhancing Nicoracine degradation via solar light, facilitated by ROS generation. Kinetic analysis suggested a pseudo-first-order reaction model. This green synthesis method offers a sustainable solution for wastewater treatment and industrial pollution mitigation.

Pyrolysis characteristics and kinetic analysis of coating pitch derived from ethylene tar using model-free and model-fitting methods

This work conducted the pyrolysis of coating pitch derived from the ethylene tar through thermogravimetry analysis. The thermogravimetry-mass spectrometry and solid-state 13C nuclear magnetic resonance spectroscopy were performed to correlate the structural characteristics with the pyrolysis behavior. Meanwhile, the pyrolysis kinetics were estimated with model-free and model-fitting methods. The TG-DTG results showed that the pyrolysis process was generally divided into drying, fast pyrolysis, and polycondensation stages, accompanied by the decomposition of active functional groups like the aliphatic carbons bonded to oxygen (falO), the pyrolysis of relatively stable groups like the non-protonated aromatic carbon (faH), and the condensation of high bonding-energy aromatic structure like aromatic bridgehead carbon (faB). The activation energy obtained from model-free analysis ranged from 78.12 to 150.92kJ/mol with the increasing conversion, indicating the pyrolysis process as a multi-step reaction mechanism. Furthermore, the reaction model A1/3 (gα=[−ln(1−α)]3) was identified as the most suitable model for the pyrolysis of coating pitch in the conversion range of 0.25-0.8. The modeling values matched well with the experimental data, indicating the accuracy and feasibility of the results.

Development and Validation of a Clinical Prediction Model for Paclitaxel Hypersensitivity Reaction on the Basis of Real-World Data: Pac-HSR Score.

Paclitaxel is effective chemotherapy against various cancers but can cause hypersensitivity reaction (HSR). This study aimed to identify predictors associated with paclitaxel HSR and develop a clinical prediction model to guide clinical decisions. Data were collected from the medical records database of Rajavithi Hospital. Patients with cancer treated with paclitaxel from 2015 to 2022 were included, and a multivariable logistic regression analysis identified predictors associated with paclitaxel HSR. The scoring system was transformed and calibrated on the basis of diagnostic parameters. Discrimination and calibration performances were assessed. Internal validation was conducted using bootstrap resampling with 1,000 replications. This study involved 3,708 patients with cancer, with an incidence of paclitaxel HSR of 10.11%. An 11-predictor-based Pac-HSR scoring system was developed, involving the following factors: younger age; poor Eastern Cooperative Oncology Group performance status; previous history of paclitaxel HSR; medication allergy history; chronic obstructive airway disease; lung and cervical cancers; high actual dose of paclitaxel; no diphenhydramine premedication; low hemoglobin level; high WBC count; and high absolute lymphocyte count. The C-statistics was 0.73 (95% CI, 0.70 to 0.76), indicating acceptable discrimination. The P value of the Hosmer-Lemeshow goodness-of-fit test was 0.751. The ratio of observed and expected values was 1.00, indicating good calibration. At a cutoff point of 8, specificity was 75.28% and sensitivity was 57.07%. Internal validation indicated good performance with minimal bias, and decision curve analysis demonstrated improved prediction with the use of this scoring system in clinical decision making. This study developed the 11-predictor-based Pac-HSR scoring system for predicting paclitaxel HSR in patients with cancer. High-risk patients identified by this score should be prioritized for close monitoring and early treatment prophylaxis.

Geochemical modeling of diagenetic reactions between albitization of K-feldspar and plagioclase feldspar in sandstone reservoirs under the influence of CO2 partial pressure

Diagenetic albitization has been observed in sedimentary basins around the world. This process significantly changes the original composition of sandstones and the chemistry of the formation waters under the influence of partial pressure of CO2. The transformation of detrital feldspars into albite is considered a crucial diagenetic process in the Gulf Coast and North Sea reservoirs. Earlier studies suggest that plagioclase albitization typically happens before that of K-feldspar. In the Gulf Coast's Frio Sandstone, located in the Upper Oligocene at depths between 900 and 2400 m, detrital plagioclase is often dissolved and replaced by albite, while K-feldspar mostly dissolves without much substitution. Similarly, in the North Sea reservoirs, especially in the upper section of the Upper Triassic Lunde Formation at depths beyond 2900 m, plagioclase tends to undergo albitization, whereas K-feldspar remains largely unaffected or experiences minimal transformation. This research focuses on analyzing the differences in the albitization patterns of detrital and K-feldspar plagioclase through the KINDISP and Geochemist's Workbench (GWB) geochemical modeling tools, aiming to compare them. These diagenetic processes are crucial for reservoir geology, as they influence the concentration of silica in water, which, in turn, affects quartz cementation. This study aims to explore the variations in the albitization behavior of detrital and K-feldspar plagioclase using the KINDISP and Geochemist's Workbench (GWB) geochemical models and conduct a comparative analysis between them. Understanding these diagenetic reactions becomes relevant for reservoir geology analysis, as such phenomena control the aqueous silica concentration to some extent, which is consequently reflected in the quartz cementation. The dissolution of plagioclase and K-feldspar releases silica into the pore fluids. As the concentration of silica in the fluid increases, it leads to the precipitation of quartz as overgrowths on detrital quartz grains, a process known as quartz cementation. This was observed particularly in simulations involving temperature increases up to 150 °C, where the equilibrium between albite and anorthite was closely linked to the stability of quartz (Ben et al., 1993). The removal of feldspar through albitization reduces porosity and permeability but contributes silica to the system, which promotes quartz cementation. This, in turn, decreases the reservoir quality by filling pore spaces with secondary quartz, reducing the rock's ability to store and transmit fluids. Thus, the study highlights the importance of these diagenetic processes in reservoir evaluation, as the balance between feldspar dissolution and quartz cementation ultimately controls reservoir properties.

Quantifying the Temperature Dependence of the Multi-Species, Multi-Reaction Model: Part II. Estimation of Entropy Coefficient for Meso-Carbon Micro-Bead Graphite

In Part 1 of this paper, the temperature impact on the Multi-Species, Multi Reaction (MSMR) model was studied. This was accomplished by acquiring data from slow rate lithiation and delithiation of a meso-carbon micro-bead (MCMB) graphite. Through this analysis, the temperature impact on the total fraction of available host sites in a particular MSMR gallery (Xj), the impact on the reference potential ( Ujo ), and the impact on the parameter detailing the deviation from Nernstian behavior (ω j) was determined. Here, the intercalation material is discussed, compared to traditional methods of acquiring the entropy coefficient, and comparison is made to previous mathematical estimates. Some of the challenges in using temperature dependent constant rate charge and discharge data as compared to the potentiodynamic entropy coefficient calculation method are also discussed, and a recommendation for future applications is proposed.

Multiphase Reactions of Hydrocarbons Into an Air Quality Model With CAMx‐UNIPAR: Impacts of Humidity and NOx on Secondary Organic Aerosol Formation in the Southern USA

AbstractSecondary organic aerosol (SOA) mass in the Southern USA during winter‐spring 2022 was simulated by integrating Comprehensive Air quality Model with extensions (CAMx) with the UNIfied Partitioning‐Aerosol phase Reaction (UNIPAR) model, which predicts SOA formation via multiphase reactions of hydrocarbons. UNIPAR streamlines multiphase partitioning of oxygenated products and their heterogeneous reactions by using explicitly predicted products originating from 10 aromatics, 3 biogenics, and linear/branched alkanes (C9‐C24). UNIPAR simulations were compared with those using Secondary Organic Aerosol Partitioning (SOAP) model, which uses simple surrogate products for each precursor. Both UNIPAR and SOAP showed similar tendencies in SOA mass but slightly underpredicted against observations at given five ground sites. However, SOA compositions and their sensitivity to environmental variables (sunlight, humidity, NOx, and SO2) were different between two models. In CAMx‐UNIPAR, SOA originated predominantly from alkanes, terpenes, and isoprene, and was influenced by humidity, showing high SOA concentrations with wet‐inorganic salts, which accelerated aqueous reactions of reactive organic products. NO2 was positively correlated with biogenic SOA because elevated levels of nitrate radicals and hygroscopic nitrate aerosol effectively oxidized biogenic hydrocarbons at night and promoted SOA growth via organic heterogeneous chemistry, respectively. Anthropogenic SOA, which formed mainly via daytime oxidation with OH radicals, was weakly and negatively correlated with NO2 in cities. In CAMx‐UNIPAR, the sensitivity of SOA to aerosol acidity (neutral vs. acidic aerosol at cation/anion = 0.62) was dominated by isoprene SOA. The reduction of NOx emissions could effectively mitigate SOA burdens in the Southern USA where biogenic hydrocarbons are abundant.

Kinetics, catalyst design, and hydrodynamic analysis in Fischer–Tropsch synthesis: Fixed Bed vs Fluidized Bed Reactors

While fixed beds maximize contacting between the fluid and solid phase, commercial processes operate with fluidized beds for highly exothermic reactions, like Fischer–Tropsch (FT), to maximize heat transfer thereby minimizing catalyst sintering and deactivtion. However, conversion is lower due to gulf-streaming and poorer gas-solids contacting. In experimental reactors (<10mm) gulf-streaming is negligible and gas-solids contacting is excellent as bubbles are small. Here, we measure CO conversion over 3 FT catalysts—Fe/Ce/SiO2-K, Cu, Fe/Zr/SiO2-K, Cu, Fe/Catalox-K, Cu—across the same reactor operating in the fluidized bed and fixed bed regime. Flow rates were increased up to a maximum of 5 times the minimum fluidization velocity (Umf). The reactor operated at 2MPa, with a H2/CO molar ratio of 2, and 275°C≤T≤325°C. The average CO conversion was higher in the fixed bed but temperature control was more difficult, which could account for some of the differences. The highest ▪ selectivity (80% to 84%) was with the Fe/Catalox-K, Cu at 275°C, 2 to 4×Umf, in the fixed bed reactor. A first order reaction model characterized CO conversion well (R2>0.91) for the Fe-Catalox and Fe-Zr catalysts with activation energies >70kJmol−1. Conversion was essentially independent of temperature for the Fe-Ce composition in both the fixed bed and fluidized bed. BET surface area decreased 22% to 52% after the reaction. XRD analysis after the reaction revealed a 4% to 10% decrease in crystallinity, along with the presence of various Fe carbide compounds. Post-reaction SEM-EDS images indicated particle agglomeration and carbon deposition on the catalyst surface. Despite these morphological changes, the impact on CO conversion seemed minimal. Residence time distribution tests confirmed that gas was essentially in plug flow for both the fixed bed and fluidized bed configurations.