Reaction Model Research Articles

Turing instability in the Lengyel–Epstein fractional Laplacian system

This paper discusses a space-fractional version of the conventional Lengyel–Epstein CIMA reaction model. First, we prove the global existence, uniqueness, and boundedness of a unique solution. We next investigate the system fundamental analytic properties. Following this, we establish the conditions on the reactor size and diffusion coefficient such that the system does not allow positive steady-state solutions that are not constant. Finally, the stability of constant steady-state solutions for ODE and PDE models is studied.

Introduction of a consecutive first-order reaction model for soil nitrogen mineralization and derivation of parameters based on chemical analysis values

ABSTRACT A number of exponential models, classified as first-order reaction models, have been proposed for predicting the mineralization rate of soil organic nitrogen (SON). However, the considerable fluidity and uncertainty associated with the model parameters present a significant challenge. This issue is thought to be attributable to two principal factors: Initially, there is a discrepancy between the model structure and the actual phenomena. Secondly, the model parameters are derived from intra-model calculations. To address these issues, we propose introducing a consecutive first-order reaction model that embodies the recent paradigm for understanding soil nitrogen dynamics, namely the relationship between organic nitrogen (N) polymers, organic N monomers, and inorganic N, and further links the parameters to soil chemistry. The model comprises two discrete pools of SON, specifically persistent organic N (PON) and easily degradable organic N (EON). The model hypothesizes that PON is converted to EON, which then results in N mineralization. The first-order rate law was applied to both reactions. Concurrently, eight paddy soils that had been managed for two years and seven months under non-flooding (oxidative) conditions were maintained in an incubator under oxidative conditions at temperatures 20°C, 25°C, and 30°C for 511 days. N mineralization was quantified on 13 occasions The model parameters were calibrated in accordance with the soil chemistry. The capacity of the EON pool was found to be dependent on the contents of ATP (adenosine triphosphate) and LFN (light fraction N). The capacity of the PON pool was contingent upon the total N and EON pools. The reaction rate constant for PON was found to be a function of the acidic ammonium oxalate extracted aluminum content and pH, and the reaction rate constant for EON was observed to be a function of pH. The activation energies for both reactions were found to be constants specific to all soils, respectively. The root mean square error (RMSE) of the model calculation results for measured values from 0 to 409 mg kg−1 was as low as 6.9 mg kg−1, indicating that the model has robust predictive ability across a wide variety of soil types, temperatures, and incubation periods.

An Unstructured Mesh Reaction-Drift-Diffusion Master Equation with Reversible Reactions.

We develop a convergent reaction-drift-diffusion master equation (CRDDME) to facilitate the study of reaction processes in which spatial transport is influenced by drift due to one-body potential fields within general domain geometries. The generalized CRDDME is obtained through two steps. We first derive an unstructured grid jump process approximation for reversible diffusions, enabling the simulation of drift-diffusion processes where the drift arises due to a conservative field that biases particle motion. Leveraging the Edge-Averaged Finite Element method, our approach preserves detailed balance of drift-diffusion fluxes at equilibrium, and preserves an equilibrium Gibbs-Boltzmann distribution for particles undergoing drift-diffusion on the unstructured mesh. We next formulate a spatially-continuous volume reactivity particle-based reaction-drift-diffusion model for reversible reactions of the form . A finite volume discretization is used to generate jump process approximations to reaction terms in this model. The discretization is developed to ensure the combined reaction-drift-diffusion jump process approximation is consistent with detailed balance of reaction fluxes holding at equilibrium, along with supporting a discrete version of the continuous equilibrium state. The new CRDDME model represents a continuous-time discrete-space jump process approximation to the underlying volume reactivity model. We demonstrate the convergence and accuracy of the new CRDDME through a number of numerical examples, and illustrate its use on an idealized model for membrane protein receptor dynamics in T cell signaling.

Synthesis of n-Butene via Dimethyl Ether-to-Olefin Reaction over P-Loaded Ferrierite Zeolites

In the dimethyl ether (DME)-to-olefin (DTO) reaction over 20 types of P-loaded ferrierite zeolites with different P loading amounts, the synthesis of n-butenes such as 1-butene, trans-2-butene, and cis-2-butene was investigated to maximize the n-butene yield by optimizing the P loading amount. The zeolites were characterized using X-ray diffractometry (XRD), N2 adsorption-desorption isotherms, and NH3 temperature-programmed desorption (NH3-TPD). Micropore and external surface areas, total pore and micropore volumes, and weak and strong acids affected the DTO reaction’s characteristics. The P-loaded ferrierite zeolite with a P loading of 0.3 wt.% calcined at 500 °C exhibited an n-butene yield of 35.7 C-mol%, which exceeds the highest yield reported to date (31.2 C-mol%). Multiple regression analysis using the obtained data showed that the strong acid/weak acid ratio and total pore volume had a high correlation with the n-butene yield, with a contribution rate of 64.3%. Based on the multiple regression analysis results, the DTO reaction mechanism was discussed based on the proposed reaction model involving the dual-cycle mechanism.

Optimal Tax Policy of a Stage Structured Prey Predator Fishery: A Dynamic Reaction Model

In a fully dynamic model of an open-access fishery, the level of fishing effort expands or contracts according as the perceived rent (i.e., the net economic revenue to the fishermen) is positive or negative. A model reflecting this dynamic interaction between the perceived rent and the effort in a fishery is called a dynamic reaction model. In this paper, we study a dynamic reaction model, in which the prey species is subjected to harvesting in the presence of predator and it is assumed that an external agency regulates the fishery by imposing a suitable tax per unit biomass of landed fish. The fishing effort is taken as a dynamic variable depending on the capital invested in the fishery. The steady states and their stability are studied. The problem of the optimal tax policy is solved by Pontryagin’s maximum principle keeping the ecological balance. Keywords: Fisheries, Dynamic reaction, Prey-Predator system, harvesting, taxa- tion.

Congo Red Dye Removal from Aqueous Solutions by Photocatalytic Redox Reactions Using Anatase Nano-TiO2 as a Heterogeneous Catalyst: Degradation Kinetics and Simulation Using Dispersion Model

Water pollution caused by Congo red as a textile dye is a significant concern for the aquatic environment. The photocatalytic redox reactions were carried out in a closed batch photoreactor using 0.2 g/L Anatase nano-TiO2 as a catalyst to remove different initial concentrations (32, 71, and 178 ppm COD) of the dye from its neutral aqueous solutions at 40℃. The air was supplied to the reactor as an oxygen source at a rate of 0.2 L/min. The COD removal values decreased with the increasing initial dye concentration, and the best removal value was recorded (89.47 %) for the lowest initial COD (32 ppm) after 255 minutes of radiation. The kinetics study showed that the Congo red dye removal followed a first-order reaction model. A mathematical model was developed based on the axial dispersion phenomenon to simulate the product distribution of the dye through several types of reactors (ideal and nonideal plug flow and mixed flow reactors). Effects of initial concentration, dispersion number, and space-time on the organic distribution through the reactors were studied and discussed. The simulated results show that the ideal plug flow reactor (zero dispersion) performance was better than that of the nonideal plug flow reactor, and the performance decreased with the increasing dispersion number and gave the worst performance in the mixed flow reactor (infinity dispersion).

Risk factor screening and prediction modeling of gastrointestinal adverse reactions caused by GLP-1RAs

ObjectiveThis study aimed to explore the risk factors for gastrointestinal side effects (GISEs) in patients with type 2 diabetes mellitus (T2DM) during treatment with glucagon-like peptide-1 receptor agonists (GLP-1RAs) based on real-world data and to develop a prediction model for GLP-1RA-related GISEs.MethodsA total of 855 patients who attended the First Affiliated Hospital of Shandong First Medical University from January 2020 to May 2023 were selected as the study participants, who were divided into the training set (598 cases) and the validation set (297 cases) using a simple random sampling method at a ratio of 7:3. The general information and biochemical indicators of the participants were collected to assess the risk factors for GLP-1RA-related GISEs, and multifactorial logistic regression analysis was used to obtain the best predictors. A nomogram prediction model was constructed. The Hosmer–Lemeshow test was used to assess the differentiation and calibration of the nomogram model, and decision curve analysis (DCA) was used to evaluate the clinical utility of the model.ResultsAge, gender, history of gastrointestinal disorders, and number of combined oral medications were found as risk factors for the occurrence of GISEs in patients with T2DM using GLP-1RAs (p < 0.05). The nomogram prediction model based on these four factors had good discriminability (AUC values of the training and validation sets of 0.855 and 0.836, respectively) and accuracy (Hosmer–Lemeshow test: p > 0.05 for the validation set). DCA showed that the prediction model curve had clinical utility in the threshold probability interval of >5%.ConclusionsThe established nomogram model has an excellent predictive effect on GISEs induced by GLP-1RAs in patients with T2DM.

Chloride Interferences in Wet Chemical Oxidation Measurements: Plausible Mechanisms and Implications.

Wet chemical oxidation (WCO) methods measure total organic carbon (TOC) in aqueous solutions through the formation and detection of carbon dioxide (CO2). Prior research documents chloride (Cl-) interference during WCO. However, the mechanism that determines WCO interference is not established. We investigate WCO and find that formic acid exhibits TOC recovery (89-108%) within measurement uncertainty in the presence of Cl-, while acetic acid recovery is substantially reduced (3-67%). We postulate that chlorine radical (•Cl) formation during WCO alters oxidation pathways for organic compounds with methyl groups to form stable halogenated organic species that are thus not detected as CO2, reducing observed TOC recovery. We develop a kinetic model of elementary step reactions that reproduces observed TOC recoveries at multiple organic (1 and 5 ppm of C) and Cl- (>0.01 M) concentrations for both acetic and formic acids. Independent experiments with pyruvic acid and different halogen salts are consistent with the proposed mechanism. Our findings provide a plausible mechanistic explanation for Cl- interference in WCO-derived TOC measurements of environmental samples for which halogenated salts are present. A plausible mechanism provides a more complete understanding of how and why the TOC is biased low in environmental aquatic samples from saline environments when WCO is employed.

Solvent-free synthesis of citronellyl acetate using Fermase: Optimization, kinetics and RSM studies

Citronellyl acetate is a flavor ester with a fresh fruit aroma and a fruity, sweet flavor. The current study illustrates the synthesis of citronellyl acetate via a transesterification reaction of citronellol and vinyl acetate in a solvent-free system with the help of biocatalyst Fermase. The effect of various parameters affecting the reaction, including reactant mole ratio, enzyme loading, temperature, and agitation speed, was studied to obtain the maximum conversion of citronellol. Under optimized conditions with a 1:10 mole ratio of citronellol to vinyl acetate, 3% (w/w) enzyme loading with respect to citronellol, 300 RPM agitation speed, and 60 °C temperature, a maximum conversion of 99.8% was achieved in 2 h reaction time. The enzyme was reused for six reaction cycles, retaining 85% of its activity. Various kinetic models for enzymatic reactions were explored and validated. The ping-pong bi-bi model with both substrate inhibition gave the best fit for the experimental data. Optimization studies were also conducted using the response surface methodology to observe the interaction of various parameters.

Thermodynamics of coal oxidation mass gain behavior based on parallel reaction model by TG and DSC

Thermodynamics of coal oxidation mass gain behavior based on parallel reaction model by TG and DSC

Stern-Brocot arithmetic in dynamics of a biochemical reaction model.

A simple almost fifty year old four-variable model of the peroxidase-oxidase reaction has been studied using 2D isospike stability diagrams, 2D maximum Lyapunov exponent diagrams, and other nonlinear numerical methods. The model contains two positive feedback loops. For slightly different sets of parameters, compared to the original parameters, the model reveals a wealth of dynamic behaviors, not previously reported for this model. For example, contrary to expectations, the model is capable of reproducing all early observations of mixed-mode and bursting oscillations and chaos. Furthermore, for some parameters, the mixed-mode oscillations are organized according to Stern-Brocot arithmetic. The regions of mixed-mode oscillations are separated by narrow regions of chaotic dynamics.

Modeling and simulation of self-propagating exothermic reactions in Al/Ni reactive multilayer films and experimental validation

This paper reports the simulation and experimental validation of a MEMS (micro-electro-mechanical systems)-based Al/Ni reactive multilayer films (RMFs). A finite element model of a double V-shaped Al/Ni reactive multilayer films was developed by combining a thermoelectric coupling model with a self-propagating exothermic reaction model. The results show that the reactive multilayer films with a modulation ratio of 3:2 reach the energy peak the fastest under the same voltage excitation, which suggests that the modulation ratio determines the energy level of the reactive multilayer films before 20 μs, thus affects the energy output of the whole ignition process. Al/Ni reactive multilayer films with different modulation ratios were prepared using electron beam evaporation, the results of the ignition experiments showed that the reactive multilayer films with a modulation ratio of 3:2 had larger flames, which agreed with the simulated results. This suggests that calculating the enthalpy changes process of reactive multilayer films by coupling the self-increasing exothermic reaction can be used to analyze the chemical reaction process of the reactive multilayer films at any moment prior to 20 μs and to predict the flame size to some extent. This approach can be extended to other ignition prediction applications for MEMS-based ignitors.

Numerical study of the fuel rod melting and molten material migration behavior using the MPS method

The catastrophic consequences of nuclear reactor core meltdowns necessitate a comprehensive understanding of fuel rod behavior during severe accidents. This study employs the moving particle semi-implicit (MPS) method to simulate fuel rod melting and molten material migration, capturing complex phenomena such as phase changes, chemical reactions, and fluid dynamics. The developed MPS code integrates models for heat transfer, eutectic reactions, and surface tension, allowing for detailed three-dimensional simulations. Validation of the code is achieved through comparisons with analytical solutions and experimental data from the FROMA experiments. Simulations of Al–Zn substitute material rods show accurate temperature responses and phase transitions, highlighting the impact of radiation heat transfer and molten pool depth on melting behavior. Additional simulations of a single rod and a 2 × 2 rod bundle in a pressurized water reactor under extreme conditions reveal the significant role of atomic diffusion. Mass transfer between the cladding and fuel pellet expands the melting area and facilitates the formation of low-melting-point substances. The high-temperature behavior of the rod bundle demonstrates characteristic patterns, including the downward migration of molten zirconium and the dissolution of unmelted cladding. Analysis of molten UO2 migration within the rod bundle channel illustrates the influence of initial temperature and volume on migration dynamics and Zr cladding dissolution rates. This study offers valuable insights into understanding and mitigating the risks associated with core meltdowns, thereby enhancing nuclear reactor safety.

Experimental and kinetic studies on steam gasification of oxidized carbon-rich fraction from coal gasification fine slag

Gasification is an important method to realize the resource utilization of coal gasification fine slag (CGFS). In this work, the carbon-rich fraction (CF) of CGFS was modified by oxidation, and the gasification reactivities, structures, and kinetics of samples were studied. The results demonstrate that compared to CF, the gasification characteristic temperatures of oxidized CF are lower, the weight loss rates are faster, and the gasification reactivities are significantly enhanced. These improvements are attributed to the structural evolutions of oxidized CF. Compared with CF, the specific surface area and pore volume of oxidized CF increase by at least 2.5 and 1.5 times, the proportions of oxygen-containing groups rise, and the carbon microstructure of different oxidized CF varies significantly. CF oxidized by steam exhibits the most developed porosity and the most disordered carbon microstructure, corresponding to the highest gasification reactivity of all the samples. The kinetics results showcase that the diffusion reaction model is suitable for describing the gasification process of samples, so porosity emerged as the primary factor determining the gasification reactivity. However, the influence of carbon microstructure and active groups on the gasification reactivity of oxidized CF is enhanced when the porosity meets the diffusion requirements of the gasification reaction.

071 High-Fat Diet Promotes Chronicity of Skin Inflammation and IL-10 Resistance in a Murine Delayed-Type Hypersensitivity Reaction Model of Psoriasis

071 High-Fat Diet Promotes Chronicity of Skin Inflammation and IL-10 Resistance in a Murine Delayed-Type Hypersensitivity Reaction Model of Psoriasis

Molecular dynamics simulation of combustion reaction process and products of oxygen-containing functional groups in coal based on Machine Learning Potential

Oxygen-containing functional groups are the main heat source of coal spontaneous combustion, but their complex reaction pathways and microscopic mechanisms are still unclear. In this study, the molecular dynamics simulation of the composite combustion reaction model system with four oxygen-containing functional groups was conducted using the Machine Learning (ML) potential force field. The results showed that the stability order of these four oxygen-containing functional groups in the combustion reaction system is as follows: ‒OH < ‒COOH < ‒C‒O < ‒C=O. These simulation findings align with those obtained from in-situ FTIR experiments, thereby validating the accuracy of the ML potential force field. Notably, ‒C‒O exhibits the highest tendency for CO2 conversion (58.57%); ‒COOH displays the highest tendency for H2O conversion (45.00%); and ‒OH demonstrates the highest tendency for CO conversion (59.17%). The essence of the oxidative combustion reaction pathway involving oxygen-containing functional groups lies in the heat accumulation resulting from the oxidative dehydrogenation effect.

Exploring the kinetics and thermodynamics of TiFe0.8CrxMn0.2-x hydrogen storage alloys

The influence of Fe substitution by Cr and/or Mn on the hydrogenation properties of TiFe0.8CrxMn0.2-x hydrogen storage alloys was explored for several substitution amounts (x = 0, 0.05, 0.1, 0.15 and 0.2). The synthesized alloys consisted of a dominant TiFe (cubic, CsCl-type) and a secondary C14 Laves phase (hexagonal, MgZn2-type). The increase in Cr content, and consequently in C14 Laves phase fraction, improved the first hydrogenation kinetics and the hydrogen intake after activation (1.60–1.70 wt% H2 at 30 °C within 3 min), while substantially stabilizing the monohydride phase. The reaction enthalpy obtained from pressure-composition-temperature (PCT) curves hence increased along Cr substitution, ranging 24.35 ± 0.34 to 35.39 ± 1.00 kJmol-1 for the absorption, and 31.08 ± 1.39 to36.34 ± 1.99 kJmol−1for the desorption (absolute values). These experimental findings were in good agreement with density functional theory (DFT) predictions performed across the explored composition space. The estimated entropy values on the other hand remained nearly constant, fluctuating between 84.28 ± 4.76 and 102.64 ± 3.12 J mol−1 H2 K−1 for the absorption, and 100.46 ± 9.71 up to 105.45 ± 4.31 J mol−1 H2 K−1 for the desorption. Solid-gas reaction modeling showed that, under practical service conditions, the hydrogenation of activated alloys was interface-controlled followed by diffusion-controlled mechanisms as the reaction proceeded.

Co-firing characteristic prediction of solid waste and coal for supercritical CO2 power cycle based on CFD simulation and machine learning algorithm

The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO2 (S-CO2) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, and reduce pollutant emission. This study focuses on the co-firing characteristics of CSW and coal under S-CO2 power cycle, and simulations are conducted by employing Multiphase Particle-in-cell (MP-PIC) method integrated with the comprehensive chemical reaction models in a 300 MW S-CO2 CFB boiler. Effects of operating parameters including fuel mixture proportion and first stage stoichiometry on the gas emission characteristics are further analyzed. Based on training and testing database based on the simulation results, a novel Improved Whale Optimization Algorithm and Bi-dictionary Long Short-Term Memory (IWOA-BiLSTM) algorithm model is established to predict CFB temperature, NOx emission concentration, and SO2 emission concentration, respectively. Results show that CO and SO2 decrease with the coal mass ratio of the fuel mixture increasing, while NOx increases. With the increase of first stage stoichiometry, CO increases, NOx declines, and the change of SO2 is not obvious. Compared with two other basic algorithm models, the prediction error of the proposed algorithm model for the three targets is minimal with the average relative error of 0.032 %, 0.231 %, and 0.157 %, respectively, which can meet the prediction requirements with acceptable accuracy.

Study on the degradation of methyl orange by UV-acetylacetone advanced oxidation system

In recent years, Acetylacetone (abbreviated as AA) has garnered considerable scientific interest, particularly in the field of dye wastewater treatment due to its distinctive enol-keto structures. In this work,degradation of methyl orange(MO) by UV/AA process was explored. Effects of AA dosage, MO concentration, initial pH value and water matrices were investigated.Experimental results showed that under conditions of 298 K, a pH of approximately 5.73, a stirring speed of 1150 rpm, an initial MO concentration of 15 mg/L and an AA dosage of 0.5 mM, the decolorization rate reached nearly 98.4 % after 12 min of photolysis. The decolorization process fitted well with the pseudo-zero-order reaction model in the UV/AA system with an R2 value greater than 0.990. The reaction rate increases as the pH decreases; at approximately pH 2.0, the decolorization rate is 99.3 % after 6 min, while at approximately pH 9.0, it is only 41.2 %. 10 mM HCO3⁻significantly inhibit the system, 0.1 mM Cl⁻has a slight promoting effect at low concentrations but inhibits at high concentrations and NO3⁻inhibits the reaction while SO42- has minimal impact at a concentration of 0.1–10 mM .0.1 mM iron ions accelerated the reaction.The sodium citrate, a printing and dyeing auxiliary, has negative impacts on the MO degradation. Free radical capture experiments and Electron Paramagnetic Resonance (EPR) tests reveal that singlet oxygen (¹O2) is the primary active species in the UV/AA system. UV-Vis absorption spectroscopy indicates that azo bonds are largely destroyed after 12 min, with a decrease in AA concentration as the reaction proceeds. Liquid chromatography-mass spectrometry (LC-MS) results suggest a possible conversion pathway for MO during the UV/AA advanced oxidation process.

Development and characterization of advanced nano-coating with CeO₂, Al₂O₃, ZnO, and TiO₂ nanoparticles fWor enhanced durability and corrosion resistance

This study introduces an innovative sol-gel nano-coating designed to address silica scaling and corrosion in hydrothermal and high-stimulation environments. By incorporating CeO₂, Al₂O₃, ZnO, and TiO₂ nanoparticles into a polymer matrix through precise sonication techniques, the coating achieves uniform dispersion and enhanced functional performance. The meticulous characterization of nanoparticle integration optimizes mechanical strength, thermal stability, and chemical resistance. Applied via a directional supplying device, the nano-coating is mechanically deposited onto the cemented walls of wells, providing robust protection against scaling and corrosion across diverse conditions, including varying temperatures and pH levels. Laboratory testing demonstrates significant reductions in silica scaling and corrosion rates, confirming the coating's efficacy in maintaining production efficiency in both hydrothermal projects and fracking operations. This paper details the synthesis process and molecular chemistry involved in nanoparticle integration, alongside the resultant structural properties of the coating. Thermogravimetric analysis (TGA) assesses thermal stability, while kinetic models such as Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) evaluate activation energy without assuming specific reaction models. The findings highlight the potential of this advanced nano-coating as a robust solution for enhancing operational longevity and efficiency in challenging industrial applications.