Reaction Kinetic Model Research Articles

A carbon-based bifunctional heterogeneous enzyme: toward sustainable pollution control.

We present a study on an immobilized functional enzyme (IFE), a novel biomaterial with exceptional sustainability in enzyme utility, widely employed across various fields worldwide. However, conventional carriers are prone to eroding the active functional domain of the IFE, thereby weakening its intrinsic enzyme activity. Consequently, there is a burgeoning interest in developing next-generation IFEs. In this study, we engineered a carbon-based bifunctional heterogeneous enzyme (MIP-AMWCNTs@lipase) for the intelligent recognition of di(2-ethylhexyl)phthalate (DEHP), a common plasticizer. The heterogeneous enzyme contains a bifunctional structural domain that both enriches and degrades DEHP. We investigated its dual-response performance for the enrichment and specific removal of DEHP. The imprinting factor of the carrier for DEHP was 3.4, demonstrating selectivity for DEHP. The removal rate reached up to 94.2% over a short period. The heterogeneous enzyme exhibited robust activity, catalytic efficiency, and excellent stability under harsh environmental conditions, retaining 77.7% of its initial lipase activity after 7 cycles. Furthermore, we proposed a stepwise heterogeneous enzyme reaction kinetic model based on the Michaelis-Menten equation to enhance our understanding of enzyme reaction kinetics. Our study employs a dual-effect recognition strategy of molecular blotting and enzyme immobilization to establish a method for the removal of organic pollutants. These findings hold significant implications for the fields of biomaterials and environmental science.

Enhanced catalytic reductive hydrogenation of an organic dye by Ag decorated graphitic carbon nitride modified MCM-41.

Utilization of efficient, stable and reusable catalysts for wastewater treatment and catalytic elimination of toxic pollutants is a challenge among researchers. This present work shows the synthesis of high-surface-activity Ag nanoparticle decorated gC3N4 modified MCM-41 and its efficiency towards catalytic hydrogenation of organic dye in the presence of reducing agent NaBH4. The proposed mechanism is based on the transfer of H+ and 2e- between the dye and the catalyst. Adsorption of dye stuff on the catalyst is a rate-determining step and is accelerated by the MCM-41 support which enhances the surface area. The catalytic efficiency and optimum time requirement were examined through the adsorption-desorption equilibrium, pseudo-first-order reaction kinetic model for the dye. The result obtained was 98% catalytic efficiency followed by the catalytic hydrogenation reaction.

Electrochemical semi-hydrogenation of adiponitrile over copper nanowires as a key step for the green synthesis of nylon-6.

The industrial production of nylon 6 usually includes synthesizing caprolactam through the cyclohexanone-hydroxylamine route. This approach requires complex protocols, elevated temperatures, noble metal catalysts and the use of hazardous strong acids or hydroxylamine. Additionally, a significant quantity of ammonium sulphate is generated during the synthesis procedure. This study aims to develop an electrochemical reduction system for the conversion of ADN generated from the electrolytic dimerization of acrylonitrile (AN) to 6-aminocapronitrile (ACN), a precursor of nylon 6. This system utilizes a cost-effective Cu nanomaterial under eco-friendly conditions, avoiding lengthy and harsh processes, eliminating NH2OH use, and reducing low-value ammonium sulfate generation. This electrosynthesis method maintains approximately 85% ACN selectivity at 40-100 mA cm-2 when passing the charge required for 37% theoretical conversion. When extending the reaction time to achieve an 80% conversion, ACN selectivity still reached 81.6%, exceeding the theoretical value of non-selective hydrogenation by 20%. The pseudo-first-order reaction kinetic modeling proves that the reaction rate constant for ADN hydrogenation is significantly greater than that for ACN hydrogenation, highlighting the selectivity advantage of the system for ACN. This study establishes the foundation for developing a continuous electrolysis process to produce the nylon 6 precursor from AN feedstock.

Study of the interaction mechanism between the components of microalgae by thermal behaviors and pyrolysis characteristics

There is significant effect on thermal behaviors pyrolytic characteristics of the interactions between microalgal components. In order to understand the reaction process, interaction mechanism, and better utilization of microalgae, co-pyrolysis of microalgal model compounds (soybean protein (PT), sunflower oil (OL) and sucrose (SC)) was carried out with TG-FTIR and Py-GC/MS. The results showed that co-pyrolysis of PT and SC significantly changed the thermal behaviors, and accelerated decomposition at lower temperature to generate CO, CO2 largely. And it could promote the generation of linear O-compounds (such as acetic acid), and inhibit the formation of N-heterocycles and furans. Moreover, OL co-pyrolysis with PT or SC could significantly promote the formation of long-chain acid and inhibit the generation of aliphatics. Meanwhile, co-pyrolysis of PT and OL inhibited the generation of N-heterocycles. And co-pyrolysis of SC and OL accelerated the generation of furans. Furthermore, co-pyrolysis of model compounds reduced the average activation energy of the pyrolysis process, and changed the reaction kinetic model.

Changes in food quality and characterization under thermal accumulation conditions during Chinese cooking.

Chinese cooking is the primary treatment method for table food in China. The process is complex and large-scale, which is important to the macroeconomy and national nutrition and health. First, this article puts forward the concept of thermal accumulation for Chinese cooking by taking pork tenderloin fried at different oil temperatures, explaining changes in moisture content, hardness, and color with different thermal accumulation conditions, and measuring kinetic parameters. The variations of L* and b* obtained by the experimental results belong to the first-order reaction kinetic model, while the changes in water content and shear force belong to the zero-order reaction kinetic model. Simultaneously, the superheat value is used as a thermal accumulation indicator, combined with sensory evaluation to determine that the Z value of the human sensory overheating of pork tenderloin is 99°C, and O s,max (Z = 99°C, the reference temperature is 110°C) is 5.86 min.

Automation of the Formation of a Mathematical Formulation of Kinetics for Multistage Chemical Reactions and Numerical Solution to a Direct Problem

Introduction. The basis for research, analysis and mathematical optimization of any chemical process is an adequate mathematical model that takes into account the kinetics of the object. Kinetic analysis is a challenge in chemical technology, since it allows for optimizing synthesis processes and predicting their efficiency. Numerous chemical processes involve several stage reactions. For successful design and optimization, a mathematical model that describes each stage is needed. Creating such a model manually can be time-consuming and costly, since it requires processing a large amount of information. The modern level of automation makes it possible to accelerate the obtaining of a mathematical formulation of the kinetics of multistage reactions. In this case, working with data is greatly simplified, and the probability of making mistakes is reduced. The resulting mathematical model can be applied for further analysis and optimization of the process. The paper considers the industrial reaction of catalytic reforming of gasoline, which occupies an important place in the modern scheme of oil refining, since it is a source of high-octane components of commercial gasolines and individual aromatic hydrocarbons. This process is characterized by the participation of a large number (up to 300) of various hydrocarbons, a change in the number of moles, and non-isothermality in it. Mathematical modeling of such processes involves detailing the stages to the required level. The detailing of up to 173 stages is considered. In this setting, automation of the formation of a mathematical formulation of kinetics for catalytic reforming of gasoline has not been carried out before. Therefore, the presented work aimed at implementing effective numerical methods and algorithms for automating the building of a mathematical model taking into account kinetics, thermodynamics, and changes in the number of moles.Materials and Methods. The mathematical formulation of the kinetics of multistage reactions was developed on the basis of the mass action law. The kinetic parameters values were taken from literary sources. The direct kinetics problem was solved using algorithms: the Gear method, the Runge-Kutta method of the 4th order, and the scipy.odeint() method of the Python language. The automation concept was implemented using the IDEF0 methodology. The software was written in the Python programming language.Results. A new software was created to automate the process of forming a mathematical model, taking into account the kinetics, thermodynamics, and the volume of the reaction mixture. The program results were presented by the example of catalytic reforming of gasoline. The model implemented the possibility of taking into account the intermediate heating of the mixture in the reactor cascade. Numerical values of temperature changes corresponding to industrial data were obtained.Discussion and Conclusion. The results obtained through modeling chemical transformations in the cascade of gasoline catalytic reforming reactors confirmed the exothermic nature of the reaction. The developed software product provides displaying changes in the concentrations of reactants, as well as temperature variations in the reactor, and it can be used in scientific research organizations for the analysis of multistage catalytic processes. The results of the reaction kinetics modeling will be used in the subsequent optimization of the process conditions in production.

Improved prediction of reaction kinetics for amine absorbent-based carbon capture using reactive site-based transition state conformer search method

There is no doubt that carbon emissions are one of the greatest challenges facing humanity today. Carbon capture, utilization, and storage is an effective way to achieve carbon neutrality. However, the commonly used commercial absorbents for post-combustion captures still have some limitations such as low chemical absorption rate constants. In this paper, a universal reaction kinetic model is developed for amine-based carbon capture based on the transition state theory, density functional theory, and hybrid solvation model. The developed reaction kinetic model is applicable to a wide range of amine-solvent solutions involving primary/secondary/tertiary amines and aqueous/nonaqueous solvents. The key contribution of this work is developing a reactive site-based search method for the GENeration of Conformers for Transition States (GENConf-TS). GENConf-TS has greatly improved the prediction accuracy of the reaction kinetic model from R2 = 0.882 to R2 = 0.950 based on a dataset of 23 various amine-solvent solutions. The results highlight the critical impacts of the transition state conformational isomers on amine-based CO2 chemical absorption rate constants.

Energy and power characteristics of nanocatalyzed Belousov-Zhabotinsky reactions via bifurcation analyses.

Active stimuli-responsive materials, intrinsically powered by chemical reactions, have immense capabilities that can be harnessed for designing synthetic systems for a variety of biomimetic applications. It goes without saying that the key aspect involved in the designing of such systems is to accurately estimate the amount of energy and power available for transduction through various mechanisms. Belousov-Zhabotinsky (BZ) reactions are dynamical systems, which exhibit self-sustained nonlinear chemical oscillations, as their catalyst undergoes periodic redox cycles in the presence of reagents. The unique feature of BZ reaction based active systems is that they can continuously perform mechanical work by transducing energy from sustained chemical oscillations. The objective of our work is to use bifurcation analyses to identify oscillatory regimes and quantify energy-power characteristics of the BZ reaction based on nanocatalyst activity and BZ reaction formulations. Our approach involves not only the computation of higher order Lyapunov and frequency coefficients but also Hamiltonian functions, through normal form reduction of the kinetic model of the BZ reaction. Ultimately, using these calculations, we determine amplitude, frequency, and energy-power densities, as a function of the nanocatalysts' activity and BZ formulations. As normal form representations are applicable to any dynamical system, we believe that our framework can be extended to other self-sustained active systems, including systems based on stimuli-responsive materials.

Model-Based design of a novel process applicable to solution and slurry polymerization with phase change

This work aims on developing a novel process that is applicable to solution and slurry polymerization, which can efficiently control production efficiency, product properties and reactor thermal load through changing the flow ratios of cooled evaporation streams between different reactors. Furthermore, various process routes can be created by varying the destinations of cooled evaporation streams, markedly enhancing the process flexibility. To provide a thorough insight into the characteristics of the developed process, numerical simulations based on coupling the constructed models of polymerization reaction kinetics, thermodynamic properties and reactors are conducted to comprehensively study the impact of various factors (e.g., process routes, pressure, monomer and catalyst concentration, flow rates of cooled evaporation streams in different reactors) on the ethylene/1-octene solution copolymerization system with several stirred reactors connected in series. Some strategies for regulating production efficiency, product properties and reactor heat load of different process routes are obtained.

Co-precipitation of iron and silicon: Reaction kinetics, elemental ratios and the influence of phosphorus

A sufficient supply of dissolved silicon (DSi) relative to dissolved phosphorus (DP) may decrease the likelihood of harmful algal blooms in eutrophic waters. Oxidative precipitation of Fe(II) at oxic-anoxic interfaces may contribute to the immobilization of DSi, thereby exerting control over the DSi availability in the overlying water. Nevertheless, the efficacy of DSi immobilization in this context remains to be precisely determined. To investigate the behavior of DSi during Fe(II) oxidation, anoxic solutions containing mixtures of aqueous Fe(II), DSi, and dissolved phosphorus (DP) were exposed to dissolved oxygen (DO) in the batch system. The experimental data, combined with kinetic reaction modeling, indicate that DSi removal during Fe(II) oxidation occurs via two pathways. At the beginning of the experiments, the oxidation of Fe(II)-DSi complexes induces the fast removal of DSi. Upon complete oxidation of Fe(II), further DSi removal is due to adsorption to surface sites of the Fe(III) oxyhydroxides. The presence of DP effectively competes with DSi via both of these pathways during the initial and later stages of the experiments, with as a result more limited removal of DSi during Fe(II) oxidation. Overall, we conclude that at near neutral pH the oxidation of Fe(II) has considerable capacity to immobilize DSi, where the rapid homogeneous oxidation of Fe(II)-DSi results in greater DSi removal compared to surface adsorption. Elevated DP concentration, however, effectively outcompetes DSi in co-precipitation interactions, potentially contributing to enhanced DSi availability within aquatic systems.

Kinetic Study of Non-Isothermal Reactions on the Pyrolysis of Various Biomass Waste by using Thermogravimetric Data

Population growth causes an increase in the need for petroleum. However, petroleum as primary energy is currently increasingly limited in availability. Required alternative energy sources that can be renewed to overcome these problems, one of which is bio-oil. Bio-oil is produced by a pyrolysis process using biomass such as sugarcane bagasse, rice husk, and empty oil palm fruit bunches (EFB), by heating in the absence of oxygen. Kinetic studies on pyrolysis of this type of biomass (sugar cane bagasse, rice husk, and empty oil palm fruit bunches) were carried out using the thermogravimetric method. The Coats-Redfern method was used in this study. The purpose of this study is to obtain the most appropriate reaction kinetics model to represent the pyrolysis process for each type of biomass. In addition, to determine the optimal temperature used in forming bio-oil. Approximately 5 g of each biomass is used with a heating rate of 10°C/minute. Pyrolysis was carried out until the temperature reached 750°C. The results of the research on the selected kinetic model for each biomass is a geometric model with a correlation coefficient (R2) close to 1 and the optimum temperature for producing bio-oil is around 550 - 600°C.

Biological H2(g) Production and Modelling with Computational Fluid Dynamics (CFD)

In this study, bio-hydrogen gas [bio-H2(g)] production and modeling with a three-phase computational fluid dynamics (CFD) model, heat and mass transfer of bio-hydrogen production, reaction kinetics, and fluid dynamics; It was investigated by dark fermentation process in an anaerobic continuous plug flow reactor (ACPFR). The three-phase CFD model was used to determine the bio-H2(g) production in an ACPFR. The effect of different operating parameters, increasing hydrolic retention times (HRTs) (1, 2, 4, 8, and 12 days), different pH values (4.0, 5.0, 6.0, 7.0, and 8.0), and increasing feed rate as organic loading rates (OLRs) (0.5, 1.0, 2.0, 4.0, 8.0 and 10.0 g COD/l.d) on the bio-H2(g) production rates were operated in municipal sludge wastes (MSW) with Thermoanaerobacterium thermosaccharolyticum SP-H2 methane bacteria during dark fermentation for bio-H2(g) production. The effect of HRT, pH, and feed rate on the bioH2(g) efficiencies and H2(g) production rates were examined in the simulation stage. Production of volatile fatty acids (VFAs) namely, acetic acids, butyric acids, and propionic acids were important points influencing the bio-H2(g) production yields. The artificial neural network (ANN) model substrate inhibition on bio-H2(g) production to the methane (CH4) bacteria was also investigated. The reaction kinetics model used Thermotoga neapolitana microorganisms with the Andrews model of substrate inhibition. Furthermore, the ANN model was well-fitted to the experimental data to simulate the bio-H2(g) production from chemical oxygen demand (COD).

Green Synthesis of Stable and Reusable Zinc Nanoparticle Adsorbents for the Removal of Carcinogenic Heavy Metals in Aqueous Solution

industrial applications led to an alarming rise in their presence, heightening the potential for contamination in various environmental mediums. In order to mitigate the adverse impacts of these heavy metals, it is imperative to reduce their concentrations in environmental samples. Therefore, this study aimed to produce zinc nanoparticles employing Diospyros chloroxylon (Roxb.) to effectively eliminate carcinogenic metals from water. The produced nanoparticles were subjected to comprehensive characterization using FT-IR, XRD, SEM, and EDX techniques. The XRD data indicated the emergence of a hexagonal wurtzite structure. SEM images illustrated the spherical morphology of the synthesized particles, with an average diameter measuring 53 nm and having elemental zinc accounting for 69.4% of the composition. The subsequent heavy metal sorption experiments encompassed a range of variables, remarkably, the nanoparticles displayed exceptional adsorption capabilities, achieving maximum removal rates of 95.81%, 90.13%, and 91.25% within an equilibrium time of 90 minutes for Cr, Pb, and Cd, respectively. The adsorption process adhered to a pseudo-first-order reaction kinetics model, with high correlation coefficients of 0.9561, 0.99058, and 0.98481, along with respective rate constants (K) of 0.483, 0.233, and 0.328 for Cr, Pb, and Cd. The outcomes highlight that the synthesized zinc nanoparticles exhibit biocompatibility, stability, and reusability, making them a promising tool for effectively removing carcinogenic heavy metals from polluted water sources.

Study on the preparation of glycerylphosphorylcholine by transesterification under supported sodium methoxide

Abstract Glycerylphosphorylcholine (GPC) was prepared by transesterification using supported sodium methoxide as catalyst and natural lecithin as raw material. Sodium methoxide has been proved to be an effective catalyst for the preparation of GPC, which is easy to recover and reuse. After six repeated uses, its stability is satisfactory. The effects of agitation speed, catalyst dosage, and reaction temperature on the reaction were investigated, respectively, and the optimum conditions for preparing GPC catalyzed by supported sodium methoxide were found: the concentration of phosphorylcholine was 0.1 mol·L−1, the stirring speed was 600 rpm, the amount of catalyst was 7.5 g·L−1, the reaction temperature was 45°C, and the reaction time was 4 h; then, the conversion rate of phosphatidylcholine could reach 99%. At the same time, the reaction kinetic model was established based on the mechanism of the transesterification, and the experimental data were compared with the calculated values; it was found that the experimental data fitted the model well. Finally, the reaction activation energy obtained by the Arrhenius equation is 41.6 kJ·mol−1, which indicates that the supported sodium methoxide has good catalytic performance in this reaction system.

Assessing biochar's permanence: An inertinite benchmark

The natural removal of carbon dioxide and its permanent storage by the Earth system occurs through (i) inorganic carbon and (ii) organic carbon pathways. The former involves the “mineralization” of carbon and formation of carbonate minerals, whereas the latter employs the “maceralization” or natural carbonization of biomass into the “inertinite maceral”. The production of biochar is a carbon dioxide removal (CDR) method that imitates the geological organic carbon pathway, using controlled pyrolysis to rapidly carbonize and transform biomass into inertinite maceral for permanent storage. Therefore, the main challenge in assessing biochar's permanence is to ensure complete transformation has been achieved.Inertinite is the most stable maceral in the Earth's crust and is hence considered an ultimate benchmark of organic carbon permanence in the environment. Therefore, this study aims to measure the degree of biochar's carbonization with respect to the well-established compositional and microscopic characteristics of the inertinite. The random reflectance (Ro) of 2% is proposed as the “inertinite benchmark” (IBRo2%) and applied to quantify the permanent pool of carbon in a biochar using the Ro frequency distribution histogram. The result shows that 76% of the studied commercial biochar samples have their entire Ro distribution range well above IBRo2% and are considered pure inertinite biochar. The oxidation kinetic reaction model for a typical inertinite biochar indicates a time frame of approximately 100 million years for the degradation and loss of half of the carbon in the biochar. This estimate assumes exposure to a highly oxidizing environment with a constant surface temperature of 30°C, highlighting the inherent “permanent” nature of the material. In a less hostile environment, the expected permanence of inertinite is generally anticipated to be even longer.In addition to the inertinite that constitutes the largest fraction of the typical commercial biochar, an incompletely carbonized biochar may contain up to three other organic pools in descending order of stability. The relative concentration of these pools in a biochar can be quantified by a combination of geochemical pyrolysis and random reflectance methods. Furthermore, the Ro can be used to calculate the carbonization temperature (CT oC) of a biochar, which is the maximum temperature to which biochar fragments have been exposed during pyrolysis. This indicator provides important information about the efficiency of the carbonization process and subsequently the biochar's stability, with respect to production temperature (PT oC), heating residence time, and thermal diffusivity. Short summaryThe Earth's carbon dioxide removal and storage occur via inorganic and organic pathways: mineralization and maceralization. Biochar, imitating the organic pathway, undergoes controlled pyrolysis to transform biomass feedstock through a carbonization process into the inertinite maceral, which is a permanently stable form of organic carbon. Kinetic modeling in this study confirms inertinite's carbon stability over geological time scale.Assessing biochar's permanence hence hinges on achieving complete carbonization and transformation. Inertinite serves as the gold standard for organic carbon permanence, guiding this study to measure biochar's carbonization against inertinite characteristics. Analyzing the random reflectance (Ro) of biochar reveals that 76% of studied samples qualify as pure inertinite. Apart from inertinite, other organic pools in biochar, quantifiable through geochemical pyrolysis and Ro methods, affect stability. Determining the carbonization temperature offers insights into biochar's efficiency and stability concerning production variables.

Use of municipal solid waste incineration fly ash as a supplementary cementitious material: CO2 mineralization coupled with mechanochemical pretreatment

The use of municipal solid waste incineration fly ash, commonly referred to as “fly ash”, as a supplementary cementitious material (SCM), has been explored to mitigate the CO2 emissions resulting from cement production. Nevertheless, the incorporation of fly ash as an SCM in mortar has been shown to weaken its compressive strength and increase the risk of heavy metal leaching. In light of these challenges, this study aims to comprehensively evaluate the influence of CO2 pressure, temperature, and residual water/binder ratio on the CO2 uptake and compressive strength of mortar when combined with fly ash. Additionally, this study systematically examines the feasibility of mechanochemical pretreatment, which enhances the homogenization of fly ash and augments the density of the mortar's microstructure. The results indicate that the use of mechanochemical pretreatment leads to a notable 43.6% increase in 28-day compressive strength and diminishes the leaching of As, Ba, Ni, Pb, Se, and Zn by 17.9-77.8%. Finally, a reaction kinetics model is proposed to elucidate the CO2 sequestration process under varying conditions. These findings offer valuable guidance for incorporating fly ash as an SCM and CO2 sequestrator in mortar.

Integrated kinetics-computational fluid dynamic-optimization for catalytic hydrogenation of CO2 to formic acid

As enormous research findings indicate, carbon dioxide (CO2) can be converted to important products such as formic acid using catalytic hydrogenation of CO2 technologies. In this work a three-dimensional computational fluid dynamic (CFD) reactor model for the catalytic hydrogenation of CO2 to formic acid in the presence of triethylamine and water was developed, and the nature of the flow and reaction occurring inside the reactor was demonstrated. A kinetic model which estimates kinetic rate expressions was also developed and validated using experimental data. The kinetic parameters from the kinetic model were used as reaction source terms for the CFD reactor model development. Sensitivity analyses were performed on the design variables by integrating the kinetic parameters from the developed kinetic model. The Bayesian optimization algorithm was used to optimize the catalytic CO2 hydrogenation reactor. The optimal design was acquired, and the CO2 conversion increased by 32.6% compared to the initial base case. An optimized reactor design was proposed for the catalytic hydrogenation of CO2 to formic acid within a catalytic trickle-bed reactor based on the integration of reaction kinetic modeling and CFD analysis. The integrated kinetic-CFD-optimization framework proposed in this work was effectively applied to the catalytic CO2 hydrogenation reactor and the results reported on this work could give important design and operational insight to the further development of catalytic CO2 hydrogenation reactors for CO2 to formic acid conversion in carbon capture and utilization applications.

Numerical algorithm for finding the optimal composition of the reacting mixture on the basis of the reaction kinetic model

Numerical algorithm for finding the optimal composition of the reacting mixture on the basis of the reaction kinetic model

Comparative study on curing kinetics of MDI-based polyurethanes with different chain length diol curing agents

The difference in the reaction between thermosetting polyurethane (CPU) and binary alcohol system curing agents is crucial for obtaining accurate curing kinetics models and selecting curing agents. Based on a systematic comparison of the reaction activation energies and kinetic models of three different chain length fatty alcohol curing agents, ethylene glycol, 1,4-butanediol, and 1,6-hexanediol, the effect of curing agent chain length on the curing reaction was elucidated. Using differential and integral transformation methods to process non-isothermal DSC tests results, the effect of different chain lengths curing agents on the activation energy of MDI based polyurethane were analyzed. Based on the self-catalytic model, the segmented curing mechanism of the MDI based polyurethane systems were studied, and applicable high-precision segmented kinetic models’ parameters were calibrated. The optimal curing conditions for these systems were determined using extrapolation. The research results indicate that when the curing degree increases to 95 %, the overall activation energy of the MDI/1,4-butanediol system decreases by 47.1 %, accompanied by a faster self-catalytic. However, the activation energies of the other two systems, MDI/propylene glycol system and MDI/1,6-hexanediol system increased by 62. % and 295.0 %, respectively. This slows down the reaction rate of the two systems, which was 7.8 % and 10.9 % slower than the MDI/1,4 butanediol. heir molecular cross-linking network limits the diffusion ability of their chains and reduces the self-catalysis, resulting in slow reactions. These results will provide theoretical guidance and reference for the material formulation, process optimization of MDI based polyurethane actual curing production.

Dissolved organic carbon and dissolved oxygen determine the nitrogen removal rate constant in small water bodies of intensive agricultural region

Small water bodies are extensively distributed and play critical roles in nitrogen (N) removal, primarily through sediment denitrification. However, our comprehension understanding of the N removal rate constant in these systems, particularly within the first-order kinetics model, remains limited. To address this gap, a one-year field study was conducted to investigate the N removal rate and N removal rate constant in various small water bodies within a typical intensive agricultural area. We observed a decrease in N removal rates in the downstream direction, from ditches to downstream ponds and streams, potentially due to upstream water bodies receiving higher nutrient inputs. Moreover, our findings revealed that the N removal process in small water bodies generally follows a first-order kinetics reaction model, with the N removal rate constant varying from 0.22 d1 in streams and 0.48 d1 in vegetated ditches. Both water dissolved organic carbon (DOC) and dissolved oxygen (DO) concentrations collectively influenced the N removal rate constants. By leveraging the relationship between the N removal rate constant and these environmental factors, we further estimated that, on average, small water bodies remove 68% of the N loading in the Dongting Lake Basin. We recommend implementing artificial management measures, such as vegetation, to enhance the N removal capacity of water bodies. However, the caution must be exercised in measures like concrete linings in ditches, as they can hinder N removal. These findings not only offer methods for estimating N removal in small water bodies, but also provide an insight into enhancing the N removal capacity of these systems to effectively mitigate non-point N pollution.