Reaction Kinetic Parameters Research Articles

Identifying effective evolutionary strategies-based protocol for uncovering reaction kinetic parameters under the effect of measurement noises

BackgroundThe transition from explanative modeling of fitted data to the predictive modeling of unseen data for systems biology endeavors necessitates the effective recovery of reaction parameters. Yet, the relative efficacy of optimization algorithms in doing so remains under-studied, as to the specific reaction kinetics and the effect of measurement noises. To this end, we simulate the reactions of an artificial pathway using 4 kinetic formulations: generalized mass action (GMA), Michaelis–Menten, linear-logarithmic, and convenience kinetics. We then compare the effectiveness of 5 evolutionary algorithms (CMAES, DE, SRES, ISRES, G3PCX) for objective function optimization in kinetic parameter hyperspace to determine the corresponding estimated parameters. ResultsWe quickly dropped the DE algorithm due to its poor performance. Baring measurement noise, we find the CMAES algorithm to only require a fraction of the computational cost incurred by other EAs for both GMA and linear-logarithmic kinetics yet performing as well by other criteria. However, with increasing noise, SRES and ISRES perform more reliably for GMA kinetics, but at considerably higher computational cost. Conversely, G3PCX is among the most efficacious for estimating Michaelis–Menten parameters regardless of noise, while achieving numerous folds saving in computational cost. Cost aside, we find SRES to be versatilely applicable across GMA, Michaelis–Menten, and linear-logarithmic kinetics, with good resilience to noise. Nonetheless, we could not identify the parameters of convenience kinetics using any algorithm.ConclusionsAltogether, we identify a protocol for predicting reaction parameters under marked measurement noise, as a step towards predictive modeling for systems biology endeavors.

Two-Stage Global Biomass Pyrolysis Model for Combustion Applications: Predicting Product Composition with a Focus on Kinetics, Energy, and Mass Balances Consistency

This work presents a comprehensive model for lignocellulosic biomass pyrolysis, addressing kinetics, energy balances, and gas product composition with the aim of its application in wood combustion. The model consists of a two-stage global mechanism in which biomass initially reacts into tar, char, and light gases (non-condensable gases), which is followed by tar reacting into light gases and char. Experimental data from the literature are employed for determining Arrhenius kinetic parameters and key energy parameters, like tar and char heating values and the specific enthalpy of primary and secondary reactions. A methodology is introduced to derive correlations, allowing the model’s application to diverse biomass types. This work introduces several novel approaches. Firstly, a pyrolysis model that determines the composition of light gases by solving mass, species, and energy balances is developed, limiting the use of correlations from the literature only for tar and char elemental composition. The mass rate of light gases, tar, and char being produced is also determined. Secondly, kinetic parameters for primary and secondary reactions are determined following a Shafizadeh and Chin scheme but with a modified Arrhenius form dependent on Tn, significantly enhancing the accuracy of product composition prediction. Additionally, correlations for the enthalpies of reactions, both primary and secondary, are determined as a function of pyrolysis temperature. Primary reactions exhibit an overall endothermic behavior, while secondary reactions exhibit an overall exothermic behavior. Finally, the model is validated using cases reported in the literature, and results for light gases composition are presented.

Experimental and modeling studies on char combustion under pressurized O2/H2O conditions

The desorption kinetic parameters for pressurized combustion and gasification reactions were determined based on a C++ program coupled with the Langmuir-Hinshelwood (L-H) kinetic model developed and experimental data from pressurized char combustion, and the established L-H kinetic model for pressurized char-O2/H2O combustion was refined in the current paper. The activation energy for desorption in reactions involving pressurized char-O2 and char-H2O was determined to be 250.8 kJ/mol, accompanied by a pre-exponential factor of 5.42×1010 g/(m2 s). Using this foundation, the current research conducted simulations to investigate the impacts of temperature, pressure, and H2O concentration on the oxidation adsorption rate (Rads,oxi), desorption rate (Rdes), gasification adsorption rate (Rads,gas), and the competitive influences of kinetics and diffusion processes within the pressurized char-O2/H2O combustion. The simulation results indicate a gradual increase in Rdes and Rads,gas with char conversion to reach a peak, followed by a gradual decline. Conversely, the Rads,oxi varies smoothly throughout the char conversion process. At 1673 K/1.0 MPa, the char-O2/H2O reaction rate is primarily constrained by Rads,oxi and Rads,gas, with the adsorption reaction serving as the rate-controlling step. Moreover, it was noted that a rise in pressure resulted in a linear increase in Rads,oxi, Rdes, and Rads,gas. At elevated temperatures, the impact of pressure on them becomes more noticeable. However, the introduction of H2O mitigates this effect. Elevated temperature and pressure facilitate the competition on the kinetics of char-O2 combustion for O2 diffusion, resulting in the conversion of char being more susceptible to O2 diffusion rate limitation. With the addition of 20% H2O, the competition effect was weakened. In the case of pressurized combustion involving char and O2/H2O, the char conversion is primarily constrained by the O2 diffusion rate and is scarcely influenced by the H2O diffusion rate.

Study on A New Type of High Temperature Resistant Adsorption Type Retarded Acid System

Abstract Deep carbonate reservoirs present significant hurdles for reservoir stimulation due to extreme temperatures and rapid acid-rock reactions. The dense adsorption layer has the ability to postpone the interaction between rock and hydrogen ions, which is crucial for lowering the acid rock reaction rate. Based on the surfactant and film-forming agent’s synergistic impact, the retarding agent SH-1—which has the ability to generate a dense adsorption film on the surface of rock samples—was chosen for this study. After adding synergist and corrosion inhibitor, a new type of high temperature resistant adsorption type retarding acid system ’ 0.9% SH-1 + 20% HCl + 0.1% synergist + 1.5% corrosion inhibitor ’ was developed. The retarding performance of the retarding acid system at high temperature and various parameters of acid rock reaction kinetics were studied. The results show that the new adsorption-type retarded acid system can achieve good retarding effect at high temperature and ultra-high temperature, and the retarding rate is 90 % at 180 °C. In comparison to traditional hydrochloric acid, the new adsorption-type retarded acid exhibits a lower hydrogen ion mass transfer rate and a higher acid-rock reaction activation energy. These differences can effectively lower the acid-rock reaction rate. Additionally, an examination of the etching morphology reveals that the retarded acid is more easily etched along the cracks leading to the deep core. The novel adsorption-delayed acid offers excellent retarding power, high temperature resistance, and minimal damage. Consequently, it has certain reference value for the study of acidification transformation of ultra-high temperature deep carbonate reservoirs.

Analysis of the co-hydrogenation process of coal tar and kitchen waste oil based on reaction kinetics model

Kitchen waste oil (KWO) and coal tar (CT) are two commonly used alternatives to crude oil for fuel production through hydrogenation. If these two raw materials can be co-hydrogenated, it will help broaden the company's sources of raw materials. Therefore, in order to reveal the positive and negative impacts of the co-hydrogenation process of these two materials and to conduct a quantitative analysis of these phenomena, co-hydrogenation experiments of CT and KWO were completed in this study. The reaction kinetics parameters of the co-hydrogenation reaction were calculated. Experiments have shown that co-hydrogenation with coal tar hydrogenation products (CTHP) can increase the hydrogenation efficiency of KWO by approximately 1.5%. This promoting effect is mainly attributed to the hydrogen-supplying properties of compounds such as tetralin and hexahydro naphthalene present in the CTHP. Through a combined model of reaction kinetics and thermodynamics, it is calculated that the activation energy of KWO hydrodeoxygenation under the action of catalysts is 50.936kJ·mol-1, while under the action of CTHP hydrogen supply, it is 148.429kJ·mol-1, and this promoting effect accounts for 19.3% of the total reaction (as deduced from comparing reaction rate constants). The experimental data presented in this paper and the calculated reaction parameters can provide a basis for design improvements in technology.

DEVELOPMENT OF AN ALGORITHM FOR CALCULATING THE RATE CONSTANT OF HYDROCHLORIC ACID REACTION WITH A CARBONATE ROCK FORMATION

One of the main factors reducing acid stimulation efficiency is the intensive reaction of active acid in the immediate vicinity of the wellbore, which leads to insufficient completeness of reservoir rock dissolution in the remote reservoir zone. The reservoir hydrodynamic characteristics are not being improved properly, and the efficiency of oil production stimulation measures does not reach the planned values.To get high results of acid treatments it is necessary to achieve deep penetration of acid into the formation thickness. The reaction rate constant is used to compare the reactivity of different acid compositions and to select the most suitable acid composition for the geological and physical conditions of the treated object, which provides the highest treatment efficiency. It relates the initial substances concentrations with reaction products formation rate. To determine the reaction rate constant, a volumetric apparatus was created and methodological aspects were developed to work on it, allowing to minimize the measurement error and to achieve the greatest accuracy in determining the kinetic parameters of the reaction. But in the course of further investigations in the work of the existing algorithm for experimental data processing, a number of significant deficiencies distorting the results of calculations were revealed. The aim of the research is to develop a new improved algorithm for reaction rate constant calculation, which will improve the understanding of the process of determining the kinetic parameters of acid reaction with carbonate rock.To achieve this aim, the authors conducted a series of experiments according to the unified methodology, the results of which revealed ways to eliminate the identified deficiencies using a new algorithm. It includes obtaining and saving initial data, subsequent treatment and direct calculation of reaction kinetic parameters with results saving.The developed algorithm makes it possible to unify and automate the process of determining the kinetic parameters of the acid reaction with the formation rock, as well as to determine the reaction characteristics with higher accuracy and reduce the influence of the human factor on the research results, thus reducing the errors of the calculation results.

Composition changes and micro explosion characteristics of burning droplets formed by combustion of micrometer iron wires

To analyze the composition changes during the combustion process of iron droplets using the energy balance equation, iron wires with diameters of tens of micrometers were burned to form temperature-stable iron droplets with diameters of hundreds of micrometers. High-speed two-color imaging pyrometry was employed to measure the spatially resolved surface temperature and volume changes of the droplets under varying oxygen concentrations. Experimental results showed that the droplet's temperature stabilized between the melting points of wüstite and iron. Quantitative analysis revealed the presence of bubbles within the droplets, primarily sourced from the oxidation of carbon in the iron to carbon dioxide. Simulation results of the droplet combustion process revealed that at the experimental combustion temperatures, the transport of oxygen in molten iron oxides was the rate-limiting step. The gas responsible for micro-explosions originates from the release of dissolved excess oxygen before the solidification of molten iron oxides, with rough estimates indicating that the mass of the released gas is only 0.02% to 0.03% of the droplet mass. The impact of reaction kinetics parameters on the simulation results, as well as the role of the micro-explosion mechanism in the self-sustained combustion of iron wires, were also discussed.

A shelf life prediction model of Actinidia arguta ‘Chang Jiang No.1’ based on postharvest quality evaluation combined with fuzzy mathematics

Actinidia arguta has good taste and nutritional value. It is a climacteric fruit that is not durable during storage and has a short shelf life. To investigate the effects of storage and transportation on the quality of the early maturing variety Chang Jiang No. 1 (CJ No. 1), shelf life models were developed applicable at different temperatures. Fuzzy mathematics was used to evaluate the sensory senses of different storage stages at 2, 5, 15 and 25 °C, and the storage end-time was determined to be 35, 25, 15 and 10 days, respectively. All indices followed zero-order reaction kinetics (ΣR02 > ΣR12) and kinetic parameters k, A and Ea were calculated. Combined with the Arrhenius equation, a kinetic model was established based on key indices. The mean relative errors (MRE) of the key indices and shelf-lifeAll (SLAll) were less than 10% when comparing predicted and measured values. The weight of each index was determined using the Analytic Hierarchy Process (AHP), and a consistency test was conducted. Samples at 20 °C were selected to verify the model. The shelf life of CJ No.1 from 2 to 25 °C can be predicted according to the weighted model. The results of this study can help distributors and consumers determine the best time to eat A. arguta and the appropriate storage time. The ideas and methods of this study can also be promoted and applied to other fruit and vegetables to achieve a wider temperature range and a method of prediction of their shelf lives.

CRISPR/Cas13a analysis based on NASBA amplification for norovirus detection

Human norovirus (HuNoV) is a leading cause of foodborne diseases worldwide, making rapid and accurate detection crucial for prevention and control. In recent years, the CRISPR/Cas13a system, known for its single-base resolution in RNA recognition and unique collateral cleavage activity, is particularly suitable for sensitive and rapid RNA detection. However, isothermal amplification-based CRISPR/Cas13 assays often require an external transcription step, complicating the detection process. In our study, an efficient diagnostic technique based on the NASBA/Cas13a system was established to identify conserved regions at the ORF1-ORF2 junction of norovirus. The RNA amplification techniques [Nucleic Acid Sequence-Based Amplification (NASBA)] integrates reverse transcription and transcription steps, enabling sensitive, accurate, and rapid enrichment of low-abundance RNA. Furthermore, the CRISPR/Cas13a system provides secondary precise recognition of the amplified products, generating a fluorescence signal through its activated accessory collateral cleavage activity. We optimized the reaction kinetics parameters of Cas13a and achieved a detection limit as low as 51pM. The conditions for the cascade reaction involving CRISPR analysis and RNA amplification were optimized. Finally, we validated the reliability and accuracy of the NASBA/Cas13a method by detecting norovirus in shellfish, achieving results comparable to qRT-PCR in a shorter time and detecting viral loads as low as 10 copies/μL.

A Study of Hydroxyl-Terminated Block Copolyether-Based Binder Curing Kinetics.

In order to determine the curing reaction model and corresponding parameters of hydroxyl-terminated block copolyether (HTPE) and provide a theoretical reference for its practical application, the non-isothermal differential scanning calorimetry (DSC) method was used to analyze the curing processes of three curing systems with HTPE and N-100 (an aliphatic polyisocyanate curing agent), isophorone diisocyanate (IPDI), and a mixture of N-100 and IPDI as curing agents. The results show that the curing activation energy of N-100 and HTPE was about 69.37 kJ/mol, slightly lower than the curing activation energy of IPDI and HTPE (75.60 kJ/mol), and the curing activation energy of the mixed curing agent and HTPE was 69.79 kJ/mol. The curing process of HTPE conformed to the autocatalytic reaction model. The non-catalytic reaction order (n) of N-100 and HTPE was about 1.2, and the autocatalytic order (m) was about 0.3, both lower than those of IPDI and HTPE. The reaction kinetics parameters of the N-100 and IPDI mixed curing agent with HTPE were close to those of N-100 and HTPE. The verification results indicate a high degree of overlap between the experimental data and the calculated data.

MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction.

Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (kcat) and Michaelis constant (Km), key kinetic parameters for measuring enzyme catalytic efficiency, are crucial for analyzing enzymatic reaction mechanisms and the directed evolution of target enzymes. Experimental determination of kcat and Km is costly in terms of time, labor, and cost. To consider the intrinsic connection between kcat and Km and further improve the prediction performance, we propose a universal pretrained multitask deep learning model, MPEK, to predict these parameters simultaneously while considering pH, temperature, and organismal information. Through testing on the same kcat and Km test datasets, MPEK demonstrated superior prediction performance over the previous models. Specifically, MPEK achieved the Pearson coefficient of 0.808 for predicting kcat, improving ca. 14.6% and 7.6% compared to the DLKcat and UniKP models, and it achieved the Pearson coefficient of 0.777 for predicting Km, improving ca. 34.9% and 53.3% compared to the Kroll_model and UniKP models. More importantly, MPEK was able to reveal enzyme promiscuity and was sensitive to slight changes in the mutant enzyme sequence. In addition, in three case studies, it was shown that MPEK has the potential for assisted enzyme mining and directed evolution. To facilitate in silico evaluation of enzyme catalytic efficiency, we have established a web server implementing this model, which can be accessed at http://mathtc.nscc-tj.cn/mpek.

One‐dimensional kinetic model with novel bubble size equation in molten‐metal bubble column reactors for CH4 pyrolysis

AbstractNon‐oxidative methane pyrolysis produces hydrogen and solid carbon without CO2 in molten‐metal bubble column reactors (MMBCRs). One‐dimensional MMBCR models, which involve bubble hydrodynamics, reactions, heat transfer, and axial dispersion, have been developed for reactor design; however, empirical equations of the mean bubble size derived from bench‐scale experiments have also been used for industrial‐scale MMBCRs. In this study, a novel bubble size equation based on dimensionless numbers was proposed for the bubbling, transient, and slugging flow regimes, which is applicable to both bench‐ and industrial‐scale reactors. Using the MMBCR model coupled with the new bubble size, reaction kinetic parameters were identified for four bench‐scale MMBCRs with Te‐based alloys in the bubbling flow regime. In four industrial‐scale MMBCRs at 980°C, belonging to the transient flow regime for an H2 production of 10,000 Nm3/h, the bubble size and methane conversion were approximately 40 mm and under 35%, respectively.

Characterization of oxygen initiation process in the autothermic pyrolysis in-situ conversion of Huadian oil shale

The oxygen initiation process, one of the key processes in the early stage of the autothermic pyrolysis in-situ conversion technology, has not been deeply investigated, which seriously limits its development. In this study, the reaction behaviors, kinetic parameters, heat and product release characteristics during the isothermal oxygen initiation process of Huadian oil shale in O2/N2 mixtures with different oxygen concentrations and initiation temperatures were investigated via TG/DSC-FTIR. The results show that the samples exhibit three different reaction behaviors during the initiation stage, consisting of two main parts, i.e., the oxidative weight-gain and the oxidative reaction phases. The former phase is mainly characterized by the oxygen addition reaction that produces oxidizing groups which increase the sample mass. And the latter stage consists of two main subreactions. The first subreaction involves the oxidative cracking and pyrolysis of oxidizing groups and kerogen to produce fuel deposits such as residual carbon, while the second subreaction focuses on the oxidation of the resulting fuels. Furthermore, increasing the oxygen concentration significantly promotes the above reactions, leading to an increase in the reaction intensity and reaction rate. Owing to the combined effect of oxygen concentration and residual organic matter content, the total heat release increases with the increasing initiation temperature and reaches its maximum at 330–370 °C. In addition, the preheating stage primarily produces hydrocarbon gases, while the initiation stage predominantly generates CO2. As the preheating temperature increases, the CO2 output intensifies, the required reaction time shortens, and the release becomes more concentrated. Based on these findings, a reaction mechanism for the oxygen initiation process of Huadian oil shale was proposed, and recommendations were provided for optimizing the construction process.

Flue gas desulfurization by natural recyclable manganese ore in packed bed reactor and its performance prediction by random pore model

Various grades of manganese dioxide ores, as a natural recyclable sorbent, can be used in dry flue gas desulfurization (FGD) at moderate temperatures (350–450 °C). This research provided low- and high-grade manganese dioxide ores to examine SO2 removal in a packed bed reactor. To obtain characteristic parameters of mineral sorbents, XRD, XRF, BET, and mercury porosimetry were employed. Then, kinetic parameters of desulfurization reaction were determined using thermogravimeter analyzer (TGA) and random pore model (RPM) for a single pellet. In desulfurization experiments of simulated flue gas in a packed bed reactor and mass spectrometer (MS) apparatus, the breakthrough times were measured under various operating conditions. The onset of these breakthrough times or life-time of MnO2 reactor for the SO2 removal was predicted successfully by RPM for a packed bed reactor using related kinetic constants from TGA. In addition, reacted sorbets were recycled multiple times after washing with water. Not only does this simple method separate MnSO4 from unreacted sorbents as a valuable byproduct to reduce the FGD cost, but it also improves pore size distribution (PSD) of mineral MnO2 by creating large pores. Modified PSD of this recycled sorbent caused increased breakthrough time.

Immobilized lipase based on SBA-15 adsorption and gel embedding for catalytic synthesis of isoamyl acetate

In this study, Candida rugosa lipase (CRL) was immobilized on the silica carrier SBA-15 by physical adsorption, then mixed with hydrophobically modified sodium alginate and dropped into calcium chloride solution. Finally, the adsorption-embedding immobilized lipase (L-SBA-15-Mgel) was successfully prepared. The conformation of the carrier before and after lipase immobilization were analyzed by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FT-IR) and other characterization techniques. The molecular docking and molecular dynamics simulation of CRL and modifier dodecyl glycidyl ether (DGE) ligand were carried out to analyze the potential influence of modifier on enzyme characteristics. The basic enzymatic properties including the activity, stability and reaction kinetic parameters of the immobilized lipase L-SBA-15-Mgel were studied. L-SBA-15-Mgel showed good storage stability and reusability. After 16 days of storage, the activity retention was 47.85%, and there was still 63.20% of the residual activity after seven cycles of reuse. The immobilized lipase was applied to the efficient synthesis of food flavor ester isoamyl acetate. Under the reaction conditions of 50 °C and 200 rpm, the highest yield of isoamyl acetate catalyzed by L-SBA-15-Mgel was 85.19%.

In-situ growth of vertically stacked 2D SnS2/SnS heterostructure for highly sensitive and rapid room temperature NO2 gas sensor

Construction of 2D heterostructure is a potential strategy to improve the sensing performance of 2D layered materials owing to the high-quality of heterointerfaces. This attributed to the remarkable electronic band alignment between the constituent materials and their distinctive characteristics. Woefully, very limited attempts have been taken to investigate the effect of 2D heterointerface for gas sensing applications. Here, the SnS2/SnS heterostructure is fabricated on a SiO2/Si substrate using a single-step atmospheric chemical vapor deposition technique for room temperature NO2 sensing. The heterostructure has imparted a 1.3 times enhancement in response (S(%)), with ultra-fast response (τres) and recovery time (τrec) of 32 s and 382 s, towards 40 ppm of NO2 at 30 °C. Moreover, the impact of humidity on the sensing performance of SnS2/SnS has also been studied, confirming its negligible effect on relative humidity. Additionally, it also demonstrates a remarkable stability of 93% over a period of 40 days. Besides, due to strong adsorption energy of SnS2 (1914 meV) and SnS (600 meV) towards NO2 endorses the reaction kinetic parameters validated by the gas adsorption/desorption isotherm analysis of heterostructure. The substantial interface contacts between the SnS2/SnS heterostructure facilities the fermi-level mediated charge transfer, contributing significantly towards the improvement in sensing performance. Therefore, the formation of hierarchical 2D heterostructure with electron depletion layer can be considered as a conducive way for the future development low-powered gas sensor.

New design of eco-friendly Catalytic Electro - Photo Desulfurization process for real diesel fuel

Recently, due to the refineries processes considerations and environmental issues major limitations have been imposed on the sulfur compounds presented in petroleum distillates. Therefore, to reduce the sulfur compounds to minimum levels and to meet the global legislations, many of techniques were used, among them electro chemical photo desulfurization technique was used here. In this study, DBT was removed using electro chemical photo desulfurization over electrodes of titanium and stainless steel using Fe2O3/TiO2 as a catalyst under different temperatures (45, 60, 75 ℃), current density (10, 15, 20 A/m2), electrolyte concentration (25, 35, 45 wt%). The catalyst was characterized by different advanced surface techniques such as N2- adsorption-desorption, SEM-EDX, FTIR, and XRD. The reaction kinetic parameters (reaction order and activation energy) were estimated based on the experimental runs. According to the results obtained, this technique was revealed an efficient method with highest removal of 93.79% achieved using Fe2O3/TiO2 under the best of experimental operating conditions at 75 ℃, 20 A/m2 and 35 wt% of temperature, current density and electrolyte concentration respectively. It can be concluded that the electro chemical photo oxidative desulfurization reaction followed was pseudo 1st order and 41.67 kJ/mole activation energy over titanium dioxides catalyst.

Novel kinetic modeling of photocatalytic degradation of ethanol and acetaldehyde in air by commercial and reduced ZnO: Effect of oxygen vacancies and humidity

A comprehensive kinetic model has been developed to address the factors and processes governing the photocatalytic removal of gaseous ethanol by using ZnO loaded in a prototype air purifier. This model simultaneously tracks the concentrations of ethanol and acetaldehyde (as its primary oxidation product) in both gas phase and on the catalyst surface. It accounts for reversible adsorption of both compounds to assign kinetic reaction parameters for different degradation pathways. The effects of oxygen vacancies on the catalyst have been validated through the comparative assessment on the catalytic performance of commercial ZnO before and after the reduction pre-treatment (10% H2/Ar gas at 500 °C). The influence of humidity has also been assessed by partitioning the concentrations of water molecules across the gas phase and catalyst surface interface. Given the significant impact of adsorption on photocatalytic processes, the beginning phases of all experiments (15 min in the dark) are integrated into the model. Results showcase a notable decrease in the adsorption removal of ethanol and acetaldehyde with an increase in relative humidity from 5% to 75%. The estimated number of active sites, as determined by the model, increases from 7.34 10−6 in commercial ZnO to 8.86 10−6 mol gcat−1 in reduced ZnO. Furthermore, the model predicts that the reaction occurs predominantly on the catalyst surface while only 14% in the gas phase. By using quantum yield calculations, the optimal humidity level for photocatalytic degradation is identified as 25% with the highest quantum yield of 6.98 10−3 (commercial ZnO) and 10.41 10−3 molecules photon−1 (reduced ZnO) catalysts.

Impact of Composition Ratio on the Expansion Behavior of Polyurethane Grout.

Different formulations of foaming polyurethane grout offer controlled expansion rates. This is crucial for precision in filling voids without exerting excessive pressure on surrounding structures, which could potentially cause damage. This study focuses on the impact of composition on the expansion performance of tailor-made polyurethane grouting materials. Initially, multiple unknown chemical reaction kinetic parameters were identified by combining free expansion tests, which involved measuring density and temperature changes, with the particle swarm optimization algorithm. A numerical simulation, integrating chemical kinetic models and fluid flow equations, was established to replicate the free expansion process of polyurethane grout in a cup, aligning with our experimental results. Subsequently, we analyzed the polymerization process of polyurethane grout with varying compositions to determine the effect of composition ratios on grout expansion. Our findings reveal that the expansion ratio of foaming polyurethane is predominantly influenced by the concentrations of physical and chemical foaming agents, followed by isocyanate concentration. Polyol, in contrast, exerts a relatively minor influence. Furthermore, the solubility of the physical foaming agent in the grout determines both its maximum allowable concentration and its maximum contribution to volume increase. This study provides valuable insights for the design and selection of polyurethane grout components tailored to diverse applications.

Kinetic analysis of monomolecular cracking of normal Alkanes (C4[sbnd]C6) over Brønsted Acid site of Zeolitic type catalyst with energetic evaluation of transition states using Quantum-Chemical modeling

The work aims to determine the kinetic parameters of reactions for production of light olefins via catalytic cracking reactions of C4–C6 n-alkanes based on the energy characteristics of the transition state using quantum chemical calculations. Cracking reactions of C4–C6 n-alkanes proceed via protolytic mechanism on the Brønsted acid sites of zeolite-containing catalysts. For kinetic studies in this work, the thermochemical parameters of the intermediate stages, including hydrocarbon adsorption and transition state were determined, then the activation energies and rate constants were determined over the temperature range of catalytic cracking process from 773 to 903 K (500–630 °C).The results showed that DFT method in combination with B3LYP and ωB97X-D functionals, and 3–21 G basis demonstrated quite high accuracy in determining thermochemical parameters, including enthalpy, entropy and Gibbs free energy at both energetic levels of adsorption and transition state. Then, modeling continued by calculations of activation energies and rate constants of reactions. Obtained kinetic parameters made it possible to determine the reactivity of hydrocarbons with different chain length. It was obtained that the rate constants of butane cracking reactions with the formation of ethylene are 54–90 times higher than the formation of propylene. The rate constants of pentane cracking reactions with the formation of butylene are on average 5 times higher than the formation of propylene. The rate constants for hexane cracking reactions with the formation of butylene are 2.9–3.7 times higher compared to the formation of propylene.