Reaction Model Research Articles

Degradation of norfloxacin by the synergistic effect of micro-nano bubbles and sodium hypochlorite: kinetics, influencing factors and pathways.

This study thoroughly investigated the degradation of norfloxacin (NOR) under the influence of micro-nanobubbles (MNBs) and sodium hypochlorite (NaClO), focusing on their synergistic effects. The impact of various environmental factors, including NaClO concentration, pH, inorganic anions, and surfactants, on NOR degradation efficiency within the MNBs/NaClO system was systematically assessed. The basic properties of the MNBs/NaClO system and the degradation kinetics of NOR were explored. The degradation products and pathways of NOR were explored to reveal the degradation mechanism of antibiotics in the MNBs/NaClO system by employing density functional theory (DFT) and high-performance liquid chromatography-mass spectrometry (HPLC-MS). The redox potential of the MNBs/NaClO system exhibited significantly superior properties than the single system, with bubble sizes predominantly in the nanoscale. The degradation kinetics of NOR adhered to a pseudo-first-order reaction model, with optimal degradation occurring at a 0.025% NaClO volume concentration. Acidic conditions promoted the degradation of NOR, and alkaline conditions inhibited the degradation of NOR. Inorganic anions PO43-, HCO3-, and CO32- in the water matrix led to strong inhibition of NOR degradation. Cationic surfactants accelerated the degradation process of NOR, while anionic and nonionic surfactants had a consistent inhibitory effect on the degradation of NOR. Based on the degradation behavior, three potential pathways for NOR degradation were proposed: quinolone group transformation, defluorination reaction, piperazine ring cracking and quinolone ring decomposition. This research contributes a novel technical approach for addressing antibiotic pollution and offers a theoretical framework for understanding the fate of antibiotics in the environment.

Validity analysis of γ-ray strength function models for radiative capture reactions of heavy nuclei

Accurate simulation of radiative capture reactions (RCRs) requires precise modeling of [Formula: see text]-ray strength functions (GSF). Various GSF models exist but need normalization based on experimental total radiative width (TRW) data. This study found that current normalization methods fail for neutron-induced RCRs in [Formula: see text]U and [Formula: see text]Th nuclei. In this regard, re-normalization values are proposed in order to improve model consistency at low energies. The standard Lorentzian (SLO) model fits experimental data best with minimal normalization.

Numerical Evaluation for Influence of Ca Treatment and Slag Composition on Compositional Changes in Non-metallic Inclusion Using Coupled Reaction Model for Ladle Treatment

Numerical Evaluation for Influence of Ca Treatment and Slag Composition on Compositional Changes in Non-metallic Inclusion Using Coupled Reaction Model for Ladle Treatment

Effects of water injection on reaction temperature and hydrogen production in horizontal co-axial underground coal gasification

Underground coal gasification (UCG) is process of directly recovering energy as combustible gases such as hydrogen and carbon monoxide by combusting unmined coal resources in situ. During UCG process, the temperature in the gasification zone can exceed 1,300 °C, raising concerns about the potential melting of the steel pipe for oxidant injection. To control the temperature in the gasification zone, the use of water injection as an injection agent can be an option. Injecting water during UCG process serves two purposes: it decreases the temperature in the reaction zone by the endothermic effect of water, and it enhances the production of H2 by the reduction reaction of water. However, injecting excessive amounts of water may lead to a significant decrease in the temperature in the reaction zone, consequently cannot maintain the temperature range required for the UCG reaction. This study discusses the effects of water injection on the temperature of the gasification zone and the product gas by developing a chemical reaction model of UCG using COMSOL Multiphysics® software. The model was developed based on the temperature and produced gas results obtained from laboratory-scale artificial coal seam UCG experiments. Our findings reveal that water injection significantly influences the gasification process, controlling temperature in the reaction zone and promoting H2 production through steam gasification and water-gas shift reactions. Moreover, under the experiment and analysis conditions of this study, it is revealed that water injection up to an H2O/O2 molar ratio of 3.9 can effectively control the temperature of the gasification zone with enhancing H2 production.

A Comprehensive Investigation on Catalytic Behavior of Anaerobic Jar Gassing Systems and Design of an Enhanced Cultivation System

The rapid and reliable diagnosis of anaerobic bacteria constitutes one of the key procedures in clinical microbiology. Automatic jar gassing systems are commonly used laboratory instruments for this purpose. The most critical factors affecting the cultivation performance of these systems are the level of residual oxygen remaining in the anaerobic jar and the reaction rate determined by the Pd/Al2O3 catalyst. The main objective of the presented study is to design and manufacture an enhanced jar gassing system equipped with an extremum seeking-based estimation algorithm that combines real-time data and a reaction model of the Pd/Al2O3 catalyst. The microkinetic behavior of the palladium catalyst was modeled through a learning-from-experiment methodology. The majority of microkinetic model parameters were derived from material characterization analysis. A comparative validation test of the designed cultivation system was conducted using conventional gas pouches via six different bacterial strains. The results demonstrated high cell viability, with colony counts ranging from 1.26 × 105 to 2.17 × 105 CFU mL−1. The favorable catalyst facets for water formation on Pd surfaces and the crystal structure of Pd/Al2O3 pellets were identified by X-ray diffraction analysis (XRD). The doping ratio of the noble metal (Pd) and the support material (Al2O3) was validated via energy-dispersive spectroscopy (EDS) measurements as 0.68% and 99.32%, respectively. The porous structure of the catalyst was also analyzed by scanning electron microscopy (SEM). During the reference clinical trial, the estimation algorithm was terminated after 878 iterations, having reached its predetermined termination value. The measured and modelled reaction rates were found to converge with a root-mean-squared error (RMSE) of less than 10−4, and the Arrhenius parameters of ongoing catalytic reaction were obtained. Additionally, our research offers a comprehensive analysis of anaerobic jar gassing systems from an engineering perspective, providing novel insights that are absent from the existing literature.

Reaction kinetics and product evolution of hydrolysis in copper-chlorine thermochemical cycle for hydrogen production

By-products of the hydrolysis reaction in the copper-chlorine thermochemical cycle for hydrogen production are key to the final thermal and hydrogen efficiency. The current study focuses on the influences of reaction time, temperature, and steam partial pressure on the hydrolysis reaction and by-product formation mechanism via experimental and multiple analytical methods. The result demonstrates that the hydrolysis reaction of CuCl2 and steam converts to CuCl and Cu2OCl2, with a high conversion of 97%, while the Cu2OCl2 and CuCl2-CuO product mixtures exhibit interconversion capabilities. The increase of temperature increases the CuCl product content, while the decrease of steam partial pressure increases the by-product CuCl2. Particle morphology and reaction thermodynamics are analyzed for main and by-products formation. Finally, the homogeneous reaction model and shrinking core model are used and compared for the activation energy of the formation of Cu2OCl2 for the hydrolysis reaction and the effect of by-products.

Influence of BN microstructure on oxidation of SiC/BN/SiC composites

AbstractThis study investigates the effects of boron nitride (BN) coating characteristics on the subsurface oxidation behavior of SiC/SiC composites in high‐temperature, water‐rich environments. Three types of coatings were examined: a crystalline stoichiometric BN, an amorphous BN, and a Si‐doped amorphous BN, the latter two containing 5–10 at% of oxygen and carbon. High‐resolution imaging and chemical analysis techniques were used to probe microstructural changes after oxidation at 1000°C for 1 or 12 h in flowing 20 vol% H2O, focusing on effects of coating thickness. Complementary chemical thermodynamic calculations and models for reaction‐ and transport‐controlled recession were used to interpret the experimental findings. Crystalline BN coatings produce open recession channels without forming borosilicate glass, a consequence of carbothermal reduction arising from C/CO produced through concomitant SiC oxidation. The combination of active oxidation and the relatively thick coatings in this system (ca. 1 µm) leads to a recession rate controlled by the intrinsic BN volatilization rate rather than the rate of gas transport. In contrast, amorphous coatings, both undoped and Si‐doped, readily oxidize to form borosilicate glasses that replace the BN. Broadly, the recession lengths increase with coating thickness. In the early stages, while the glass is boria‐rich and thus permeable to environmental oxidants, recession is controlled by the BN oxidation rate. As boria volatilizes, the silica concentration in the glass increases, eventually reaching the saturation limit and precipitating solid silica on the internal surfaces, essentially arresting further recession.

Analytical solutions for the Noyes Field model of the time fractional Belousov Zhabotinsky reaction using a hybrid integral transform technique

In this work, we employed an attractive hybrid integral transform technique known as the natural transform decomposition method (NTDM) to investigate analytical solutions for the Noyes-Field (NF) model of the time-fractional Belousov–Zhabotinsky (TF-BZ) reaction system. The aforementioned time-fractional model is considered within the framework of the Caputo, Caputo–Fabrizio, and Atangana–Baleanu fractional derivatives. The NTDM couples the Adomian decomposition method and the natural transform method to generate rapidly convergent series-type solutions via an elegant iterative approach. The existence and uniqueness of solutions for the considered time-fractional model are first investigated via a fixed-point approach. The reliability and efficiency of the considered solution method is then demonstrated for two test cases of the TF-BZ reaction system. To demonstrate the validity and accuracy of the considered technique, numerical results with respect to each of the mentioned fractional derivatives are presented and compared with the exact solutions as well as with those from existing related literature. Graphical representations depicting the dynamic behaviors of the chemical wave profiles of the concentrations of the intermediates are presented with respect to varying fractional parameter values as well as temporal and spatial variables. The obtained results indicate that the execution of the method is straightforward and can be employed to explore nonlinear time-fractional systems modeling complex chemical reactions.

A modified variational approach to noisy cell signaling.

Signaling in cells is full of noise and, hence, described with stochastic biochemical models. Thus, an efficient computation algorithm for these fluctuating reactions is much needed. Apart from the very popular Monte Carlo simulation, methods based on probability distributions are frequently desired due to their analytical tractability and possible numerical advantages in diverse circumstances, among which the variational approach is the most notable. In this paper, new basis functions are proposed to better depict possibly complex distribution profiles, and an extra regularization scheme is supplied to the variational equation to remove occasional degeneracy-induced singularities during the evolution. The new extension is applied to four typical biochemical reaction models and restores the Gillespie results accurately but with greatly reduced simulation time. This modified variational approach is expected to work in a wide range of cell signaling networks.

Curing kinetics of block copolymerization thermoset polyurethane by non‐isothermal DSC method

AbstractPolyurethanes consist of hard and soft segments, with the hard segments typically comprising blocks containing isocyanate groups, while the soft segments often consist of chains terminated with hydroxyl groups. The hard segments contribute to the mechanical properties of polyurethanes, while the soft segments provide elasticity and flexibility. The essence of curing lies in the mixing of hard and soft segments and subjecting the system to high temperatures. The curing kinetics of PEG/PCL/IPDI/N100 in‐situ block copolymers were investigated using dynamic isothermal differential scanning calorimetry (DSC). Key curing parameters were obtained from non‐isothermal DSC curves, and these parameters were incorporated into an n‐order reaction model to determine the reaction type and apparent activation energy, thus deriving the reaction equation. The curing kinetics of PEG/PCL/IPDI/N100 in‐situ block copolymers follows an n‐th order autocatalytic reaction, where n is 1, and the activation energy is approximately 52.79 kJ/mol. Based on the reaction equation, the curing process conditions, namely the initial curing temperature (Ti), the peak exothermic temperature (Tp), and the finishing temperature (Tf), were deduced. Studying the curing kinetics of thermosetting polyurethanes can deepen our understanding of the interactions and reaction mechanisms between reactants under different conditions, thereby enhancing our grasp of the curing process. Furthermore, research into curing kinetics can provide a basis for optimizing preparation processes.

Modeling impacts of indoor environmental variables on secondary organic aerosol formation

There are numerous air pollutants indoors including chemicals emitted from building environments as well as outdoor-origin species due to human activities. Despite the significance of indoor air quality, the atmospheric process indoors is not well studied. In this study, the secondary organic aerosol (SOA) formation from the oxidation of α-pinene blended with toluene was simulated under varying indoor environments (lamps, NO2, ozone, and inorganic seed) using the UNIfied Partitioning Aerosol Reaction (UNIPAR) model. Explicitly predicted lumping species produced during the atmospheric oxidation of precursors are used in the model and they process multiphase partitioning and aerosol phase reactions. The performance of the model was demonstrated using indoor chamber experiments in both dark conditions (ozonolysis) and light conditions with commercialized fluorescent or LED lamps. α-Pinene SOA was dominated by ozonolysis even in the presence of indoor light. Toluene, which is known to be photochemically processed, was oxidized in the dark condition with OH radicals that were derived from ozonolysis products of α-pinene. At given dark simulation conditions (10 ppb α-pinene, 30 ppb ozone, and 50 ppb of toluene), toluene contributed 15 % of SOA mass. α-Pinene SOA was insensitive to hygroscopicity of inorganic seed, but toluene blended with α-pinene increased the sensitivity to seed conditions due to the formation of oligomeric matter via aqueous reactions of reactive toluene products. In the presence of NO2. α-pinene SOA formation significantly increased with increasing NO2 owing to the reaction of α-pinene with nitrate radicals to form low volatile products. This study concludes that ozone and NO2, intruded from outdoors to indoors, effectively oxidize terpenes and furthermore aromatic hydrocarbons with OH radicals originating from ozonolysis of terpenes. The reaction paths with ozone and nitrate radicals are more effective at forming SOA than that with OH radical under the indoor light condition with commercialized lamps.

Modeling and Numerical Investigations of Flowing N-Decane Partial Catalytic Steam Reforming at Supercritical Pressure

Steam reforming is an effective method for improving heat sinks of hypersonic aircraft at high flight Mach numbers. However, unlike the industrial process of producing hydrogen with a high water content, the catalytic steam reforming mechanism for the regeneration cooling process of hydrocarbon fuels with a water content below 30% is still unclear. Catalytic steam reforming (CSR) and catalytic thermal cracking (CTC) reactions occur at low temperatures, with the main products being hydrogen and carbon oxides. Thermal cracking (TC) reactions occur at high temperatures, with the main products being alkanes and alkenes. The above reaction exists simultaneously in the regeneration cooling channel, which is referred to as partial catalytic steam reforming (PCSR). Based on the experimental measurement results, an improved neural network correction method was used to establish a four-step global reaction model for the PCSR of n-decane under low water conditions. The reliability of the four-step model was verified by combining the model with a numerical simulation program and comparing it with the experimental results obtained by electric heating hydrocarbon fuels with a pressure of 3 MPa and a water content of 5/10/15%. The experimental and predicted results using the developed kinetic model are consistent with an error of less than 5% in the decane conversion rate. The average absolute error between the fuel outlet temperature and total heat sink is less than 10%. Using the PCSR model to predict the heat transfer characteristics of mixed fuels with different water contents, the convective heat transfer coefficient is basically the same, and the Nu number is affected by the thermal conductivity coefficient, showing different patterns with changes in the water content.

A Carbon Capture and Utilization Process for the Production of Solid Carbon Materials from Atmospheric CO2 - Part 1: Process Performance.

The successful operation of a process that converts atmospheric CO2 into solid carbon products is presented as an alternative to fossil based solid carbon production. In a first step, CO2 is removed from the atmosphere by a direct air capture (DAC) unit. The gas is then mixed with hydrogen and enters a methanation unit. Depending on the operation conditions, gas mixtures consisting of mainly methane with either H2 or CO2 as side-component are obtained. After precipitating the water formed during the methanation step, the remaining gas mixture is fed into a bubble column reactor filled with liquid tin. During the rise of the gas bubbles, methane is thermally split up into hydrogen and solid carbon. The latter is continuously removed from the liquid metal surface as a fine powder by pneumatic conveying. This article is the first of two articles, focusing on the performance of the methanation and methane pyrolysis steps. The experimental results are complemented by thermodynamic analyses and reaction modelling. A detailed analysis of the solid carbon product of the process is presented in the second part.

Investigation of dissolution kinetics of colemanite in propionic acid solutions

ABSTRACT Colemanite is one of the raw materials used to produce boron compounds which have a constituent of the richest composition ratio boron trioxide ( B 2 O 3 ) . The main purpose of this study is to investigate the dissolution kinetics of colemanite in a propionic acid solution. Reaction temperature, solid–liquid ratio, propionic acid concentration, stirring speed, and particle size were chosen as relevant parameters in the dissolution. According to the results of the study, the dissolution rate was directly proportional to the rise in the reaction temperature and inversely proportional to the increase in the solid–liquid ratio, acid concentration, and particle size. Additionally, it was observed that stirring speed did not significantly effect. Experiment results were correlated with the use of the Statistica10 software programme for linear regression. For the dissolution kinetics of colemanite, a model that can control the reaction was obtained by using homogeneous and heterogeneous reaction models. It was determined that the dissolution rate of the process was controlled by diffusion through the product film (ash) and the Activation energy was calculated as 37.51 kJ . mo l − 1 . Experimental data were analyzed with graphical and statistical methods, and a semi-empirical mathematical model was determined, which included the parameters of the study.

Optimizing H2 production from biomass: A machine learning-enhanced model of supercritical water gasification dynamics

Supercritical water gasification (SCWG) is recognized as an efficient technology for biomass conversion, demonstrating substantial potential in the sustainable energy sector. This paper focuses on the H2 production by SCWG of biomass. The objective is to develop an accurate gasification kinetic model that can facilitate the optimization of industrial reactor designs. A series of SCWG experiments is conducted in a batch reactor system under temperature of 500–600 °C and residence time of 1–20 min. Based on the experimental results, a hybrid-driven model for SCWG reaction is established. Firstly, experimental data is utilized to delineate SCWG reaction mechanistic model and forecast gas yields with an acceptable error margin. Subsequently, a Wasserstein Generative Adversarial Network Gradient Boosting Regression Grid Search (WGAN-GBR-GRID) model is applied to acquire knowledge of the predictive errors from the mechanistic model and to develop a hybrid model. The hybrid-driven model significantly enhances the average relative prediction error from 15.56 % to 0.02 % when compared to the mechanistic model. This result underscores the potential of the hybrid model in optimizing SCWG technology and the Shapley Additive exPlanations (SHAP) values in feature analysis shows the possible shortcomings of mechanistic model, thereby providing a new perspective for SCWG reaction dynamics modeling.

Numerical analysis of mixing performance in Y-junction mixers and its impact on yields from supercritical water hydrolysis

This study investigates the mixing behavior in a Y-junction mixer for supercritical water hydrolysis using large eddy simulation with a discrete phase model. Yield changes were simulated using a two-step reaction model with first-order kinetics, based on particles’ temporal temperature data. Effective mixing produced closely matched mass and particle flow temperature distributions, both exhibiting bell-shaped profiles near the mixed temperature. Although variations in flow rate within ±25 % and changes in the inlet temperatures of supercritical water from 350 °C to 430 °C and subcritical water from 100 °C to 170 °C did not significantly affect the overall mixing performance, they did alter the mixed temperature and, subsequently, yield changes. Additionally, backflow occurred when Richardson number for the subcritical inlet reached approximately 7. In effective mixing, simulated yields were approximately 15 % lower than the ideal theoretical yields, calculated using the reaction rate constant at the mixed temperature.

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

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

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

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

Statistical adiabatic channel model for termolecular reactions.

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

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

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