Kinetic Model Research Articles

Scaling up global kinetic models of pulsar magnetospheres using a hybrid force-free-PIC numerical approach

Context. The particle-in-cell approach has proven effective in modeling neutron-star and black-hole magnetospheres from first principles, but global simulations are plagued with an unrealistically small separation between the scales where microphysics operates and the system-size scales due to limited numerical resources. A legitimate concern is whether the scale separation achieved to date is large enough for results to be safely extrapolated to realistic scales. Aims. In this work, our aim is to explore the effect of scaling up physical parameters and to check whether salient features uncovered by pure kinetic models at smaller scales are still valid, with a special emphasis on particle acceleration and high-energy radiation emitted beyond the light cylinder. Methods. To reach this objective, we developed a new hybrid numerical scheme coupling the ideal force-free and the particle-in-cell methods to optimize the numerical cost of global models. We propose a domain decomposition of the magnetosphere based on the magnetic-field topology using the flux function. The force-free model is enforced along open field lines while the particle-in-cell model is restricted to the reconnecting field line region. Results. As a proof of concept, this new hybrid model is applied to simulate a weak millisecond pulsar magnetosphere with realistic scales using high-resolution axisymmetric simulations. Magnetospheric features reported by previous kinetic models are recovered, and strong synchrotron radiation above 100MeV consistent with the Fermi-LAT gamma-ray pulsar population is successfully reproduced. Conclusions.This work further consolidates the shining-reconnecting current sheet scenario as the origin of the gamma-ray emission in pulsars, as well as firmly establishing pulsar magnetospheres as at least teraelectronvolt particle accelerators.

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.

DEVELOPMENT AND IN VITRO - IN VIVO EVALUATION OF OCULAR INSERT CONTAINING KETOROLAC TROMETHAMINE AND MOXIFLOXACIN HYDROCHLORIDE

Purpose: Conjunctivitis is a common eye disorder that causes swelling and inflammation of the conjunctiva. Topical dosage form containing antibiotics and non-steroidal anti-inflammatory drugs are prescribed for the treatment and in order to overcome problems of conventional dosage forms the present study aims to develop an ocular insert containing Moxifloxacin HCl and Ketorolac Tromethamine.Methods: Insert was prepared by a solvent casting method by taking different polymers PVA, PVP K 30, and a combination of both as film-forming polymer, and glycerol as a plasticizer and characterized by various parameters like thickness, folding endurance, pH, swelling index, drug content, mechanical properties, in vitro and in-vivo release study.Results: The Formulation prepared by a combination of both polymers demonstrated significantly improved properties including % Elongation, tensile strength, swelling index, drug content and drug release compared to the formulation made with single polymer. The In vitro release data indicated that the batch R8 exhibited sustain release of drug (85 % release in 10 hr) and following the Higuchi model for release kinetics. In vivo, study in rabbit eyes revealed the sustained release of the drug up to 16 hr with a good correlation between in vitro and in vivo release data.Conclusion: From the study, it can be concluded that the developed ocular insert can be a promising formulation for rational therapy of conjunctivitis.

Modeling of Dynamic Recrystallization Kinetics of a High Strength Low Alloy Steel During Hot Rolling

Modeling of Dynamic Recrystallization Kinetics of a High Strength Low Alloy Steel During Hot Rolling

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.

Investigating intermittent immersion during osmotic dehydration of mango (Mangifera indica L. Moench). Part B mathematical modeling of D2I and D3I kinetics in mango (Mangifera indica L. Moench) slices

This work aims to investigate the dynamics of water loss (WL) and solute gain (SG) during dehydration impregnation by immersion (D2I) and intermittent immersion (D3I). WL and SG of mango slices, 4 × 1× 1 cm3 in size, during dehydration immersion impregnation (D2I) and dehydration impregnation by intermittent immersion (D3I) were determined at 35, 45 and 55 °C for 270 min. Mango slices were immersed in a hypertonic sucrose solution of (61.6 ± 0.2) °Brix at a ratio of 6 mL of hypertonic solution per gram of fruit. Five semi-empirical models, two of which have been modified, were used to study mass transfer during D2I and D3I, namely the Azura, Weibull, Crank, Modified Crank I, and Modified Crank II models. The equilibrium water loss (WL∞), the equilibrium solute gain (SG∞), the diffusion coefficient, and activation energy were determined using the Modified Crank II model which was the best of all the tested models. Equilibrium water loss during D2I decreased with increasing temperature, while during D3I it increased with temperature. The SG∞ during D2I and D3I increases with temperature but was higher in D2I than in D3I. The average water diffusion coefficients were (6.02 ± 2.62) × 10−8 m2 s−1 for D2I and (4.89 ± 0.55) × 10−8 m2 s−1 for D3I and the average solute diffusion coefficients were (4.45 ± 0.53) × 10−8 m2 s−1 for D2I and (8.33 ± 0.79) × 10−8 m2 s−1 for D3I. The activation energies for WL in D2I and D3I were respectively 38789 J mol−1 and 9503 J mol−1. The respective values for SG were 9037 J mol−1 and 7327 J mol−1. This work demonstrates that mass transfers in D3I are better than those in D2I, and it highlights that, unlike the D2I process, the D3I process is less sensitive to temperature variations, making it particularly advantageous for processing products with high nutritional value.

Green Synthesis Study: Adsorption of Congo Red Dye with Selenium Nanoparticles Obtained from Prunus Armeniaca L. Leaf Waste

AbstractIn this study, it was aimed to remove Congo Red (CR) dye in aqueous solution by biosynthesized Selenium Nanoparticles from Prunus armeniaca L. (PAL‐SeNPs) leaf wastes by green synthesis method. The characteristic structure of PAL‐SeNPs was determined by UV‐vis spectroscopy, X‐ray diffraction (XRD), Brunauer–Emmett–Teller (BET), scanning electron microscope (SEM), energy dispersive X‐ray (EDX), fourier transform infrared spectroscopy (FTIR), thermogravimetry‐differential thermal analysis (TGA‐DTA), dynamic light scattering (DLS), zetasizer, and point of zero charge (pHpzc). The effects of pH, adsorbent amount, time, initial concentration, and temperature were investigated by batch adsorption studies. 2 different kinetic and 4 isotherm models were tested and error analysis functions were determined for the most suitable model. Accordingly, the particle size, crystallinity, pHpzc value and average surface charge of PAL‐SeNPs were determined as 9.969 nm, 48.50 %, 3.47, and −23.6 mV, respectively. Also, the most suitable kinetic and isotherm models for the removal of CR dye with PAL‐SeNPs were found as Pseudo‐second‐order and Freundlich, with R2 values of 0.996, respectively. Also, where the optimum pH was 7.00, the maximum adsorption capacity was calculated as 96.59 mgCR/gPAL‐SeNPs. The results obtained show that environmentally friendly and low‐cost PAL‐SeNPs produced by the green synthesis method are a suitable alternative for the removal of CR dye.

Kinetics Study on Microwave Alkaline Roasting-Water Dissolving of Germanium from Zinc Oxide Dust

Abstract Zinc hydrometallurgy plants produce large amounts of germanium (Ge)-containing zinc oxide (ZnO) dust during the production process. However, the present leaching percentages of Ge by the sulfuric leaching process from ZnO dust are generally lower than 60%. Thus, a novel process of microwave alkaline roasting followed by water dissolving is proposed to further improve Ge extraction from ZnO dust, and the kinetic behaviors and related theoretical models are studied. Perhaps it can be promoted Ge leaching percentages by water after microwave alkaline roasting, the dissolving reaction kinetics follow the diffusion control model, and the apparent activation energy is 15.46 kJ/mol.

The effect of different subgrid-scale models on the flow field in cyclone separator using large-eddy simulations: A benchmark study

Abstract The cyclone separator is extensively utilized across industries to extract solid particles from gas streams. This study is focused on the steady and unsteady simulations of the Stairmand cyclone using large-eddy simulations aiming to assess the performance using different subgrid-scale models viz. standard Smagorinsky (Cs =1), dynamic Smagorinsky, Wall-Adapting Local Eddy-Viscosity (WALE), Wall-Modeled LES (WMLES), and dynamic kinetic energy models. The velocity profiles within the cyclone separator were analyzed under both steady and unsteady conditions, with reference to the Hoekstra experiment for validation and comparison. Velocity profiles inside the cyclone separator were inadequately predicted by the steady-state simulation, whereas the unsteady-state simulation yielded results more aligned with experimental values. The present study suggests that adopting subgrid-scale LES models such as standard Smagorinsky and WMLES offers a better option for analyzing flow patterns.

Effect of HEDTA on the Adsorption of 2,2 Bipyridyl and 3-Mercaptobenzothiazole and Electroless Cu Deposition Rate

Surface-enhanced Raman spectroscopy (SERS) and chronoamperometry were utilized to evaluate the electroless deposition of Cu in hydroxyethylethylelenediaminetriacetic acid (HEDTA)- and tartrate-based baths containing 2,2′-bipyridyl (BP) and 2-mercaptobenzothiazole (MBT). The Cu deposition rate was shown to be faster in tartrate baths, with rates at 0.08 μm min−1 without MBT or BP but decreased to near zero with concentrations approaching 6 μM of either MBT or BP. HEDTA baths displayed a slower rate of 0.04 μm min−1 without MBT or BP. However, the addition of MBT increased the rate up to 4-fold, while BP concentration did not affect the deposition rate. SERS data showed that HEDTA adsorbs to the surface while tartrate does not. Kinetic Langmuir isotherm model fits showed a decrease in MBT and BP adsorption rate in the presence of HEDTA and showed a decrease in HEDTA adsorption upon MBT injection while BP injection did not affect the HEDTA adsorption. Competition between the complexing and the stabilizing agent is a key factor for the rate of electroless Cu deposition.

Species specific kinetics of imidacloprid and carbendazim in mouse and rat and consequences for biomonitoring

This study aimed to develop physiologically based kinetic (PBK) models to predict the blood concentrations of imidacloprid and carbendazim and their primary metabolites 5-hydroxy-imidacloprid and 2-aminobenzimidazole after single or repeated oral exposure in mouse (Mus musculus), and compare this to corresponding kinetic data in rat (Rattus norvegicus). PBK model constants for conversion of imidacloprid and carbendazim and formation and clearance of their selected primary metabolites were quantified by in vitro mouse liver microsomal and S9 incubations. The performance of the newly developed PBK models was evaluated, based on a comparison to available literature data, showing that the models performed well. Predictions made were also compared to results from PBK model simulations for rats reported previously to obtain insight in species dependent differences in kinetics of these pesticides. The results thus obtained revealed substantial species differences in kinetics for these two pesticides between mouse and rat, especially for imidacloprid and to a lesser extent for carbendazim. Repeated dose PBK model simulations revealed that the models can facilitate estimation of external exposure levels under wildlife conditions based on internal blood concentrations of the parent compound. The rate of conversion and liver volume fraction were shown to influence the accuracy of these predictions with lower values providing less variable outcomes. It is concluded that PBK modeling provides a new approach methodology of use for wildlife biomonitoring studies and that results of the present study facilitate benchmarking of the species and compounds for which kinetics enable this with sufficient accuracy.

Isothermal Reduction and Avrami–Erofeev Kinetic Model for Reducing Iron Ore Pellets in a 70% N2–30% H2/CO Atmosphere

Isothermal Reduction and Avrami–Erofeev Kinetic Model for Reducing Iron Ore Pellets in a 70% N2–30% H2/CO Atmosphere

Evaluation of the reactivity of co-combustion of wheat straw and waste rubber thermolysis char

The co-combustion of wheat straw (WS) and waste rubber thermolysis char (WRTC) was examined with the perspective of utilizing WRTC as a high-calorific value fuel addition to agricultural biomass. The study investigated the effect of different proportions of WS-WRTC blends (10/15/25/49 wt% WRTC) and a maximum of 4 wt% binders, including potato starch and calcium oxide, on the reactivity of co-combustion and the distribution of products during the process. Thermogravimetric analysis with Fourier Transform Infrared Spectroscopy (TGA-FTIR) analyses was employed at a temperature range of 25–1000 ° C with a heating rate of 10 ° C/min. The kinetics of co-combustion were analyzed using the Fraser-Suzuki (FS) deconvolution method and a model-based kinetic modeling. The results indicate that a 10% addition of WRTC char reduces the intensity and rate of combustion and prolongs the combustion time. It was observed that the optimal addition to the blend is 25% WRCT, and it resulting in a reduction in activation energy and combustion indexes. However, it remains with no significant impact on process stability and efficiency. Kinetics of the decomposition of the WRTC25 mixture modeled by the deconvolution method indicates a 5-step reaction course, which is a combination of the characteristic combustion stages of both fuels. The main denoted functional group observed in the FTIR absorption spectra were C=O, C-O, O-H, and C-H related to the release of CO2, CO, H2O, CH4, aromatic compounds, and hydrocarbons.

Improving heat transfer prediction across catalytic SiC interface through a multiscale framework leveraging machine learning and data fusion techniques

Accurate aerothermal prediction under hypersonic flow conditions is crucial for any thermal protection materials design and engineering. The surface catalytic effect, where dissociated atoms recombine into their molecular forms at the air-solid interface, is an exothermic reaction and plays an important role in high-enthalpy aerodynamic environment prediction. Taking SiC, a widely recognized high-temperature thermal protection material as an example, a multiscale fusion approach for aerothermal prediction is proposed. The approach utilizes reactive molecular dynamics method to construct an interface catalysis model, and the Bayesian maximum entropy to integrate experimental and simulational data into an optimized database. Subsequently, using the radial basis function neural network algorithm, a machine learning-based reaction kinetics model with precise analysis of surface catalysis is trained. The obtained catalytic recombination efficiency is used as a boundary input for computational fluid dynamics simulation, enabling rapid and accurate prediction of hypersonic thermal environment. The result shows that the predicted surface heat flux by this novel approach is consistent with the benchmark studies, but comes with significantly reduced computation time. The stagantion heat flux predictions based on the assumptions of full catalytic wall, finite rate catalytic wall (from the proposed multiscale fusion method), and non-catalytic wall are determined to be 8.65×106 W/m2, 7.51×106 W/m2, and 4.02×106 W/m2, respectively. Comparing these with the wind tunnel benchmark value of 7.48×106 W/m2, the error from the proposed multiscale fusion method is 0.30 %, indicating significant enhancement in prediction accuracy through the proposed upscaling method. The new approach could not only reveal complex exothermic reaction processes at the interface, but also enhance the prediction accuracy at much higher computational efficiency, providing an alternative for multiscale modeling of complex flow and heat transfer at the interface.

LET-based approximation of the microdosimetric kinetic model for proton radiotherapy.

Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges. This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy. At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons. A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed. The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

Collapsed State Mediates the Low Fidelity of the DNA Polymerase β I260 Mutant.

DNA polymerase β (Pol β) fills single nucleotide gaps during base excision repair. Deficiencies in Pol β can lead to increased mutagenesis and genomic instability in the cell, resulting in cancer. Our laboratory has previously shown that the I260 M somatic mutation of Pol β, which was first identified in prostate cancer, has reduced nucleotide discrimination in a sequence context-dependent manner. I260 M incorporates the incorrect G opposite A in this context more readily than WT. To identify the molecular mechanism of the reduced fidelity of I260M, we studied incorporation using single turnover kinetics and the nature and rates of conformational changes using steady-state fluorescence and Förster resonance energy transfer (FRET). Our data indicate that the I260 M mutation affects the fingers region of rat Pol β by creating a "collapsed" state in both the open (in the absence of nucleotide) and closed (prior to chemistry) states. I260 M is a temperature-sensitive mutator and binds nucleotides tighter than the WT protein, resulting in reduced fidelity compared to the WT. Additionally, we have generated a kinetic model of WT and I260 M using FRET and single turnover data, which demonstrates that I260 M precatalytic conformation changes differ compared to the WT as it is missing a precatalytic noncovalent step. Taken together, these results suggest that the collapsed state of I260 M may decrease its ability for nucleotide discrimination, illustrating the importance of the "fingers closing" conformational change for polymerase fidelity and accurate DNA synthesis.

Biochar from Malt Residue: Toward a Circular Economy for Sustainable Fluoroquinolone Removal in Aqueous Systems

Malt bagasse holds potential as a high-value material, contributing to a circular economy. Biochars were synthesized via pyrolysis (PC-500) and hydrothermal carbonization (HC-150), with one-pot activation using phosphoric acid. Additionally, PC-500 activated with H3PO4 was synthesized for comparison. Various analytical methods were used to characterize the materials. The PC-500 and PCA-500 samples exhibited higher degrees of carbonization, whereas the HC-150 sample retained its functional groups more effectively. Biochars showed higher porosity than biomass, with microspheres present in HC-150. Evaluations were conducted on the removal of fluoroquinolones from water using biochars. Maximum removal efficiency was obtained at pH 8, favoring neutral fluoroquinolone species with a Brønsted acid-base nature. The experimental outcomes were further rationalized by the computational calculation of the physicochemical properties of the adsorbates, in analogy with the structural activity relationship approach in medicinal chemistry. The pseudo-second-order kinetic model proved to be the most suitable for fitting the experimental data, while the Langmuir model effectively described the adsorption isotherms. Ciprofloxacin, enrofloxacin, and norfloxacin showed maximum adsorption capacities (qmax) of 95, 164, and 99mgg-1, respectively, when HC-150 was used. On the other hand, with PC-500, qmax of 57, 12, and 20mgg-1 were obtained for ciprofloxacin, enrofloxacin, and norfloxacin, respectively. Although PCA-500 enhanced adsorption capacity compared to PC-500, the qmax remained lower than the results obtained with HC-500, measuring at 51, 102, and 95mgg-1. These findings emphasize malt bagasse biochar as a viable adsorbent.

Facile Synthesis of Silver‐Exchanged Phosphotungstic Acid Immobilized on Sn‐Bi Bimetallic Metal–Organic Frameworks for Enhanced Esterification

ABSTRACTMetal–organic frameworks (MOFs) are ideal supports for the synthesis of porous composite catalysts. In the present study, Sn‐Bi bimetallic metal–organic frameworks (Sn‐Bi‐MOFs) supported silver‐doped phosphotungstic acid (AgPW) catalysts (AgPW@Sn‐Bi‐BDC and AgPW@Sn‐Bi‐BDC (NH2)) were successfully synthesized via a simple in situ impregnation method, which was subsequently applied to catalyze esterification for the production of biodiesel from oleic acid (OA). The physico‐chemical properties of the prepared composite catalysts underwent comprehensive analysis through XRD, FTIR, N2 physisorption, SEM, EDX, NH3‐TPD, Py‐FTIR, TG, and XPS techniques, confirming the successful impregnation of AgPW on the Sn‐Bi‐MOFs framework. Among the catalysts tested, AgPW@Sn‐Bi‐BDC (NH2) exhibited the better catalytic activity than that of Sn‐Bi‐BDC, Sn‐Bi‐BDC (NH2), and AgPW@Sn‐Bi‐BDC, reaching 91.6% of OA conversion with the methanol:OA molar ratio of 20:1 and the catalyst quantity of 0.2 g at 130°C for 4 h. The high activity of AgPW@Sn‐Bi‐BDC (NH2) is attributed to the available multiscale pore structure, high acidity, and the synergistic action of the Brønsted and Lewis acidic sites. Additionally, the esterification with AgPW@Sn‐Bi‐BDC (NH2) followed the first‐order reaction kinetic model, with an Ea of 34.5 kJ/mol. Moreover, the recyclability of the composites was also assessed, demonstrating sustained catalytic activity after four reuses. This approach showed a potential for sustainable and efficient energy production through bimetallic MOFs‐based composite catalysts.

Sodium Triphosphate Effect on Encapsulation of Vitamin B<sub>6</sub> into Chitosan-Alginate Nanoparticles and Its <i>In Vitro</i> Drug Release Study

The in-vitro drug release study of vitamin B6 encapsulated into sodium tripolyphosphate crosslinked chitosan-alginate (B6-TCA) nanoparticles aims to determine the effect of sodium tripolyphosphate on the encapsulation efficiency of vitamin B6 and effectiveness of the nanoparticles to release vitamin B6. The focus of this research is synthesizing and characterizing TCA nanoparticles to encapsulate vitamin B6 as an effective delivery system by studying the kinetics release of vitamin B6. The research resulted in the formation of coarse solid powder nanoparticles in yellowish-white color with a nanoparticle size of 22.55 nm. Sodium tripolyphosphate decreased the percentage of encapsulation efficiency in the B6-TCA nanoparticles as its concentration increased. However, the increasing sodium tripolyphosphate causes a slower release of vitamin B6 from nanoparticles. The encapsulation efficiency of vitamin B6 is 82.04%. The optimum composition of B6-TCA nanoparticles ratio is 2:1:1.5:2, where Korsmeyer-Peppas kinetics model suited its better with the Fickian diffusion mechanism of 0.989 and has the smallest reaction rate constant of 0.039 occurred within 6 h.

Efficiency-enhancing methods for predicting nitrogen mineralization characteristics in paddy soils using soil properties and rapid soil extraction

Soil mineralized nitrogen (N) is a vital component of soil N supply capacity and an important N source for rice growth. Unveiling N mineralization (Nm) process characteristics and developing a simple and effective approach to evaluate soil Nm are imperative to guide N fertilizer application and enhance its efficiency in various paddy soils with different physicochemical properties. Soil properties are important driving factors contributing to soil Nm differences and must be considered to achieve effective N management. Nevertheless, discrepancies in Nm capacity and other key influencing factors remain uncertain. To address this knowledge gap, this study collected 52 paddy soil samples from Taihu Lake Basin, south China, which possesses vastly different physicochemical properties. The samples were subjected to a submerged anaerobic incubation experiment at a constant temperature to obtain the soil Nm characteristics. In addition to other analyses, reaction kinetics models were employed to compare characteristic differences between Nm potential (Nmp) and short-term accumulated mineralized N (Amn) processes in relation to soil physicochemical properties. Based on these relationships, simplified Nmp prediction methods for paddy soils were established. The results revealed that the Nmp values in pH < 6.50, pH range from 6.50 to 7.50, and pH > 7.50 were 145.18 mg kg-1, 88.64 mg kg-1 and 21.03 mg kg-1, respectively. Significantly, after comparing different incubation days, short-term Amn at 14 days showed a good correlation (P < 0.01) with Nmp (R2 = 0.94), indicating that the prevailing short-term incubation experiment is an acceptable marker for Nmp. Moreover, Nmp correlated well with the ultraviolet absorbance obtained at 260 nm using NaHCO3 extraction (Na260), streamlining the Nmp estimation method further. The incorporating easily obtainable soil properties, including pH, total nitrogen (TN), and the ratio of total organic carbon to TN (C/N) alongside Na260 for Nmp evaluation allowed the multiple regression model, Nmp = 58.62 × TN - 23.18 × pH + 13.08 × C/N +86.96 × Na260, to achieve high predictive accuracy (R2 = 0.95). The reliability of this prediction was further validated with published data in paddy soil from the same region and the other rice regions, demonstrating the regional applicability and prospects of this model. This study underscored the roles of soil properties in Nm characteristics and mechanisms and established a site-specific prediction model based on rapid extraction and edaphic properties from the paddy soil, paving the way for developing rapid, precise Nm prediction models.