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The dyes present in textile effluents have a complex structure and low biodegradability, making it necessary to use efficient treatments such as advanced oxidation processes (AOP). The aim of this study was to compare the efficiency of photo-Fenton (PF) and electro-Fenton (EF) AOPs in the degradation of direct black dye 22 (DB22), defining the best experimental conditions and evaluating the kinetics and toxicity of the proposed treatments. Initially, for the PF system, using UV-C and sunlight radiation, 99.08% and 99.98% degradations were reached, respectively for [H2O2] = 20 mg·L−1 and [Fe] = 1.0 mg·L−1. From the volume variation study, it was observed that the increase in volume did not compromise the degradation of the dye. For the EF process, the [Fe] that promoted the highest percentage of degradation (95.16%) was equal to 1 mg·L−1. The volume study for the EF process also did not interfere significantly in the efficiency of the process. The PF and EF systems presented satisfactory adjustments to the proposed kinetic models, suggesting that the treatment follows a pseudo-first-order kinetics. The ecotoxicological tests showed no toxicity for the thyme seed after using the EF process. Therefore, it is evident that different AOP techniques can be applied in the treatment of DB22. [ABSTRACT FROM AUTHOR]

Monitoring of molding processes is one of the most challenging future tasks in polymer processing. In this work, the in situ monitoring of the curing behavior of highly filled EMCs (silica filler content ranging from 73 to 83 wt%) and the effect of filler load on curing kinetics are investigated. Kinetic modelling using the Friedman approach was applied using real-time process data obtained from in situ DEA measurements, and these online kinetic models were compared with curing analysis data obtained from offline DSC measurements. For an autocatalytic fast-reacting material to be processed above the glass transition temperature Tg and for an autocatalytic slow-reacting material to be processed below Tg, time–temperature–transformation (TTT) diagrams were generated to investigate the reaction behavior regarding Tg progression. Incorporating a material containing a lower silica filler content of 10 wt% enabled analysis of the effects of filler content on sensor sensitivity and curing kinetics. Lower silica particle content (and a larger fraction of organic resin, respectively) favored reaction kinetics, resulting in a faster reaction towards Tg1. Kinetic analysis using DEA and DSC facilitated the development of highly accurate prediction models using the Friedman model-free approach. Lower silica particle content resulted in enhanced sensitivity of the analytical method, leading, in turn, to more precise prediction models for the degree of cure. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD), the most common form of dementia, is closely related to the overproduction of reactive oxygen species (ROS). A kinetic model based on free radical polymerization of amyloid beta (Aβ) utilizing ROS as an initiator is proposed. Kinetic parameters involved in the model are tuned with the reported experimental data on fibril molecular weight. The tuned model is used to simulate time evolution of fibril length and polydispersity of Aβ aggregates. The simulated values are compared with the reported experimental values for these fibril properties. A good agreement is observed between the model simulated fibril properties and the reported experimental data. This supports the hypothesis of ROS as the cause of Aβ aggregation using the free radical polymerization. The proposed model is also able to predict the sigmoidal growth of fibrils at different set of parameter values. Sensitivity analysis has been performed to check the reliability of the proposed model. It is envisaged that the proposed model will be helpful to elucidate ROS-based therapeutic strategies for AD treatment in near future. [ABSTRACT FROM AUTHOR]

Introduction: Fusion of the fragment crystallizable (Fc) to protein therapeutics is commonly used to extend the circulation time by enhancing neonatal Fcreceptor (FcRn)-mediated endosomal recycling and slowing renal clearance. This study applied kinetic modeling to gain insights into the cellular processing contributing to the observed pharmacokinetic (PK) differences between the novel recombinant ADAMTS13 fragment (MDTCS) and its Fcfusion protein (MDTCS-Fc). Methods: For MDTCS and MDTCS-Fc, their plasma PK profiles were obtained at two dose levels following intravenous administration of the respective proteins to mice. The plasma PK profiles of MDTCS were fitted to a kinetic model with three unknown protein-dependent parameters representing the fraction recycled (FR) and the rate constants for endocytosis (kup, for the uptake into the endosomes) and for the transfer from the plasma to the interstitial fluid (kpi). For MDTCS-Fc, the model was modified to include an additional parameter for binding to FcRn. Parameter optimization was done using the Cluster Gauss-Newton Method (CGNM), an algorithm that identifies multiple sets of approximate solutions ("accepted" parameter sets) to nonlinear least-squares problems. Results: As expected, the kinetic modeling results yielded the FR of MDTCS-Fc to be 2.8-fold greater than that of MDTCS (0.8497 and 0.3061, respectively). In addition, MDTCS-Fc was predicted to undergo endocytosis (the uptake into the endosomes) at a slower rate than MDTCS. Sensitivity analyses identified the association rate constant (kon) between MDTCS-Fc and FcRn as a potentially important factor influencing the plasma half-life in vivo. Discussion: Our analyses suggested that Fc fusion to MDTCS leads to changes in not only the FR but also the uptake into the endosomes, impacting the systemic plasma PK profiles. These findings may be used to develop recombinant protein therapeutics with extended circulation time. [ABSTRACT FROM AUTHOR]

Purpose: Estrogen receptors (ER) are implicated in psychiatric disorders. We assessed if ER availability in the human brain could be quantified using 16α-[18F]-fluoro-17β-estradiol ([18F]FES) positron emission tomography (PET). Procedures: Seven post‑menopausal women underwent a dynamic [18F]FES PET scan with arterial blood sampling. A T1-weighted MRI was acquired for anatomical information. After one week, four subjects received a selective ER degrader (SERD), four hours before the PET scan. Pharmacokinetic analysis was performed using a metabolite-corrected plasma curve as the input function. The optimal kinetic model was selected based on the Akaike information criterion and standard error of estimated parameters. Accuracy of Logan graphical analysis and standardized uptake value (SUV) was determined via correlational analyses. Results: The reversible two-tissue compartment model (2T4k) model with fixed K1/k2 was preferred. The total volume of distribution (VT) could be more reliably estimated than the binding potential (BPND). A high correlation of VT with Logan graphical analysis was observed, but only a moderate correlation with SUV. SERD administration resulted in a reduced VT in the pituitary gland, but not in other regions. Conclusions: The optimal quantification method for [18F]FES was the 2T4k with fixed K1/k2 or Logan graphical analysis, but specific binding was only observed in the pituitary gland. [ABSTRACT FROM AUTHOR]

Catalysts are often employed to enable nonisothermal reaction kinetic studies when tracking cure progression of polyurethane reactions. However, when quickly reacting, catalyzed materials are prepared through mixing followed by the addition of fillers or additives, subsequent processing of the partially reacted material becomes difficult. Here, chemorheology is used to track changes in viscoelastic properties of uncatalyzed polybutadiene‐diisocyanate reactions for multiple days, which quantifies the degree of cure during polymerization. Viscosity profiles are accurately captured by the two‐stage Arrhenius model (r2>0.95), and conversion progress is adequately represented by the Kamal–Sourour model (r2>0.76). Transition state analysis via Wynne–Jones–Eyring–Evans theory (WJEE) reveals the presence of an associative mechanism according to entropic and enthalpic activation energies ΔS# = −96.9 J K−1 and ΔH# = 36.4 kJ, respectively. These rheokinetic modeling results align with Fourier transform infrared spectroscopy findings. To the knowledge, no rheokinetic studies have tracked cure progress of this uncatalyzed system for the extended timeframe presented here. The cure profile also presents unique viscosity growth, representative of molecular weight buildup, compared to catalyzed systems. This finding emphasizes the novelty of applying previously developed chemorheological models to multiday thermosetting reactions within a flow field in a manner that is generalizable to many long‐term curing systems. [ABSTRACT FROM AUTHOR]

Shortwave ultraviolet light (UV-C) disinfection is an emerging technology used to enhance food safety by reducing the pathogen load. Computational fluid dynamics (CFD) served as a numerical simulation tool to calculate the average radiation intensity within a disinfection chamber. The resulting CFD data was employed to estimate the UV-C inactivation kinetic parameters for Escherichia coli O157:H7, Salmonella Typhimurium, and Listeria monocytogenes. Experimental procedures involved irradiating bacterial suspensions with UV-C doses ranging from 0 to 6.028 kJ/m2. The inactivation of S. Typhimurium was described using a log-linear equation, while UV-C survival curves for E. coli O157:H7 and L. monocytogenes were best fitted to Weibull model. Subsequently, the integration of CFD simulations and kinetic parameters enabled the estimation of UV-C doses approaching 6 kJ/m2 for the treatment of fresh-cut 'Tommy Atkins' mangoes inoculated with the mentioned microorganisms. This integrated approach partially predicted the inactivation of pathogens on the surface of mango spears. [ABSTRACT FROM AUTHOR]

This work studies the fermentation kinetics to produce mead using Saccharomyces cerevisiae, selected from three commercial yeasts to generate a product with better organoleptic characteristics and greater acceptance by a group of untrained tasters. The values of the kinetic parameters of the fermentation were obtained from a series of fermentations at laboratory scale, maintaining constant the initial concentration of biomass (1.5 g/L), the operating temperature (33 °C) and the pH (4) and varying the initial soluble solids concentration in four values (10, 16, 22 and 25 °Brix). Based on the experimental results, a mathematical modeling was developed to estimate the variables of interest. Thus, from the application of the Monod model, the saturation constant (Ks) of 336.6 g/L was obtained, with a maximum specific growth rate ( μ max ) of 0.071 h−1. Using the integrated logistic model, the experimental values were adjusted to obtain the average value of μ max of 0.0815 h−1. Finally, the maximum ethanol production rate (rpm) of 0.2621 g/L was obtained through the modified Gompertz model. Therefore, Monod, integrated logistic and modified Gompertz models were ideal mathematical tools to interpret the kinetic behavior of honey fermentations, predict and control this process, both on a laboratory scale and on a subsequent industrial scale. Thus, contributing to the knowledge of the dynamic behavior of mead production and its level of technological development. Fermentation for mead production with Saccharomyces cerevisiae. Monod, integrated logistic and modified Gompertz models checked for describing kinetics. Determination of key kinetic parameters for mead production in batch bioreactor. Influence of substrate concentration on mead production in a batch bioreactor. [ABSTRACT FROM AUTHOR]

In the post-COVID-19 era, the demand for polypropylene (PP) has been growing for uses for medical and food packaging applications, resulting in the generation of a huge amount of plastic waste. Pyrolysis has been widely used to convert plastic waste to liquid fuels. However, the capability of predicting product yields and compositions over a wide range of pyrolysis process conditions remains a challenge, especially for industrial-scale processes. This study aimed to develop a mathematical model that has predictive power for the pyrolysis of PP. To overcome the limitations of detailed kinetic data, a six-lump model was developed that consisted of plastic molecules, melted plastics, heavy and light fuel oil, non-condensable gas, char, and ten monomolecular, irreversible, first-order reactions. The initial values of the Arrhenius constants and activation energies were set based on the kinetic constants from the literature. The kinetic parameters were calibrated with an experimental dataset to give a < 10% difference between the compositions of the major products from the simulation and experimental data. The model was used to predict an optimum temperature for the production of pyrolysis oil, mass balances, carbon conversion, and energy efficiency of an industrial-scale integrated pyrolysis-condensation-combustion process using Aspen Plus. The simulation predicted that the proportion of pyrolysis oil was highest at 460 °C, and the product composition was 59.17% pyrolysis oil, 13.18% char, and 27.65% gas with carbon conversion of 87.30%, energy efficiency of 87.56%, and a higher yield of gasoline (0.3595 kg/kg of PP) than heavy diesel (0.2675 kg/kg of PP). [ABSTRACT FROM AUTHOR]

Particle size reduction is a commonly used pretreatment technique to promote methane production from anaerobic digestion (AD) of food waste (FW). However, limited research has focused on the effect of micron-sized particles on AD of FW. This research presented an ultrafine wet milling (UFWM) pretreatment method to reduce the particle size of FW particles. After four hours of milling, D90 was reduced to 73 μm and cumulative methane production boosted from 307.98 mL/g vs. to 406.75 mL/g vs. without ammonia inhibition. We evaluated the performance of the AD systems and explored their facilitation mechanisms. Kinetic analysis showed that the modified Gompertz model predicted experimental values most accurately. UFWM pretreatment increased the maximum methane production rate by 44.4% and reduced the lag time by 0.65 days. The mechanical stress and collisions of milling resulted in a scaly surface of the particles, which greatly increased the voids and surface area. A rise in the XPS peak area of the C–N and C=O bonds proved the promotion of the liberation of carbohydrates and fats. Further microbial community analysis revealed that the relative abundance of Bacteroidota and Methanosarcina were enriched by UFWM. Meanwhile, methane metabolism pathway analysis confirmed that module M00567, module M00357, and related enzymes were stimulated. This study provided a theoretical basis for UFWM pretreatment applications and improvements in AD of FW. [ABSTRACT FROM AUTHOR]

Mechanism models and model‐assisted process optimization play a vital role in biopharmaceutical industry. However, the parameter estimation remains a challenging task in modeling due to the presence of multiple local optima and ill‐conditioning. In this study, we firstly presented a comparative evaluation of particle swarm optimization (PSO), genetic algorithm (GA), and simulated annealing (SA) for parameter estimation and confirmed PSO was the most efficient approach. Then an improved PSO algorithm using second‐order oscillation and particle replacement strategies was developed to enhance fitting performance in fed‐batch cell culture modeling. The results of fitting and model validation demonstrated that the improved PSO could explore more reasonable parameters and leading to a significantly enhancement in predictive accuracy throughout the entire cell culture process under varying conditions. Moreover, 10 diverse fed‐batch experiments were conducted to validate the fitting abilities on different process condition and clones, the improved PSO method exhibited improvements in accuracy and universality of parameter estimation for modeling various cultivation processes, particularly those lacking any prior knowledge. This improved algorithm is implemented to make it available to both the scientific community and industry, offering customized solutions for specific projects. [ABSTRACT FROM AUTHOR]

The global prevalence of metal corrosion is a significant challenge due to its detrimental effect. Environmentally friendly and non-hazardous alternatives for harmful and poisonous synthetic corrosion inhibitors are urgently necessary due to increasing environmental concerns and regulations prohibiting their application. In this study, indole molecules were employed as carbon steel corrosion inhibitors in acidic conditions. Gravimetrical and scanning electronic microscope (SEM) analysis was used in a preliminary investigation of indole as an organic inhibitor. The results revealed that adding indole to carbon steel before exposing it to sulfuric acid slowed and induced resistance to corrosion. The indole affixed themselves to the steel carbon surfaces, producing a barrier/protection for carbon steel. The efficacy of the indole in preventing corrosion was determined through the weight loss method. Temperature and inhibitory concentration effects on inhibition effectiveness under varying parameters were also reported. The temperatures employed were between 298 K and 328 K, while the inhibitor concentrations ranged from 1.2 × 10−3 M to 7.6 × 10−3 M, and both parameters significantly influenced corrosion inhibition effectiveness. The inhibitory mixture attained optimum efficacy in inhibiting corrosion, at 81 %, when the lowest and highest respective temperature and concentration were applied. The kinetic analysis was conducted under a range of temperatures to determine the reaction mechanisms of the inhibitor. The thermal adsorption isotherm of the inhibitor indicated that the surface adhered to Langmuir's adsorption isotherm. Additionally, investigations on corrosion and inhibition using the electrochemical impedance spectroscopy method (EIS) were conducted. This study can provide in-depth knowledge for advancing inhibitory science and engineering to enhance corrosion resistance in acidic media.

In this study, a kinetic model of the heterogeneous photocatalytic degradation of acetaminophen and its main transformation products is presented. Kinetic photocatalytic modeling and photon absorption rate modeling were included. Monte Carlo method was used to model the photon absorption process. Experiments were carried out in a reactor operated in batch mode and TiO2 nanotubes were used as photocatalyst irradiated with 254 nm UVC. Kinetic parameters were estimated from the experiments data by applying a non-linear regression procedure. Intrinsic expressions to the kinetics of acetaminophen degradation and its main transformation products were derived. Model, kinetics and photon absorption formulations and parameters proved to be affordable for describing the photocatalytic degradation of acetaminophen, but improvements should be done for better description of formation and oxidation kinetics of main transformation products. The model should be tested with other pharmaceuticals and emergent pollutants to calibrate it and evaluate its applicability in a wide range of compounds.

IntroductionRecent evidence suggests the blood-to-brain influx rate (K1) in TSPO PET imaging as a promising biomarker of blood–brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF).MethodsThe method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test–retest dataset of [18F]DPA714 scans.ResultsComparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03–0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans.DiscussionThis evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers’ unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal.

This investigation focused on the Congo red uptake, as the azo dye, from an aqueous environment. Herein, ash derived from sunflower seed pulp waste (SSPA) was used as an eco-friendly low-cost adsorbent. Based on the BET results, the specific active surface area of SSPA was approximately 102 m2/g. The effect of the initial analyte concentration (10–50 mg/L), the concentration of the adsorbent (1–5 g/L), and the processing time (10–240 min) on the rate of Congo red uptake was also evaluated and optimized. According to the results, the maximum dye removal from synthetic solution (91.89%) was achieved at a dye concentration of 50 mg/L, an adsorbent concentration of 3 g/L, and a processing time of 180 min. The maximum SSPA capacity for Congo red uptake from aquatic solution was 15.34 mg/g, achieving under optimized operational conditions. The adsorption process of SSPA also follows a pseudo-second-order kinetic model (qe = 15.85 mg/g; R2 > 0.99), considering the results of BET and FTIR, suggesting that the rate-controlling step in analyte removal is the chemical interaction between functional groups in SSPA and used dye. Finally, the SSPA washing with different solvents showed that the adsorbent treated with 1 M sodium hydroxide still performed well after his five reuses. HIGHLIGHTS Sunflower seed pulp ash (SSPA) was prepared and applied as an eco-friendly low-cost adsorbent for Congo red uptake.; Experiments showed the rate-controlling step in dye adsorption is the chemical interaction of functional groups between SSPA and Congo red.; According to the washing process of the adsorbent used by different solvents, one molar solution had a high capacity to wash the SSPA.;

The catalytic hydrogenation of carbon dioxide to methanol represents a promising avenue for global warming alleviation. In the present study, the kinetics of high-pressure methanol synthesis from CO 2 hydrogenation over a Cu/ZnO/Al 2 O 3 catalyst were investigated. This study focused on developing a robust kinetic model based on a competitive single-active site Langmuir−Hinshelwood−Hougen−Watson (LHHW) mechanism and utilizing the model to investigate the influence of various operating conditions on the catalytic fixed-bed reactor performance, including temperature, total reactor pressure, feed composition, and gas hourly space velocity (GHSV). The model satisfied the physicochemical constraints to be thermodynamically consistent, and its prediction results of molar flow rates showed a satisfactory correlation of 99% with experimental data available in the literature. The kinetic modeling results revealed that the overall rate of methanol synthesis is inhibited by the surface concentration of formate. Furthermore, adsorbed H 2 and CO 2 were identified as the most abundant intermediates, constituting approximately 80% and 10% of surface coverage throughout the catalytic bed, respectively. According to the present model, relatively mild temperature and pressure ranges of 200–220 °C and 80–100 bar were deemed the optimal operating conditions for enhanced catalytic activity and selectivity towards methanol. These findings not only provide valuable insights into the chemical kinetics of CO 2 hydrogenation to methanol but also enable reliable catalytic reactor designs. [Display omitted] • A detailed chemical kinetics study of methanol synthesis over Cu/ZnO/Al 2 O 3 catalyst. • A robust competitive adsorption kinetic model proposed under industrial conditions. • 99% correlation obtained between model predictions and experimental data. • Adsorbed H 2 and CO 2 identified as the dominant reaction intermediates. • Model indicated a slower methanol synthesis rate than RWGS at T > 275 °C and P < 80 bar. [ABSTRACT FROM AUTHOR]

An analysis of an out‐of‐equilibrium cyclic reaction network which continuously converts a minor undesired product enantiomer to the desired major enantiomer by irreversible addition of chemical fuel and irreversible elimination of spent fuel is presented. The reaction network is maintained as long as fuel is added; interrupted fuel addition drives the system towards equilibrium, but the cyclic process restarts upon resumed fuel addition, as demonstrated by three consecutive fuel cycles. The process is powered by the hydrolysis of methyl cyanoformate to HCN and monomethyl carbonic acid, which decomposes to CO2 and MeOH. The time it takes to reach steady state depends on the rate of conversion of the fuel and decreases with increased conversion rate. Three catalysts, one metal catalyst and two enzymes, together constitute an efficient regulation system allowing control of the forward, backward and waste‐forming steps, thereby assuring the production of high yields of products with high enantiopurity. [ABSTRACT FROM AUTHOR]

This research work aimed at the synthesis and characterization of novel xanthan gum/polyacrylamide/polyvinyl pyrrolidone (XG/PAM/PVP)-based hydrogels for the delivery of the hydrophobic drug ibuprofen. The influence of crosslinker, biopolymer, and initiator amount on the hydrogel's swelling ratio, porosity, and gel fraction was also investigated. Several techniques like Powder X-ray Diffraction (PXRD), Attenuated Total Reflection-Fourier Transform Infrared spectroscopy (ATR-FTIR), Scanning Electron Microscopy (SEM), and Thermogravimetry Analysis (TGA) were employed to characterize the synthesized hydrogels. Sol–gel analysis revealed an increase in the gel fraction with a rise in the concentration of MBA, XG, and KPS. Porosity measurements indicated a greater porosity with higher XG and KPS amounts, while porosity decreased as the MBA amount increased. Furthermore, the presence of PVP in the hydrogel was observed to greatly enhance various properties, including gel fraction, swelling ratio, porosity, drug loading, and drug release percent. Notably, under alkaline conditions (pH 7.4), the swelling ratio and release of ibuprofen were significantly increased, as compared to acidic (pH 1.2). The ibuprofen release from the XG/PAM/PVP hydrogel is governed by a Fickian diffusion mechanism, and the Korsmeyer-Peppas model serves as the most appropriate model for elucidating the drug release kinetic in both pH 1.2 and 7.4. The pH-responsive nature exhibited by the XG/PAM/PVP hydrogel highlights its potential as a drug delivery system. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop and validate a unifying kinetic model for microvascular transport by introducing an impulse response function that incorporates essential physiological parameters and integrates key features of existing models. This new methodology combines a one-compartment model of fractional order with a model that uses the gamma distribution to describe the distribution of capillary transit times. Central to this model are two primary parameters: α , representing the kurtosis of residue times, and β - 1 , signifying the width of the distribution of capillary transit times within a tissue voxel. To validate this proposed model, data from dynamic contrast-enhanced magnetic resonance imaging (DCI-MRI) were employed and the findings were compared with three existing models. Using the Akaike information criterion for model selection, the results demonstrate that the integrative model, especially at elevated blood flow rates, frequently offers superior fits in comparison to constrained models. [ABSTRACT FROM AUTHOR]

Extracting valuable compounds from waste plant tissues is a challenging process. To better understand this process, kinetic modeling was used to study the extraction of phenolic compounds from the waste tissues of industrial strawberry (RF) and apple (GS) processing using green solvents. The experimental design variables included type of solvent (W: water, EtOH: ethanol 80%), solid–liquid ratio (1:20, 1:30, 1:40), and temperature (20, 70°C). The model of Peleg (MI) and an empirical model (MII) were applied to determine the kinetic constants for total phenolic compounds (TPC) and antioxidant capacity (AC). The phenolic compound profile was determined at each experimental assay. The extraction variables affected (p < 0.001) TPC and AC of RF and GS extracts. Using EtOH increased TPC extraction yields from both tissues (up to 62% for RF). The highest AC was determined in EtOH extracts at 20°C (119 and 25 μmol TE/g for RF and GS, respectively). Temperature, extraction ratio, and solvent type significantly affected the kinetic constants of both models. The study identified nine phenolic compounds from both waste tissues, with Agrimoniin being the main compound in RF (0.49 g/kg) and quercetin pentoxide being the main compound in GS (0.23 g/kg). There was no significant increase in TPC and AC of the extracts after 90 min at 20°C and 60 min at 70°C. The kinetic modeling of phenolic compound extraction from strawberry and apple agro‐industrial by‐products using green solvents enabled the determination of the best extraction conditions, promoting the use of these waste tissues by obtaining bioactive compounds with antioxidant potential. Practical Applications: This study provides valuable insight into the effective use of green solvents in extracting bioactive compounds, thereby promoting sustainable practices and reducing waste in the industrial processing of strawberries and apples. The kinetic modeling approach for recovering phenolic compounds from strawberry and apple agro‐industrial by‐products improves our comprehension of the influence of the extraction process variables on the phenolic compound profile and antioxidant capacity of these tissues. These findings highlight the potential of these waste tissues as an alternative source of bioactive compounds. By standardizing the extraction process and optimizing the utilization of agro‐industrial by‐products, the food industry can effectively reduce the environmental impact of these waste tissues and promote sustainable operations. Additionally, using green solvents aligns with the increasing demand for environmentally friendly practices, making it easier to turn strawberry and apple agro‐industrial processes into circular processes by eco‐friendly valorization of these biowastes. [ABSTRACT FROM AUTHOR]

Continuous ohmic heating (COH) is a novel thermal technology for fruit juice processing and preservation. The present work demonstrated the effect of COH parameters like electric field strength (EFS: 30–40 V/cm), isothermal holding (0–60 s), and temperature (70–90°C) on the inactivation of polyphenol oxidase (PPO) and peroxidase (POD) in standardized pineapple juice. Statistical parameters and Akaike information criteria were used to compare kinetic models like the first order, distinct isozymes, Weibull distribution, sigmoidal logistic, and fractional conversion for PPO and POD inactivation. The findings revealed that the COH parameters significantly affected the activities of both enzymes. A maximum inactivation of 68.2% of PPO and 82.2% of POD was observed at 90°C, 60 s, and 40 V/cm. The Weibull distribution model, compared to other models, was found to describe the inactivation kinetics better for both PPO (R2 > 0.99; RMSE < 0.0101) and POD (R2 > 0.98; RMSE < 0.042). The accuracy factor (Af) and bias factor (Bf) for both PPO (Af = 1.003–1.010; Bf = 1.000–1.004) and POD (Af = 1.007–1.072; Bf = 0.992–1.009) were closer to simulation line suggesting the accuracy of the Weibull model in predicting the enzyme inactivation. Also, Akaike increment (∆i < 2) substantially supported the Weibull model. The shape factor (n < 1) explained the tailing phenomenon of the enzymes. The PPO's scale factor (δ values) was higher than POD, suggesting higher thermal stability of PPO than POD. Thus, the Weibull model is a good tool for predicting the enzyme inactivation in COH‐treated standardized pineapple juice. Practical Applications: Continuous ohmic heating (COH) is a novel electro‐thermal technology that heats the fruit juice quickly, uniformly, and volumetrically. Generally, for inactivating spoilage enzymes like polyphenol oxidase and peroxidase during pineapple juice processing in an industrial set‐up, a conventional method of conduction and convection mode of heat transfer is used. This results in a high‐temperature gradient within the juice matrix, causing a problem of over‐ and under‐processing of juice. Ohmic heating is a potential and efficient way of inactivating these spoilage enzymes to a desired level in a shorter processing time. It can be used to preserve juice by extending its shelf life. COH can reduce the total heat damage to the juice by maintaining its flavor and nutrient compounds. Overall, ohmic heating is a versatile and effective technology for the continuous processing of fruit juice for improved product quality and production efficiency. [ABSTRACT FROM AUTHOR]

Cold Plasma (CP) is an emerging non‐thermal technology that preserves and decontaminates food. Kiwifruit juice spoilage enzymes polyphenol oxidase (PPO) and peroxidase (POD) were studied at 24‐36 kV, 2‐10 mm juice depth, and 2‐10 min treatment time using log‐linear, Weibull distribution, and logistic models. The Weibull and logistic model explained enzyme inactivation kinetics well based on goodness of fit (Coefficient of determination: 0.97‐0.99 & root mean square error: 0.11‐2.15) and validation indices (accuracy factor: 1‐1.06 and bias factor: 0.96‐1.04). The logistic model suited PPO and POD inactivation curves well, with the least Akaike weight in 71.29% and 61.45%, respectively. POD had a half‐maximal activity of 11.37, 5.22, and 3.60 min at 24 kV, 30 kV, and 36 kV at 6 mm juice depth, compared to 8.71, 4.41, and 2.51 min for PPO. This shows that POD is more CP‐resistant than PPO, making its inactivation in kiwifruit juice crucial. Practical Application: Kinetic modeling helps to comprehend the fundamental process and is suitable for improving the inactivation process and enhancing its efficacy. As a relatively primary method, mathematical models facilitate a greater comprehension of the mechanism and factors influencing the inactivation processes. This study involves the inactivation of PPO and POD to produce a stable kiwifruit juice. The inactivation of PPO and POD enzymes will prevent the undesirable enzymatic browning of juice. The kinetic data related to enzyme inactivation will help in deciding the process parameters like plasma voltage, juice depth, and treatment time for producing enzymatically stable kiwifruit juice. [ABSTRACT FROM AUTHOR]

Due to the application of unknown organic loading rate (OLR), many studies had reported ammonia inhibition if using chicken manure on commercial scale. Therefore, three different OLRs of (1.50, 3.00, and 4.50) g.VS/L-d were applied by the current study, which were labeled as Phase-I, Phase-II, and Phase-III in two semi-continuous stirring tank reactors (CSTR) termed as R-A and R-B. Wheat straw was pretreated with 7.5% H2O2 for consequent co-digestion with chicken manure and goose manure in both reactors. Experimental results concluded that Phase-II of Reactor-B (C/N = 25) proved optimal with methane enhancement capability of 260.14 mL/g.VS, 63.90% VS removal, and 56.76% chemical oxygen demand (COD) removal efficiency. To truly understand the reaction kinetics, first order-kinetics, cone model, transfer function model, and modified Gompertz model were employed and synergistic effects of co-digestion of chicken manure, goose manure, and thermally oxidized wheat straw were evaluated. Modified Gompertz model has provided best suitability and reliability with further kinetic predictions and explanations. Kinetic analysis and synergistic effect evaluations had validated the role of co-digestion in enhancing methane production. [ABSTRACT FROM AUTHOR]

The effect of water on the modification of acidic properties of Nb2O5 and Nb1.3MnOx catalysts was investigated using the cracking of cumene as model reaction, and compared to the behavior of a HZSM-5 catalyst. Nb1.3MnOx exhibited stronger Lewis acidity than Nb2O5, which translated into a higher selectivity towards α-methylstyrene formed on Lewis acid sites (LAS) by dehydrogenation of cumene. Steam enhanced strongly the conversion of cumene over both Nb-based catalysts. The products distribution on Nb-based catalysts was also deeply modified in the presence of steam, the selectivity towards α-methylstyrene decreasing strongly in favor of benzene, which is formed on Brønsted acid sites (BAS) by dealkylation of cumene. In contrast, the performances of HZSM-5 for cumene cracking and the products distribution were only marginally modified in the presence of steam. A kinetic model based on the elementary steps of the cumene reaction pathways (dealkylation and dehydrogenation) was used to estimate the ratio of LAS to BAS in absence and presence of water over Nb1.3MnOx. The activation energy of the cracking reaction was higher than that of the dehydrogenation reaction. The model described correctly the changes in the catalyst activity induced by addition of ≈2 V% of water, which resulted in a decrease in the [LAS]/[BAS] ratio from approximatively 3 to 1. [ABSTRACT FROM AUTHOR]

The array of rate constants (323 K) for the addition of peroxyl radicals of different structures to the π-bonds of unsaturated compounds was obtained. These data were analyzed using a combination of correlation and quantum chemical methods. The prospects of using Denisov's parabolic model are shown in comparison with classical linear correlations. It is noted that QSPR models using quantum chemical and structural descriptors can also be used to estimate the reactivity of reacting particles in this elementary act. The obtained kinetic information can be the basis for elucidating the detailed mechanism of oxidation of biologically significant molecules. [ABSTRACT FROM AUTHOR]

Accurate positron emission tomography (PET) data quantification relies on high-quality input plasma curves, but venous blood sampling may yield poor-quality data, jeopardizing modeling outcomes. In this study, we aimed to recover sub-optimal input functions by using information from the tail (5th–100th min) of curves obtained through the frequent sampling protocol and an input recovery (IR) model trained with reference curves of optimal shape. Initially, we included 170 plasma input curves from eight published studies with clamp [18F]-fluorodeoxyglucose PET exams. Model validation involved 78 brain PET studies for which compartmental model (CM) analysis was feasible (reference (ref) + training sets). Recovered curves were compared with original curves using area under curve (AUC), max peak standardized uptake value (maxSUV). CM parameters (ref + training sets) and fractional uptake rate (FUR) (all sets) were computed. Original and recovered curves from the ref set had comparable AUC (d = 0.02, not significant (NS)), maxSUV (d = 0.05, NS) and comparable brain CM results (NS). Recovered curves from the training set were different from the original according to maxSUV (d = 3) and biologically plausible according to the max theoretical K1 (53//56). Brain CM results were different in the training set (p < 0.05 for all CM parameters and brain regions) but not in the ref set. FUR showed reductions similarly in the recovered curves of the training and test sets compared to the original curves (p < 0.05 for all regions for both sets). The IR method successfully recovered the plasma inputs of poor quality, rescuing cases otherwise excluded from the kinetic modeling results. The validation approach proved useful and can be applied to different tracers and metabolic conditions. [ABSTRACT FROM AUTHOR]

The study of the oxidation of propane-ethylene mixtures by numerical kinetic modeling allowed us to establish that in the range of 400–600°C with an increase in the conversion of propane with an increase in temperature, the selectivity of propylene formation passes through a maximum whose position depends on the concentration of ethylene in the initial mixture. The addition of ethylene to the initial mixture leads to a reduction in propane consumption and an increase in the selectivity of propylene formation. The conditions under which ethylene introduced into the initial mixture is not consumed during the process are determined; thus, formally it can be considered as a catalyst, and the process of propane oxidation as proceeding in a pseudo-catalytic regime. [ABSTRACT FROM AUTHOR]

Nitroglycerin (NG) is commonly used as an ingredient in propellant formulations. In this study, a first automatically generated detailed kinetic model of this energetic material has been developed. The construction of this model was made possible by performing computations with the open source software package Reaction Mechanism Generator (RMG). To enable a faster convergence, significant intermediate species of NG decomposition and optimized operating conditions were indicated in the RMG input parameters. Thermochemical data related to significant decomposition species were derived from ab initio calculations at the DFT B3LYP/6-31 G(d,p) level of theory. To validate the RMG-built mechanism, simulations were performed with CHEMKIN-Pro. Computed species profiles from simulations were compared with flash pyrolysis measurements from the literature. Sensitivity analyses were performed on species mole fraction, and the most significant elementary reactions were identified. Some rate constant parameters were adjusted within the reaction rate uncertainty to improve the predictability of the model. Ignition delay times were computed for NG, and consistent trends were obtained when compared against to calculations for RDX and TNT using referenced model available in the literature. Although experimental data are scarce, this automated kinetic generation approach, applied to energetic materials, is to be highly promising. [ABSTRACT FROM AUTHOR]

SUMMARY: Potato (Solanum tuberosum) is a significant non‐grain food crop in terms of global production. However, its yield potential might be raised by identifying means to release bottlenecks within photosynthetic metabolism, from the capture of solar energy to the synthesis of carbohydrates. Recently, engineered increases in photosynthetic rates in other crops have been directly related to increased yield – how might such increases be achieved in potato? To answer this question, we derived the photosynthetic parameters Vcmax and Jmax to calibrate a kinetic model of leaf metabolism (e‐Photosynthesis) for potato. This model was then used to simulate the impact of manipulating the expression of genes and their protein products on carbon assimilation rates in silico through optimizing resource investment among 23 photosynthetic enzymes, predicting increases in photosynthetic CO2 uptake of up to 67%. However, this number of manipulations would not be practical with current technologies. Given a limited practical number of manipulations, the optimization indicated that an increase in amounts of three enzymes – Rubisco, FBP aldolase, and SBPase – would increase net assimilation. Increasing these alone to the levels predicted necessary for optimization increased photosynthetic rate by 28% in potato. [ABSTRACT FROM AUTHOR]

In the current era, there is a growing emphasis on the circular economy and the valorization of waste products. Bean processing industries generate substantial nutrient-rich waste laden with valuable phytochemicals. Understanding the leaching patterns and kinetics of major phytochemicals is key to designing better processes leading to increased sustainability. This review investigates phytochemical leaching mechanisms and kinetic modeling methods. Firstly we lay the foundation with a broad theoretical framework, and later deal with kinetic modeling approaches and promising areas for future research. Currently, the composition of industrial-scale bean wastewater remains undocumented in the open literature. Nonetheless, drawing from existing studies and general bean composition knowledge, we proposed a multi-phase leaching process. We hypothesize three distinct phases: initial leaching of phytochemicals from the outer seed coat, followed by a second phase involving polysaccharides, and concluding with a third phase wherein phenolic acids within the cotyledons leach into the hydration water. This review aims to shed light on the complex process of phytochemical leaching from common beans during hydration. By combining theoretical insights and practical modeling strategies, this work seeks to enhance our understanding of this phenomenon and ultimately contribute to the optimization of food processing methods with reduced environmental impact. [ABSTRACT FROM AUTHOR]

Background: Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly 13 C -enriched glucose ( 13 C 6 -Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups. Results: We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts' knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux. Conclusions: Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data. [ABSTRACT FROM AUTHOR]

This work reports an experimental and kinetic modeling study of NH 3 /CH 4 co-oxidation in O 2 /N 2 in a jet-stirred reactor (JSR) covering a reaction temperature of 900–1450 K, equivalence ratio of 0.5–2.0, and dilution degree of 0%–30% with H 2 O and CO 2 , respectively. Experimental results show that CO formation is inhibited by H 2 O dilution while enhanced by CO 2 dilution. NO formation is suppressed by either H 2 O or CO 2 dilution under lean condition, however these two diluents generally would accelerate NO formation under stoichiometric and rich conditions. Dong2022 mechanism is selected for further kinetic analysis for NO conversion under stoichiometric condition. It shows that N 2 H 2 plays a more significant role in NO generation in N 2 /CO 2 atmosphere. The reactions of NH + OH ↔ HNO + H and NH 2 + O ↔ HNO + H contribute the most for boosting NO formation under both H 2 O and CO 2 dilution conditions. • NH 3 /CH 4 co-oxidation experiment was conducted in JSR. • Effect of H 2 O and CO 2 dilution on NH 3 /CH 4 co-oxidation was studied. • Nine existing NH 3 /CH 4 reaction mechanisms were validated against experimental data. • Important reactions for NO formation were identified. [ABSTRACT FROM AUTHOR]

Purpose: Standardized uptake value (SUV) has been prevalently used to measure [68 Ga]Ga-PSMA-11 activity in prostate cancer, but it is susceptible to multiple factors. Parametric imaging allows for absolute quantification of tracer uptake and provides a better diagnostic accuracy that is crucial for lesion detection. However, the clinical significance of total-body parametric imaging of [68 Ga]Ga-PSMA-11 remains to be fully assessed. Therefore, the aim of our study is to delve into the diagnostic implications of total-body parametric imaging of [68 Ga]Ga-PSMA-11 PET/CT for patients with prostate cancer. Methods: Twenty prostate cancer patients were included and underwent a dynamic total-body [68 Ga]Ga-PSMA-11 PET/CT scan. An irreversible two-tissue compartment model (2T3k) was fitted for each tissue time-to-activity curve, and the net influx rate (Ki) was obtained. The image quality and semi-quantitative analysis of lesion-to-background ratio (LBR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between parametric images and SUV images. Results: Kinetic modeling using 2T3k demonstrated favorable model fitting in both normal organs and lesions. All of the lesions detected on SUV images (55–60 min) could be detected on Ki images. The correlation between Ki, SUVmean, and SUVmax in both normal organs and pathological lesions was found to be positive and statistically significant. Conversely, a moderate positive correlations were found between Ki and K1 (R = 0.69, P < 0.001; R = 0.61, P < 0.001) and Ki and k3 (R = 0.69, P < 0.001; R = 0.62, P < 0.001), in normal organs and pathological lesions, respectively. Visual assessment in Ki images showed less image noise and higher lesions conspicuity compared to SUV images. Ki image-derived LBR, SNR, and CBR of pathological lesions including primary tumors (PTs), lymph node metastases (LNMs) and bone metastases (BMs), exhibited remarkably higher folds (1.4–3.6 folds) compared to those derived from SUV of corresponding lesions. Conclusions: Total-body parametric imaging of [68 Ga]Ga-PSMA-11 enhanced lesion contrast and improved lesion detectability compared to SUV images. This may potentially serve as an imaging biomarker and theranostic tool for precise diagnosis and treatment evaluation in prostate cancer patients. [ABSTRACT FROM AUTHOR]

Cell-free production systems are increasingly used for the synthesis of industrially relevant chemicals and biopharmaceuticals. Cell-free systems often utilize cell lysates, but biocatalytic cascades based on recombinant enzymes have emerged as a promising alternative strategy. However, implementing efficient enzyme cascades is a non-trivial task and mathematical modeling and optimization has become a key tool to improve their performance. In this work, we introduce a generic framework for the model-based optimization of cell-free enzyme cascades based on a given kinetic model of the system. We first formulate and systematize seven optimization problems relevant in the context of cell-free production processes including, for example, the maximization of productivity or product yield and the minimization of overall costs. We then present an approach that accounts for parameter uncertainties, not only during model calibration and model analysis but also when performing the actual optimization. After constructing a kinetic model of the enzyme cascade, experimental data are used to generate an ensemble of kinetic parameter sets reflecting their variabilities. For every parameter set, systems optimization is then performed and the resulting solution subsequently cross-validated for all other parameterizations to identify the solution with the highest overall performance under parameter uncertainty. We exemplify our approach for the cell-free synthesis of GDP-fucose, an important sugar nucleotide with various applications. We selected and solved three optimization problems based on a constructed dynamic model and validated two of them experimentally leading to significant improvements of the process (e.g., 50% increase of titer under identical total enzyme load). Overall, our results demonstrate the potential of model-driven optimization for the rational design and improvement of cell-free production systems. The developed approach for systems optimization under parameter uncertainty could also be relevant for the metabolic design of cell factories. [Display omitted] • Generic framework for model-based optimization of cell-free enzyme cascades under parametric uncertainty is presented. • Optimization problems relevant for cell-free production processes are formulated. • Cross-validation of optimization results across parameter ensemble to deal with parameter uncertainty. • Application of the approach to cell-free synthesis of the sugar nucleotide GDP-fucose. • Experimental validation of predicted optimization results improves titer, yield, and enzyme load. [ABSTRACT FROM AUTHOR]

This paper deals with the proposition of a kinetic model for the direct synthesis of DME via CO2 hydrogenation in view of the necessary optimization of the catalytic system, reactor design, and process strategy. Despite the fact that DME synthesis is typically treated as a mere combination of two separated catalytic steps (i.e., methanol synthesis and methanol dehydration), the model analysis is now proposed by taking into account the improvements related to the process running over a hybrid catalyst in a rational integration of the two catalytic steps, with boundary conditions properly assumed from the thermodynamics of direct DME synthesis. Specifically, the CO2 activation step at the metal–oxide interface in the presence of ZrO2 has been described for the first time through the introduction of an ad hoc mechanism based on solid assumptions from inherent studies in the literature. The kinetic modeling was investigated in a tubular fixed-bed reactor operating from 200 to 260 °C between 1 and 50 bar as a function of a gas hourly space velocity ranging from 2500 to 60,000 NL/kgcat/h, in a stoichiometric CO2/H2 feed mixture of 1:3 v/v. A well-detailed elementary mechanism was used to predict the CO2 conversion rate and identify the key reaction pathways, starting with the analysis of the implicated reactions and corresponding kinetic mechanisms and expressions, and finally estimating the main parameters based on an appropriate modeling of test conditions. [ABSTRACT FROM AUTHOR]

Half‐life values of organic peroxides at elevated temperature conditions are important in characterizing the reactivity and are often available in literature or through vendors. However, there is often lack of details/accuracy on methods used to obtain these values, as well as differences in methods across vendors and publications, thus resulting in discrepant reactivity profile. To address this, a method involving calorimetric experiment and thermo‐kinetic modeling was developed. The current approach was applied on five peroxides samples to obtain kinetic parameters and estimate their half‐life in the temperature range of interest. The measurements were performed by DSC under non‐isothermal conditions on the dilute peroxide solutions (∼0.12 M in mineral oil) and the data were kinetically treated according to three model‐based and one model‐free kinetic equations. A very good agreement was found between the half‐life calculated by all kinetic methods, but significant differences were noticed with the kinetic parameters reported in literature. Additionally, the obtained half‐life results, based on non‐isothermal measurements developed kinetic models, were validated through isothermal calorimetric testing. Given the accuracy and robustness of our results, the current method can be applied to estimate half‐life of organic peroxides at elevated temperature conditions. [ABSTRACT FROM AUTHOR]

The conversion of glycerol into 1,3‐propanediol (1,3‐PDO) has gained significant attention as a sustainable pathway within the biodiesel production chain. Limosilactobacillus reuteri, a bacterium capable of efficiently converting glycerol to 1,3‐PDO, holds promise for this application. In industrial biotechnology, the development of kinetic models is important for bioreactor design, process analysis and scalability, supporting the advancement of biorefineries and the bioeconomy. This study focuses on investigating the kinetics of co‐fermentation of glucose and glycerol by L. reuteri, utilizing data from previous batch culture experiments. Three different models were evaluated for these batch runs, and the parameters were adjusted using the Levenberg–Marquardt algorithm in conjunction with an integration method. The results from these previous batch experiments indicate that pH did not significantly influence the specific growth rate of the bacterium. However, as expected, reducing the temperature from 37 to 30°C resulted in a 60% reduction in the growth rate. Moreover, continuous co‐fermentation experiments were conducted, and a simple kinetic model was proposed. The advantage of the continuous process is that the productivity of 1,3‐PDO is 3.5 times higher compared with co‐fermentation in batch mode. Notably, this study represents the first attempt to model continuous co‐fermentation under a range of dilution rates (0.25–0.9 h−1), identifying a dilution rate of 0.5 h−1 as the optimal condition to produce 1,3‐PDO, considering productivity and substrate conversion. The findings of this research contribute valuable insights for future investigations on the viability of 1,3‐PDO production from glycerol, particularly within the context of waste valorization. [ABSTRACT FROM AUTHOR]

The rapid expansion of Indian cities, their economic development and increasing concerns for the segregation of Municipal Solid Waste (MSW) lead towards more production of Organic Fraction of Municipal Solid Waste (OFMSW) in most cities of developing nations. Organic Fraction of Municipal Solid Waste is the most favorable substrate in meeting goals of waste to energy in recent times using anaerobic digestion. The bio-flocculated sludge produced in Secondary Settling Tank (SST) (used from post UASB) can be a potential co-substrate for the co-digestion of OFMSW, against its independent disposal system in a conventional sewage treatment plant. The majority of Indian states have favorable meteorological conditions (20–40 °C for 9 to 10 months of a year) for anaerobic digestion. Various mixing ratios of OFMSW: Bio-flocculated sludge from SST at 50:50, 75:25, 90:10, 0:100, and 100:0 (% wet weight) are used in the current anaerobic batch reactor study. Co-digestion exhibits a quick phase of acclimatization and raises methane production. With anaerobic co-digestion, the maximum specific methane gas yield is 369.28 ± 55.51 L/kgVSadded against 167.78 ± 16.45 L/kgVSadded in batch research mono-digestion of OFMSW. The results of a kinetic analysis using the Modified Gompertz model and Logistic Function model for methane production demonstrate the acceptance of the experimental methane yield. The lab-scale process employed in this study is having the advantage of simplicity & economic affordability for replicating its use in large scale plants in developing nations like India. [ABSTRACT FROM AUTHOR]

Anaerobic co-digestion (ACoD) of cow dung (CD) and maize cob (MC) may be envisaged as the best way to enhance biomethane formation and production of nutrient-enriched fertilizer for the implementation of a circular bio-economic system. The study aimed to find out the optimum ratio for the highest biogas production to produce heat and energy and also the generation of nutrient-enriched organic fertilizer to use in crop land. A batch study was carried out for 99 days in an incubator maintaining 35 ± 1 °C temperature for seven different test groups of CD and MC (100:0, 90:10, 70:30, 50:50, 30:70, 10:90, and 0:100). The highest biogas production (356.6 ± 21.2 mL/gVS) was at 50:50 ratio with 138.05% and 32.02% increments compared to the digestion of CD and MC alone, respectively. Kinetic modeling showed the best fit using a Logistic model to evaluate ACoD of CD and MC mathematically. ACoD of available CD and MC in Bangladesh could produce 716.63 GWh/yr electricity for consumption and a large volume of nitrogen-enriched fertilizer to use in nitrogen-deficit soil. There was no significant difference in nutrient enrichment among different test groups. Awareness about ACoD technology and proper use of digestate might bring this technology to field-level utilization and thus help to implement the circular bio-economic concept through zero waste generation. [ABSTRACT FROM AUTHOR]

The Claus process is a sulfur recovery unit wherein hydrogen sulfide is converted into the elemental sulfur. This study aims to model the thermal section of the Claus process, which consists of a reaction furnace and a waste heat boiler, as a configuration of two reactors, and subsequently optimize the entire section. Two different reduced kinetic schemes were provided for both units. Using the validated kinetics, mathematical models were developed. The waste heat boiler was modeled as a plug flow reactor with heat transfer, instead of a heat exchanger. The main objective was to maximize the amount of elemental sulfur at the end of the thermal section. Additionally, maximizing the amount of steam generated in the WHB was considered as a secondary objective, and the multi-objective optimization problem was solved. The sulfur production was improved 14.1% and 30% as a result of single- and multi-objective optimization studies. In addition, as an alternative, the Taguchi method was also used for optimization studies, and optimum values were determined. Using the Taguchi method, we determined that an increase in sulfur production by 24% is possible. [ABSTRACT FROM AUTHOR]

In the quest for maximum conversion of sucrose into 1-kestose using fructosyltransferases in a continuous reactor, consideration of the reversible reactions at competing concentrations of sucrose and 1-kestose is crucial. In this study, a kinetic model based on a combined approach of rapid equilibrium and steady-state kinetics was developed to predict the profile of FOS production using recombinant sucrose: sucrose 1-fructosyltransferase from Festuca arundinacea produced in Pichia pastoris. The purified enzyme selectively converted sucrose into 1-kestose with a final yield of 0.66 g/g sucrose consumed. The reaction rate laws adequately described the kinetic profile of the substrate and the products and accurately predicted the composition of the reaction mixture. The model was fitted to experimental data obtained at three enzyme dosages and three initial sucrose concentrations. The model could predict the effect of substrate concentration on initial rate kinetics, half-saturation constant, and transferase to hydrolase ratio. For the known values of initial sucrose and enzyme concentration, the optimum reaction time and the required dilution rate were predicted for the development of a continuous process to produce 1-kestose-enriched short-chain FOS. A volumetric productivity of ∼110 g/L/h of 1-kestose with 40 % carbohydrate composition in the permeate flux was demonstrated.

Consuming vegetables is linked to health benefits. Onion flower stalk (OFS) is a green vegetable with a mild onion flavor and is widely consumed in South Asia. The objectives of this study were to evaluate and understand the effect of boiling time (5, 10, 15, and 20 min at 100 °C) on physicochemical, bioactive compounds, and antioxidant activity of OFS. After boiling, moisture content and pH increased, whereas total soluble solids, water activity, titratable acidity, and ascorbic acid content decreased with increasing boiling time. The ascorbic acid content of fresh OFS was 20.59 mg/100 g fresh weight (FW), which decreased by 71.45 % after 20 min of boiling. The total phenolics, flavonoids, and tannin content in fresh OFS were 517.16 mg GAE/kg FW, 341.55 mg QE/kg FW and 517.28 mg TAE/kg FW, respectively. However, prolonged boiling caused a damaging effect on these bioactive compounds. It was observed that 20 min of boiling caused about 55.50 % loss in total phenolic, 58.44 % loss in total flavonoids, and 55.88 % loss in total tannin. The decrease in antioxidant capability was associated with the depletion of phytochemicals. The results also demonstrated that the ethanolic extract of OFS was effective in DPPH free radical scavenging activity. For extended boiling, the IC50 values rose gradually, indicating a decrease in antioxidant activity. Kinetic modeling showed that a first order model could more accurately anticipate changes in ascorbic acid and bioactive components with a higher R2. Findings from this research would be useful in designing thermal processing equipment for fruits and vegetables.

The pyrolysis of siloxane precursors, such as tetraethoxysilane (TEOS), is commonly employed in the flame synthesis and chemical vapor deposition of silica nanoparticles. In this work, the flow reactor pyrolysis of TEOS is studied using gas chromatography (GC) and synchrotron vacuum ultraviolet photoionization mass spectrometry (SVUV-PIMS), and the congener substitution effects from the central C atom to the central Si atom are investigated through comparison with its hydrocarbon counterpart tetraethoxymethane (TEOM). Pyrolysis models of TEOS and TEOM are constructed and validated against the measured results. Modeling analysis, including rate of production analysis and sensitivity analysis, provides insights into chemistry in fuel consumption and product formation. In contrast, the observations of silicon-containing products in SVUV-PIMS experiments provide evidence for crucial decomposition pathways of TEOS. It is observed that TEOS exhibits significantly higher stability than TEOM under pyrolysis conditions. The most abundant products in the pyrolysis of TEOS and TEOM are ethylene and ethanol, and TEOS produces more hydrocarbon products than TEOM. The lower pyrolysis reactivity of TEOS is attributed to the slower unimolecular decomposition reaction which dominates the decomposition of TEOS than TEOM. This can be explained by the hindrance of the extremely strong Si-O bond resulting from the significantly different electronegativity between Si and O. The higher initial decomposition temperature of TEOS enhances the contribution of other decomposition channels, such as C-C bond dissociation and H-abstraction reactions, in TEOS consumption. This leads to the abundant formation of hydrocarbon productions such as methane, ethane, and acetaldehyde. As the main pyrolysis product, the ethanol produced by TEOM pyrolysis is four times that of TEOS due to the congener substitution effects. The ethanol formation pathway in TEOS pyrolysis is different from that in TEOM pyrolysis, which is mainly formed via a newly proposed multi-step mechanism, resulting in a lower yield in TEOS pyrolysis.

ObjectiveWe present an algorithm to estimate the delay between a tissue time-activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics.MethodsWhole-body scans of 15 patients divided equally among three tracers, namely [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, which were used in development and testing of the algorithm. Delay times were estimated by fitting the cumulatively summed input function and tissue time-activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation: name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time-activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution.ResultsOur proposed model performs better for low signal-to-noise ratio time-activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time-activity curves showed only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays.ConclusionThe algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling.

Abstract Catalysts are often employed to enable nonisothermal reaction kinetic studies when tracking cure progression of polyurethane reactions. However, when quickly reacting, catalyzed materials are prepared through mixing followed by the addition of fillers or additives, subsequent processing of the partially reacted material becomes difficult. Here, chemorheology is used to track changes in viscoelastic properties of uncatalyzed polybutadiene‐diisocyanate reactions for multiple days, which quantifies the degree of cure during polymerization. Viscosity profiles are accurately captured by the two‐stage Arrhenius model (r2>0.95), and conversion progress is adequately represented by the Kamal–Sourour model (r2>0.76). Transition state analysis via Wynne–Jones–Eyring–Evans theory (WJEE) reveals the presence of an associative mechanism according to entropic and enthalpic activation energies ΔS# = −96.9 J K−1 and ΔH# = 36.4 kJ, respectively. These rheokinetic modeling results align with Fourier transform infrared spectroscopy findings. To the knowledge, no rheokinetic studies have tracked cure progress of this uncatalyzed system for the extended timeframe presented here. The cure profile also presents unique viscosity growth, representative of molecular weight buildup, compared to catalyzed systems. This finding emphasizes the novelty of applying previously developed chemorheological models to multiday thermosetting reactions within a flow field in a manner that is generalizable to many long‐term curing systems.