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The drug release system is a process in which a bioactive substance discharged from a drug product and enters the process of absorption, distribution and metabolism to deliver its pharmacological action. The drug release is maintained at a specific rate to maximize the benefits as well as to suppress the side impacts. The release rate behaviour is affected by physiological conditions such as ion charge, pH level and enzymatic environment. Since the intestinal tract itself varies broadly in a pH environment, hence it is important to study the profile of drug release in different pH conditions. Mathematical model turns out very useful in predicting the drug release as well as reducing experimental works. The objective of this work was to study the mathematical model in describing the drug release profile in gastrointestinal tract liquid simulation. The release profiles of furosemide and sodium-iron chlorophyllin encapsulation were studied in the pH ranges 1.3-1.5 and 6.8-7.4 to simulate the different part of gastrointestinal tract acidity. The Korsemeyer-Peppas, Weibull and Gompertz were applied in describing the profile. Korsmeyer-Peppas model shows more superior (R2>0.912) than Weibull and Gompertz in describing the release kinetic of furosemide and sodium-iron chlorophyllin encapsulations in both pHs of GTS. The n values of Korsmeyer-Peppas are mostly less than 0.5 suggesting the release mechanism was governed by diffusion.

This study aims to assess kinetic modelling of the solid–liquid extraction process of total polyphenolic compounds (TPC) from apple pomace (AP). In this regard, we investigated the effects of temperature and solvent (i.e. water, ethanol, and acetone) on TPC extraction over various periods. The highest TPC yield of 11.1 ± 0.49 mg gallic acid equivalent (GAE)/g db (dry basis) was achieved with a mixture of 65% acetone–35% water (v/v) at 60 °C. The kinetics of the solvent-based TPC extraction processes were assessed via first-order and second-order kinetic models, with an associated investigation of the kinetic parameters and rate constants, saturation concentrations, and activation energies. The second-order kinetic model was sufficient to describe the extraction mechanism of TPC from AP. This study provides an understanding of the mass transfer mechanism involved in the polyphenolic compound extraction process, thus facilitating future large-scale design, optimization, and process control to valorize pomace waste.

The choice of activating agent for the thermochemical production of high-grade activated carbon (AC) from agricultural residues and wastes, such as feedstock, requires innovative methods. Overcoming energy losses, and using the best techniques to minimise secondary contamination and improve adsorptivity, are critical. Here, we review the importance and influence of activating agents on agricultural waste: how they react and compare conventional and microwave processes. In particular, adsorbent pore characteristics, surface chemistry interactions and production modes were compared with traditional methods. It was concluded that there are no best activating agents; rather, each agent reacts uniquely with a precursor, and the optimum choice depends on the target adsorbent. Natural chemicals can also be as effective as inorganic activating agents, and offer the advantages that they are usually safe, and readily available. The use of a microwave, as an innovative pyrolysis approach, can enhance the activation process within a duration of 1–4 h and temperature of 500–1200 °C, after which the yield and efficiency decline rapidly due to molecular breakdown. This study also examines the biomass milling process requirements; the influence of the dielectric properties, along with the effect of washing; and experimental setup challenges. The microwave setup system, biomass feed rate, product delivery, inert gas flow rate, reactor design and recovery lines are all important factors in the microwave activation process, and contribute to the overall efficiency of AC preparation. However, a major issue is a lack of large-scale industrial demonstration units for microwave technology.

The correct determination of the kinetic model and the kinetic parameters that describe a heterogeneous process is key to accurately predicting its progress within a wide range of conditions, which is one of the main purposes of kinetic analysis. Albeit ideal kinetic models continue to be used to gain insight about the process mechanism, they are constrained by certain assumptions that are rarely met in real experiments and limit their applicability. This is the case of contracting (or interface) kinetic models, which are one of the most commonly used. Thus, the ideal kinetic model R 2 is derived by assuming a cylindrical contraction in the radial direction but not contemplating the possibility of a contraction in the direction of the axis of the cylinder. Moreover, in the case of the ideal model R 3, it is assumed that contraction takes place simultaneously in particles of identical dimensions in all three directions of space (spheres or cubes). Here, it is revisited this type of model, and it is considered the contraction of particles with different geometries, namely cylinders with different aspect ratios and rectangular cuboids. Besides, a novel generalized interface reaction model is proposed, which covers all the studied cases and broadens the range of applicability to more complex situations involving different geometries and inhomogeneous particle sizes. Finally, the proposed model is applied to the analysis of the experimental thermal dissociation of ammonium nitrate, previously described in the literature as a sublimation process. It is proved that the novel kinetic model provides a more accurate description of the kinetics of the reaction and better prediction capabilities.

The standard method for determining the biomass composition, in terms of main lignocellulosic fraction (hemicellulose, cellulose and lignin) contents, is by chemical method; however, it is a slow and expensive methodology, which requires complex techniques and the use of multiple chemical reagents. The main objective of this article is to provide a new efficient, low-cost and fast method for the determination of the main lignocellulosic fraction contents of different types of biomasses from agricultural by-products to softwoods and hardwoods. The method is based on applying deconvolution techniques on the derivative thermogravimetric (DTG) pyrolysis curves obtained by thermogravimetric analysis (TGA) through a kinetic approach based on a pseudocomponent kinetic model (PKM). As a result, the new method (TGA-PKM) provides additional information regarding the ease of carrying out their degradation in comparison with other biomasses. The results obtained show a good agreement between experimental data from analytical procedures and the TGA-PKM method (±7%). This indicates that the TGA-PKM method can be used to have a good estimation of the content of the main lignocellulosic fractions without the need to carry out complex extraction and purification chemical treatments. In addition, the good quality of the fit obtained between the model and experimental DTG curves (R2Adj = 0.99) allows to obtain the characteristic kinetic parameters of each fraction.

Crystal violet (CV) synthetic dyes are well known in the dyeing industry for their mitotic and mutagenic poisoning. CV dye being a toxic organic dye is responsible for serious health issues as well as environmental damage. In this study, an inexpensive biosorbent (white clover: Trifolium repens ) stem powder was tested for the adsorption of CV dye (cationic dye) from an aqueous solution. The batch adsorption measurements were designed to find out the influence of contact time, pH, adsorbent dose, and dye concentration, for dye removal. The operation parameters studied are the contact time (20 to 160 min), initial dye concentration (10–100 mg/L), dose (0.1–1 g), and pH, (1–10). At optimum conditions, maximum percent removal of 92.997% and adsorption capacity value of 1.952 mg/g was achieved at pH 2, adsorbent dose (1 g), and contact time (140 min), and dye concentration (70 ppm). The results suggested that the removal of CV rose with the contact time and adsorbent dose. Langmuir and Freundlich isotherm models were applied to the equilibrium adsorption data, and data were perfectly fitted to Langmuir isotherm model. Pseudo-first-order and pseudo-second-orders were applied to the data, and it was found that the pseudo-second-order kinetic model was best fitted to the experimental data. It was also revealed that the stem powdered of the Trifolium repens plant can be employed as a useful adsorbent to remove cationic CV dye from different water samples (tap, river and distilled). Furthermore, the performance of adsorbent was also evaluated in saline water containing sodium chloride, potassium chloride and manganese chloride salts to check the effect of various ions on the performance of adsorbent and it was observed that the adsorbent showed excellent performance in saline water. Moreover, a comparative study was performed to check the efficiency of different commercial adsorbents (silica gel and active carbon) and to compare their performance with our study. All these experiments revealed that the biosorbent used in this study effectively removes contaminating dyes from industrial wastewater and as well as saline water and thus, can be used for the treatment of wastewater at the commercial level.

The growth of colloidal metal nanocrystals typically involves an autocatalytic process, in which the salt precursor adsorbs onto the surface of a growing nanocrystal, followed by chemical reduction to atoms for their incorporation into the nanocrystal. Despite its universal role in the synthesis of colloidal nanocrystals, it is still poorly understood and controlled in terms of kinetics. Through the use of well-defined nanocrystals as seeds, including those with different types of facets, sizes, and internal twin structure, here we quantitatively analyze the kinetics of autocatalytic surface reduction in an effort to control the evolution of nanocrystals into predictable shapes. Our kinetic measurements demonstrate that the activation energy barrier to autocatalytic surface reduction is highly dependent on both the type of facet and the presence of twin boundary, corresponding to distinctive growth patterns and products. Interestingly, the autocatalytic process is effective not only in eliminating homogeneous nucleation but also in activating and sustaining the growth of octahedral nanocrystals. This work represents a major step forward toward achieving a quantitative understanding and control of the autocatalytic process involved in the synthesis of colloidal metal nanocrystals.

Industry represents a fundamental component of modern society, with the generation of massive amounts of industrial waste being the inevitable result of development activities in recent years. Red mud is an industrial waste generated during alumina production using the Bayer process of refining bauxite ore. It is a highly alkaline waste due to the incomplete removal of NaOH. There are several opinions in both the literature and legislation on the hazards of red mud. According to European and national legislation, this mud is not on the list of hazardous wastes; however, if the list of criteria are taken into account, it can be considered as hazardous. The complex processing of red mud is cost-effective because it contains elements such as iron, manganese, sodium, calcium, magnesium, zinc, strontium, lead, copper, cadmium, bismuth, barium and rare earths, especially scandium. Therefore, the selection of an extraction method depends on the form in which the element is present in solution. Extraction is one of the prospective separation and concentration methods. In this study, we evaluated the kinetic modelling of the solid–liquid acid extraction process of predominantly scandium as well as other elements present in red mud. Therefore, three acids (HCl, HNO3 and H2SO4) at different concentrations (10, 20 and 30%) were targeted for the extraction of Sc(III) from solid red mud. Specific parameters of the kinetics of the extraction process were studied, namely the solid:liquid ratio, initial acid concentration, contact time and temperature. The extraction kinetics of Sc(III) with acids was evaluated using first- and second-order kinetic models, involving kinetic parameters, rate constants, saturation concentration and activation energy. The second-order kinetic model was able to describe the mechanism of Sc(III) extraction from red mud. In addition, this study provides an overview on the mechanism of mass transfer involved in the acid extraction process of Sc(III), thereby enabling the design, optimization and control of large-scale processes for red mud recovery.

In this study, we explore a new method based on color variation data to derive the kinetics of the entire process of the hydration of alkali-activated slag (AAS). Using this image analysis technique, we can monitor the induction period that cannot be observed using conventional microcalorimetry techniques. Color variation was recorded across a sequence of 9999 images, which were processed via MATLAB software package. Further, an average pixel value (APV) was determined to represent the color in each image. Reaction parameters, such as color variation velocity v(t), reaction speed ε(t), and hydration degree α(t), that govern the entire hydration process were determined. On the basis of the reaction parameters and a Krstulovic–Dabic kinetic model, integral and differential equations were derived to simulate the three basic processes of AAS hydration. Equations describing the reaction kinetics of AAS with solutions of three different concentrations of NaOH were extracted using this method.

There is a lack of literature reporting the measurement and prediction of biochemical methane potential (BMP) of vegetable crop residues (VCRs) and similarly, the kinetic assessment on the anaerobic digestion process of VCR is rarely investigated. In this paper, the BMP tests of five different vegetable (snap bean, capsicum, cucumber, eggplant, and tomato) crop residues were conducted at feed to inoculum ratio (F/I) of 2.0 under mesophilic (36 ± 1 °C) conditions. A series of single-variable and multiple-variable regression models were built based on organic components (hemicellulose, cellulose, lignin, total fat, total sugar, and crude protein) for BMP prediction. Three kinetic models, including the first-order kinetic model, the Chen and Hashimoto model, and the modified Gompertz model, were used to simulate the methane yield results of VCR and obtain valuable model parameters simultaneously. As a result, the BMPs and volatile solids (VS) degradation degree of different VCRs were respectively in the range of 94.2–146.8 mL g−1 VS and 40.4–49.9%; the regression prediction models with variables lignin (R2 = 0.704, p = 0.076), variables crude protein and lignin (R2 = 0.976, p = 0.048), and variables total fat, hemicellulose, and lignin (R2 = 0.999, p = 0.027) showed the best performance on BMP prediction among the single-factor, two-factor, and three-factor models, respectively. In addition, compared to the other two kinetic models, the modified Gompertz model could be excellently fitted (R2 = 0.986–0.998) to the results of BMP experiment, verification deviations within 0.3%.