The separation and extraction of chrysin from active ingredients of natural products are of great significance, but the existing separation and extraction methods have certain drawbacks. Here, chrysin molecularly imprinted nanofiber membranes (MINMs) were prepared by means of electrospinning using chrysin as a template and polyvinyl alcohol and natural renewable resource rosin ester as membrane materials, which were used for the separation of active components in the natural product. The MINM was examined using Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). The adsorption performance, adsorption kinetics, adsorption selectivity, and reusability of the MINM were investigated in static adsorption experiments. The analysis results show that the MINM was successfully prepared with good morphology and thermal stability. The MINM has a good adsorption capacity for chrysin, showing fast adsorption kinetics, and the maximum adsorption capacity was 127.5 mg·g−1, conforming to the Langmuir isotherm model and pseudo-second-order kinetic model. In addition, the MINM exhibited good selectivity and excellent reusability. Therefore, the MINM proposed in this paper is a promising material for the adsorption and separation of chrysin.
Acrylpimaric acid ethylene glycol acrylate was used as the cross-linking agent to prepare rosin-based polymer microspheres through membrane emulsification–microsuspension polymerization. The prepared microspheres were used as the stationary phase in high-performance liquid chromatography for the separation of polycyclic aromatic hydrocarbons (PAHs) and two analogues of alkaloids. Five PAHs (benzene, naphthalene, fluorene, pyrene, and benzo(e)pyrene) were well separated in the rosin-based polymer column with the resolution (Rs) of 6.088 ± 0.006, 5.759 ± 0.017, 7.019 ± 0.020, and 8.584 ± 0.063. A linear relationship was observed for the carbon numbers of PAHs and lnK as obtained with the equation of ln k = 0.22nc – 2.45, R2 = 0.996 . The rosin-based polymer columns were also employed to separate theophylline–caffeine and camptothecin–10-hydroxy-camptothecin, and the good results were obtained with the Rs of 4.617 ± 0.005 and 2.245 ± 0.049, respectively.
Chrysin is a natural bioactive molecule with various groups, and it has been a challenge to separate and enrich chrysin from natural products. Molecularly imprinted polymers have been widely used in the extraction of natural products, but the number and type of functional monomers limits the separation effect. The synergistic action of multiple functional monomers can improve the separation effect. In this paper, molecularly imprinted polymers (Bi-MIPs) were prepared using methacrylic acid and acrylamide as binary functional monomers for the separation and enrichment of chrysin. The Bi-MIPs were characterized using thermogravimetric analyzer (TGA), Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM). The performances of Bi-MIPs were assessed, which included adsorption isotherms, selective recognition and adsorption kinetics. The experimental results show that Bi-MIPs are shaped as a uniform sphere with an abundant pocket structure on its surface. The adsorption of chrysin on the Bi-MIPs followed a pseudo-second-order and adapted Langmuir–Freundlich isotherm models. The adsorption performance of the Bi-MIPs was determined at different temperatures, and the Bi-MIPs showed excellent adsorption performance at 30 °C. The initial decomposition temperature of the Bi-MIPs was 220 °C. After five times of adsorption and desorption, the adsorption performance of the Bi-MIPs decreased by only 7%. In contrast with single functional monomer molecularly imprinted polymers (Si-MIPs), the Bi-MIPs showed excellent specificity, with an imprinting factor of 1.54. The Bi-MIPs are promising materials in the separation and enrichment of chrysin for their high adsorption capacity, low cost and being environmentally friendly.
Alkaloids are important natural products that exhibit a wide spectrum of pharmacological activities. To efficiently separate and purify them, a rosin‐based polymer‐bonded silica stationary phase in high‐performance liquid chromatography was synthesized via the surface radical polymerization of ethylene glycol maleic rosinate acrylate and methacrylic acid onto functionalized silica. The stationary phases, columns, optimization of chromatographic conditions for alkaloids, and thermodynamic behavior of the analytes on the column were fully studied. Under the optimized conditions, the prepared column efficiently purified natural camptothecine, caffeine, and evodiamine with the corresponding purities of 92, 96, and 97%. With this work, we have developed an efficient approach to isolate alkaloids and promoted the research on rosin‐based materials in biomedicine and analytical chemistry.
The current research aims to investigate the parameters’ effect on the confinement coefficient, Ks, forecast using machine learning. Because various parameters affect the Ks, a new computational model has been developed to investigate this issue. Six parameters are among the effective parameters based on previous research. Therefore, according to the dimensions of the variables in the problem, a supply–demand-based optimization (SDO) model was developed. The performance of this model is directly dependent on its main parameters, such as market size and iteration. Then, to compare the performance of the SDO model, classical models, including particle swarm size (PSO), imperialism competitive algorithm (ICA), and genetic algorithm (GA), were used. Finally, the best-developed model used different parameters to check the uncertainty obtained. For the test results, the new SDO-ANFIS model was able to obtain values of 0.9449 and 0.134 for the coefficient of determination (R2), and root mean square error (RMSE), which performed better than other models. Due to the different relationships between the parameters, different designed conditions were considered and developed based on the hybrid model and, finally, the number of longitudinal bars and diameter of lateral ties were obtained as the strongest and weakest parameters based on the developed model for this study.
Mineral ions (mainly calcium ions) from sugarcane juice can be trapped inside the heating tubes of evaporators and vacuum boiling pans, and calcium ions are precipitated. Consequently, sugar productivity and yield are negatively affected. Calcium ions can be removed from sugarcane juice using adsorption. This paper described the experimental condition for the batch adsorption performance of rosin-based macroporous cationic resins (RMCRs) for calcium ions. The kinetics of adsorption was defined by the pseudo-first-order model, and the isotherms of calcium ions followed the Freundlich isotherm model. The maximal monolayer adsorption capacity of calcium ions was 37.05 mg·g−1 at a resin dosage of 4 g·L−1, pH of 7.0, temperature of 75 °C, and contact time of 10 h. It appeared that the adsorption was spontaneous and endothermic based on the thermodynamic parameters. The removal rate of calcium ions in remelt syrup by RMCRs was 90.71%. Calcium ions were effectively removed from loaded RMCRs by 0.1 mol·L−1 of HCl, and the RMCRs could be recycled. The dynamic saturated adsorption capacity of RMCRs for calcium ions in remelt syrup was 37.90 mg·g−1. These results suggest that RMCRs are inexpensive and efficient adsorbents and have potential applications for removing calcium ions in remelt syrup.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.