Extraction of Lycopene from Tomato Paste by Ursodeoxycholic Acid Using the Selective Inclusion Complex Method

Lycopene, a precursor of β‐carotene with well‐known antioxidant activity and powerful health properties, can be found in many natural products such as tomato (Lycopersicon esculentum), watermelon, red pepper, and papaya. Many separation methods have been reported for extracting lycopene from its sources. The inclusion complex is an effective method for extraction and purification of organic chemicals. This procedure has 2 main components: host and guest molecules. In this study, lycopene (guest) was extracted from tomato paste by ursodeoxycholic acid, the inclusive agent (host). The molecular structure of the extracted lycopene was then confirmed by ¹HNMR and its purity was evaluated using high‐performance liquid chromatography and UV‐Vis spectrophotometry methods, in comparison with a standard product. The results indicated that the proposed separation method was very promising and could be used for the extraction and purification of lycopene from tomato paste.     

A validated co-simulation of grab and moist iron ore cargo: Replicating the cohesive and stress-history dependent behaviour of bulk solids

The traditional design approach of grabs and other bulk handling equipment consists of manufacturing and testing physical prototypes. A novel design approach is to use a co-simulation of MultiBody Dynamics (MBD) and Discrete Element Method (DEM), in which the virtual prototype of a new concept interacts with bulk solids. Therefore, this study develops and validates a full-scale co-simulation that models the grabbing process of cohesive and stress-history dependent iron ore. First, by executing in-situ measurements during the unloading of a vessel, grab-relevant bulk properties of the cargo, such as penetration resistance, are determined. Second, full-scale grabbing experiments are conducted in the cargo hold, which allows the process to be recorded in realistic operational conditions. Third, full-scale co-simulation is set up using the material model that has been calibrated based on an elasto-plastic adhesive contact model. Fourth, the co-simulation is validated by comparing its predictions to experimental data from various aspects, such as the force in cables and the torque in winches. The validated co-simulation proves that the stress-dependent behaviour of cohesive cargo as it interacts with the grab could be captured successfully. Valuable information such as a grab’s kinematics and dynamics, as well as the porosity distribution of collected bulk solids, can be extracted from the simulation, supporting engineers to enhance the design and operation of equipment.     

Cytotoxic activity of greener synthesis of cerium oxide nanoparticles using carrageenan towards a WEHI 164 cancer cell line

Carrageenan hydrogel as a “greener” and a vegetable-based stabilizing agent has the potential for many biosyntheses of different nanoparticles by sol-gel method. Herein, we describe for the first time an economic and eco-friendly preparation of cerium oxide nanoparticles (CeO₂-NPs) using carrageenan. When carrageenan hydrogel comes in contact with a cerium nitrate solution, cerium ions anchor themselves to the –SO₃^- groups into the carrageenan and after the gelation process, have fewer opportunities escaping from the polymeric network. The CeO₂-NPs were well-prepared and successfully characterized by PXRD, FTIR, FESEM, UV–Vis, and TGA-DTA. The calcined CeO₂-NPs showed strong UV absorption (λ_max = 328?nm) with the calculated band gap of 2.69?eV. The results obtained from FESEM images indicate that CeO₂-NPs obtained at 600?°C ranges from 18 to 60?nm and have a mean diameter of ~34?nm. The in vitro cytotoxicity study on WEHI 164 cell line has mentioned low toxic and non-toxic CeO₂-NPs in a range of concentrations (0.97–250?μg/ml), thus, we reckon that the greener synthesized CeO₂-NPs will have persistent utilization in various fields of medical applications.     

Advanced isoconversional cure kinetic analysis of epoxy/poly(furfuryl alcohol) bio‐resin system

Furfuryl alcohol as a biomass‐derived monomer was used for synthesizing poly(furfuryl alcohol). A diglycidyl ether of bisphenol A (DGEBA) epoxy resin along with 3% and 15% by weight of the poly(furfuryl alcohol) was cured using an aliphatic amine hardener. The cure kinetics of the DGEBA/poly(furfuryl alcohol)/amine systems were investigated by nonisothermal differential scanning calorimetry. The kinetic triplets [E_α, A_α, and f(α)] were computed by using an integral isoconversional method. Based on the E_α‐dependency results a single‐step autocatalytic model was suggested for the reactions mechanism, however, the A_α‐dependency and f(α) analysis did not confirm the suggested model. Detailed kinetics analysis revealed that the cure reaction mechanism of the DGEBA did not change due to the presence of the poly(furfuryl alcohol) in the degree of conversion range < 0.75, nevertheless, it dramatically changed in the degree of conversion range > 0.75 due to the presence of 15 wt % poly(furfuryl alcohol). © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45432.     

Clozapine recognition via molecularly imprinted polymers; bulk polymerization versus precipitation method

Two clozapine (CLZ) imprinted polymers were prepared by bulk and precipitation methods. Methacrylic acid and ethylene glycol dimethacrylate (EDMA) were used as functional and crosslinker monomers, respectively. The mean diameter and particle size distribution of the imprinted (P‐MIP) and nonimprinted (P‐NIP) particles obtained in precipitation method were examined. A conventional batch‐adsorption test was applied for characterization of CLZ–polymer interaction. Dissociation constant (K_D) and maximum binding sites (B_max) were calculated using Scatchard analysis. To evaluate the recognition properties of polymers, phenytoin (PTN) binding to each polymer was also studied and compared to CLZ. The imprinting factor (IF) and selectivity factor (α) were also determined for each polymer. Average diameter and polydispersity of P‐MIP were 925 nm and 0.17, respectively. The data for P‐NIP were 1.05 μm and 0.18. The K_D, IF, and α values calculated for P‐MIP were 0.45 μM, 3.26, and 17.43, respectively. The data for imprinted polymer, prepared by bulk polymerization (B‐MIP), were 14.5 μM, 1.95, and 3.67. These results demonstrated that precipitation polymerization is a more convenient, more effective, and more reproducible method than bulk polymerization for the synthesis of uniformly sized micron and submicron‐imprinted polymer particles. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Replicating cohesive and stress-history-dependent behavior of bulk solids: Feasibility and definiteness in DEM calibration procedure

This paper presents a multi-step DEM calibration procedure for cohesive solid materials, incorporating feasibility in finding a non-empty solution space and definiteness in capturing bulk responses independently of calibration targets. Our procedure follows four steps: (I) feasibility; (II) screening of DEM variables; (III) surrogate modeling-based optimization; and (IV) verification. Both types of input parameter, continuous (e.g. coefficient of static friction) and categorical (e.g. contact module), can be used in our calibration procedure. The cohesive and stress-history-dependent behavior of a moist iron ore sample is replicated using experimental data from four different laboratory tests, such as a ring shear test. This results in a high number of bulk responses (i.e. ≥ 4) as calibration targets in combination with a high number of significant DEM input variables (i.e. > 2) in the calibration procedure. Coefficient of static friction, surface energy, and particle shear modulus are found to be the most significant continuous variables for the simulated processes. The optimal DEM parameter set and its definiteness are verified using 20 different bulk response values. The multi-step optimization framework thus can be used to calibrate material models when both a high number of input variables (i.e. > 2) and a high number of calibration targets (i.e. ≥ 4) are involved.