Studies on marigold seed oil and seed meal

The fixed oil (26%) of the seeds of Marigold (Calendula officinalis) locally known as “Gul-e-Ashrafi” growing around the laboratories, was studied for its physico-chemical properties. Fatty acid composition of the seed oil as determined by gaschromatography and UV-spectroscopy showed the presence of lauric (3.90%), myristic (3.58%), palmitic (14.96%), stearic (10.13%), palmito-oleic (4.55%), oleic (16.26%), linoleic (39.45%) and linolenic (7.15%) acids. In the seed oil, conjugated acid is present to the extent of 4.5% whereas the percentage of non-conjugated acid (linolenic acid) is only 2.65%. The residual meal after the extraction of oil was also studied for its proteins (18%) and amino acids composition.     

Physical,mechanical, and in vitro biological analysis of bioactive fibers-based dental composite

This study aimed to synthesize experimental composites reinforced with various concentrations (0, 40, 50, and 60 wt%) of nano-hydroxyapatite grafted glass fibers. The release of monomers, residual monomers, and in-vitro bioactivity of composite groups were evaluated after 1, 7, and 28 days. Compressive strength/ modulus, cell viability (by direct and indirect method), and bacterial adhesion were evaluated. The results showed that bis-GMA was released from all samples. TEGDMA released from 50 and 60 wt% samples on day 1 and UDMA showed negligible release. Compressive strength values of 40 wt% sample were higher than other experimental groups. New apatite layer was formed, whereby both direct and indirect methods demonstrated cell viability. The numbers of active colonies grown were least for 60 wt% sample while their number increased over time. The nano-hydroxyapatite/glass fibers have potential to be used as filler in dental composites and experimental composites were found to be biocompatible and comparable with commercial material.     

Application of Strong Porous Polymer Sheets for Superior Oil Spill Recovery

The usage of natural and synthetic sorbents in order to control oil spills is gaining increasing attention due to environmental concerns. In particular, polyolefins including polypropylene and polyethylene are the most commonly used oil sorbent materials because of their low cost but suffer from low oil absorption capacity. Attempts at trying to increase the surface‐to‐thickness ratio for improving uptake capacity makes them vulnerable to breakage and impractical for most oil spill applications. Novel super oil sorbent polymer sheets consisting of porous ultrahigh‐molecular‐weight polyethylene have been prepared. The presented sorbent exhibits extremely high uptake and retention capacities along with a mechanically strong structure. The combination of these factors as well as the cost effectiveness of the material used makes these sheets viable candidates for widespread production and utilization.     

Study of silver electrodeposition in deep eutectic solvents using atomic force microscopy

The electrodeposition of metals in ionic liquids and deep eutectic solvents leads to deposits with significantly different morphologies to those seen with aqueous solutions. The classical methods of fitting amperometric data to nucleation and growth mechanisms do not fit the data well in ionic systems and tend to focus on the short time-scale aspects of nucleation. In the current study, ex-situ AFM was used to model crystallite sizes and distributions by digitising and modelling the images. The deposition of silver from a deep eutectic solvent was chosen as it has been studied by several groups with a variety of techniques. The crystallite size data obtained from AFM and chronoamperometry for long time-scale deposition studies are compared and it is shown that the trends are similar, but there is a discrepancy in the nuclear number density of approximately an order of magnitude. The nuclear number density was found to be consistent with aqueous nucleation studies once differences in concentration and mass transport were accounted for.     

Dispersion and vulcanization characteristics of nitrile rubber reinforced with N,N-dimethylacetamide/lithium chloride treated silica

N,N-Dimethylacetamide/lithium chloride (DMAc/LiCl) treated silica is used as a reinforcing filler in nitrile rubber (NBR). Effect of the treatment on aggregate morphology and dispersion of silica in the matrix is investigated using XPS, SEM, and AFM. Binding energy levels of O1s and Si2p electrons in DMAc/LiCl treated silica have shifted significantly from 532.49 to 530.98 eV and 103.19 to 101.33 eV respectively. SEM observations have revealed a reduction in the agglomerate size of silica-a desirable feature for realizing better processing properties of silica filled rubber compounds. Data from AFM observations have also shown better dispersion of DMAc/LiCl treated silica. Mooney viscosity of masterbatches, measured at 100°C over a period of 7 days, has not exhibited any storage hardening which is an indication of easier processability. At 125°C, Mooney data exhibited a reduction in scorch time as a function of DMAc/LiCl concentration. However, MDR data at 160°C have not shown much changes in the scorch time while NBR with high nitrile content exhibited longer cure times. Higher crosslink density of vulcanizates indicate that DMAc/LiCl treatment of silica could effectively reduce filler-filler interactions and networking in silica filled rubber compounds thereby enabling mixing and processing operations energy efficient.     

Absorption and emission spectral studies of Sm-doped lead tungstate tellurite glasses

The present work reports the effect of concentration on photoluminescence properties of Sm³⁺ ions doped lead tungstate tellurite (LTTSm) glasses by using the absorption, emission and decay measurements. The Judd-Ofelt theory has been used to evaluate the three Judd-Ofelt intensity parameters (Ω_2,4,6) and calculated oscillator strengths (f_c). LTTSm glasses exhibited intense reddish-orange emission when excited with 477 nm wavelength. Concentration quenching has been noticed beyond 1.0 mol% of Sm³⁺ ion concentration. The decay curves of ⁴G_5/2 level exhibited single exponential behavior for all the concentrations and the measured lifetimes are found to depend strongly on Sm³⁺ concentration. From the emission characteristic parameters of ⁴G_5/2 level, it is concluded that the LTTSm glasses could be useful for photonic devices like visible lasers, fluorescent display devices and optical amplifiers.     

New multicriteria group decision support systems for small hydropower plant locations selection based on intuitionistic cubic fuzzy aggregation information

There has been a quick development in construction activities during the last couple of decades attributable to a general improvement in all features of humankind. Because of innovative progressions and regularly expanding human progress, there is a diligent requirement of power. Close by the ordinary energy sources, renewable energy sources have likewise lead significantly to the rising power requirement. All over the world in the past, a number of small hydropower plants (SHPPs) have been developed, as a renewable energy source. Generally, these SHPPs are being manufactured and worked by the private designers consenting to the administration rules. So as to help a designer in choosing the most productive and doable SHPP for development and consequent activity, the concept of the intuitionistic cubic fuzzy set (ICFS) theory is established and a few important operations for ICFSs are characterized, and also a strategy dependent on intuitionistic cubic fuzzy Hamacher hybrid averaging (ICFHHA) operator, intuitionistic cubic fuzzy Hamacher order weighted averaging (ICFHOWA) operator, and intuitionistic cubic fuzzy Hamacher weighted averaging (ICFHWA) operators is utilized in the present paper. The financial criteria and technobusiness, as assumed for examining the practicality of the candidate SHPPs, are presented qualitatively utilizing intuitionistic cubic fuzzy numbers (ICFNs). Further study their fundamental properties and the relationship among these aggregation operators. Developed group decision-making (DM) algorithm under intuitionistic cubic fuzzy (ICF) environment. An interpretative case for the analysis of SHPP for construction is given to demonstrate the feasibility and practicality of the mentioned new techniques. Further validate its effectiveness and benefits via a comparative analysis with pre-existing aggregation operators, and the outcomes demonstrate that the proposed SHPP determination model has some special favorable circumstances, which is progressively practical and adaptable for SHPP choice under a complex and uncertain environment.     

Cubic fuzzy Einstein aggregation operators and its application to decision-making

In this paper, we define some Einstein operations on cubic fuzzy set (CFS) and develop three arithmetic averaging operators, which are cubic fuzzy Einstein weighted averaging (CFEWA) operator, cubic fuzzy Einstein ordered weighted averaging (CFEOWA) operator and cubic fuzzy Einstein hybrid weighted averaging (CFEHWA) operator, for aggregating cubic fuzzy data. The CFEHWA operator generalises both the CFEWA and CFEOWA operators. Furthermore, we develop various properties of these operators and derive the relationship between the proposed operators and the exiting aggregation operators. We apply CFEHWA operator to multiple attribute decision-making with cubic fuzzy data. Finally, a numerical example is constructed to demonstrate the established approach.     

Development of a hybrid PSO–ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass

In this paper, two artificial intelligent systems, the artificial neural network (ANN) and particle swarm optimization (PSO), were combined to form a hybrid PSO–ANN model that was used to improve estimates of glucose and xylose yields from the microwave–acid pretreatment and enzymatic hydrolysis of lignocellulosic biomass based on pretreatment parameters. ANN is a powerful tool capable of determining the relationship between the desired input and output data while PSO was used as a robust population-based search algorithm to optimize the performance of the ANN model. Specifically, it was used to determine the optimum number of neurons in the hidden layer and the best value of the learning rate of the ANN model. The optimization method includes minimizing the fitness function mean absolute error that was found to be 0.0176. The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. After constructing the hybrid PSO–ANN model, the performance of the intelligent system was examined by determining the regression coefficient (R ²) for estimating the experimental values of glucose and xylose and compared to the results from a response surface methodology (RSM) model. The results of R ² of the hybrid PSO–ANN model for glucose and xylose were 0.9939 and 0.9479, respectively, while the RSM model results for the same sugars were 0.8901 and 0.8439. This analysis reveals that the hybrid PSO–ANN model offers a higher degree of accuracy in comparison with the more commonly used RSM model.