High-Performance Nanocatalyst for Adsorptive and Photo-Assisted Fenton-Like Degradation of Phenol: Modeling Using Artificial Neural Networks

High-performance activated carbon-zinc oxide (Ac–ZnO) nanocatalyst was fabricated via the microwave-assisted technique. Ac–ZnO was characterized and the results indicated that Ac–ZnO is stable, had a band gap of 3.26?eV and a surface area of 603.5?m²g^?1, and exhibited excellent adsorptive and degrading potentials. About 93% phenol was adsorbed within 550?min of reaction by Ac–ZnO. Impressively, a complete degradation was achieved in 90?min via a photo-Fenton/Ac–ZnO system under optimum conditions. An artificial neural network (ANN) model was developed and applied to study the relative significance of input variables affecting the degradation of phenol in a photo-Fenton process. The ANN results indicate that increases in both H₂O₂ and Ac–ZnO dosage enhanced the rate of phenol degradation. The highest rate constant at the optimum conditions was 0.093?min^?1 and it was found to be consistent with the ANN-predicted rate constant (0.095?min^?1).     

Ethanol-Modified Supercritical Carbon Dioxide Extraction of the Bioactive Lipid Components of <Emphasis Type="Italic">Camelina sativa</Emphasis> Seed

Camelina sativa seed is an underutilized oil source that attracts a growing interest, but it requires more research on its composition and processing. Its high omega‐3 content and growing demand for clean food processing technologies make conventional oil extraction less attractive. In this study, the effect of extraction methods on the bioactive lipid composition of the camelina seed lipid was investigated, and its bioactive lipid composition was modified at the extraction stage using ethanol‐modified supercritical carbon dioxide (SC‐CO₂). Ethanol‐modified SC‐CO₂ extractions were carried out at varying temperatures (50 and 70 °C), pressures (35 and 45 MPa), and ethanol concentrations (0–10%, w/w), and were compared to SC‐CO₂, cold press, and hexane extraction. The highest total lipid yield (37.6%) was at 45 MPa/70 °C/10% (w/w) ethanol. Phospholipids and phenolic content increased significantly with ethanol‐modified SC‐CO₂ (p < 0.05). SC‐CO₂ with 10% (w/w) ethanol concentration selectively increased phosphatidylcholine (PC) content. Apparent solubility of camelina seed lipids in SC‐CO₂, determined using the Chrastil model, ranged from 0.0065 kg oil/kg CO₂ (35 MPa/50 °C) to 0.0133 kg oil/kg CO₂ (45 MPa/70 °C). Ethanol‐modified SC‐CO₂ extraction allowed modification of the lipid composition that was not possible with the conventional extraction methods. This is a promising green method for extraction and fractionation of camelina seed lipids to separate and enrich its bioactives.     

Effect of the Addition of a Cocoa Butter–Like Fat Enzymatically Produced from Olive Pomace Oil on the Oxidative Stability of Cocoa Butter

ABSTRACT:  A cocoa butter (CB)–like fat was produced in a packed bed enzyme reactor using sn -1,3 specific lipase, and its blends with CB were prepared at different ratios (CB: CB-like fat; 100: 0, 90: 10, 80: 20, 70: 30, 60: 40, 50: 50, 0: 100). The oxidation kinetics of CB: CB-like fat blends was studied by differential scanning calorimeter (DSC). Samples were heated in DSC at different temperatures (130, 140, 150, 160 °C) under 100 mL/min oxygen. From DSC exotherms, oxidation induction times (OIT) were determined and used for the assessment of the oxidative stabilities of the blends. Oxidation kinetics parameters (activation energy, E_a ; preexponential factor, Z ; and oxidation rate constant, k ) were calculated. In general, it has been observed that above 110 °C increasing the ratio of CB-like fat in the blend increased the k value with increasing temperature. It has been observed that for all blends the increase in k value with temperature was significant ( P < 0.05). Increasing CB-like fat ratio in the blend decreased the content of major TAGs (1,3-dipalmitoyl-2-oleoyl-glycerol [POP]; 1[3]-palmitoyl-3[1]stearoyl-2-oleoyl-glycerol [POS]; 1,3-distearoyl-2-oleoyl-glycerol [SOS]), and decreased the oxidative stability of the blends.     

Macroscopic assembly of indefinitely long and parallel nanowires into large area photodetection circuitry

Integration of nanowires into functional devices with high yields and good reliability turned out to be a lot more challenging and proved to be a critical issue obstructing the wide application of nanowire-based devices and exploitation of their technical promises. Here we demonstrate a relatively easy macrofabrication of a nanowire-based imaging circuitry using a recently developed nanofabrication technique. Extremely long and polymer encapsulated semiconducting nanowire arrays, mass-produced using the iterative thermal drawing, facilitate the integration process; we manually aligned the fibers containing selenium nanowires over a lithographically defined circuitry. Controlled etching of the encapsulating polymer revealed a monolayer of nanowires aligned over an area of 1 cm(2) containing a 10 × 10 pixel array. Each light-sensitive pixel is formed by the contacting hundreds of parallel photoconductive nanowires between two electrodes. Using the pixel array, alphabetic characters were identified by the circuitry to demonstrate its imaging capacity. This new approach makes it possible to devise extremely large nanowire devices on planar, flexible, or curved substrates with diverse functionalities such as thermal sensors, phase change memory, and artificial skin.     

Fabrication and electrochemical characteristics of electrospun LiFePO4/carbon composite fibers for lithium-ion batteries

LiFePO₄/C composite fibers were synthesized by using a combination of electrospinning and sol-gel techniques. Polyacrylonitrile (PAN) was used as an electrospinning media and a carbon source. LiFePO₄ precursor materials and PAN were dissolved in N,N-dimethylformamide separately and they were mixed before electrospinning. LiFePO₄ precursor/PAN fibers were heat treated, during which LiFePO₄ precursor transformed to energy-storage LiFePO₄ material and PAN was converted to carbon. The surface morphology and microstructure of the obtained LiFePO₄/C composite fibers were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and elemental dispersive spectroscopy (EDS). XRD measurements were also carried out in order to determine the structure of LiFePO₄/C composite fibers. Electrochemical performance of LiFePO₄/carbon composite fibers was evaluated in coin-type cells. Carbon content and heat treatment conditions (such as stabilization temperature, calcination/carbonization temperature, calcination/carbonization time, etc.) were optimized in terms of electrochemical performance.     

Modeling of solar radiation using remote sensing and artificial neural network in Turkey

Artificial neural networks (ANNs) were used to estimate solar radiation in Turkey (26–45°E, 36–42°N) using geographical and satellite-estimated data. In order to train the Generalized regression neural network (GRNN) geographical and satellite-estimated data for the period from January 2002 to December 2002 from 19 stations spread over Turkey were used in training (ten stations) and testing (nine stations) data. Latitude, longitude, altitude, surface emissivity for ?_4, surface emissivity for ?_5, and land surface temperature are used in the input layer of the network. Solar radiation is the output. Root Mean Square Error (RMSE) and correlation coefficient (R²) between the estimated and measured values for monthly mean daily sum with ANN values have been found as 0.1630 MJ/m² and 95.34% (training stations), 0.3200 MJ/m² and 93.41% (testing stations), respectively. Since these results are good enough it was concluded that the developed GRNN tool can be used to predict the solar radiation in Turkey.     

Antimicrobial effect of PEG–PLA on food-spoilage microorganisms

Food Science and Biotechnology - Polyethylene glycol (PEG) and polyethylene glycol–polylactic acid (PEG–PLA) have an organic structure and no negative effect on human health. The...     

Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness

This paper focuses on cell loading and family scheduling in a cellular manufacturing environment. The performance measure is minimising the maximum tardiness of jobs. What separates this study from others is the presence of individual due dates for every job in a family and also allowing family splitting among cells. Three methods are examined in order to solve this problem, namely mathematical modelling, genetic algorithms (GA) and heuristics. The results showed that GA is capable of finding the optimal solution with varying frequency of 60–100% and it is efficient as compared to the mathematical modelling especially for larger problems in terms of execution times. The heuristics, on the other hand, were easy to implement but they could not find the optimal solution. The results of experimentation also showed that family splitting was observed in all multi-cell optimal solutions and therefore it can be concluded that family splitting is a good strategy for the problem considered in this paper.     

High‐performance liquid chromatography of some natural dyes: analysis of plant extracts and dyed textiles

In this study, wool fibre samples were mordanted by means of 25% alum mordant solution. The mordanted wool samples were dyed in 50%Reseda luteola L. (weld), 20%Rhamnus petiolaris Boiss (buckthorn) and 50%Datisca cannabina L. (bastard hemp) dyebaths. A reverse‐phase high‐performance liquid chromatography with diode‐array detection method was utilised for the identification of dyes in the dyed wool samples and the plant extracts. The extraction of dyes was carried out with a hydrogen chloride/methanol/water (2:1:1; v/v/v) mixture.