Simultaneous determination of antimony and boron in beverage and dairy products by flame atomic absorption spectrometry after separation and pre-concentration by cloud-point extraction

A new cloud-point extraction (CPE) method was developed for the pre-concentration and simultaneous determination of Sb(III) and B(III) by flame atomic absorption spectrometry (FAAS). The method was based on complexation of Sb(III) and B(III) with azomethine-H in the presence of cetylpyridinium chloride (CPC) as a signal-enhancing agent, and then extraction into the micellar phase of Triton X-114. Under optimised conditions, linear calibration was obtained for Sb(III) and B(III) in the concentration ranges of 0.5–180 and 2.5–600 μg l^?1 with LODs of 0.15 and 0.75 μg l^?1, respectively. Relative standard deviations (RSDs) (25 and 100 μg l^?1 of Sb(III) and B(III), n = 6) were in a range of 2.1–3.8% and 1.9–2.3%, respectively. Recoveries of spiked samples of Sb(III) and B(III) were in the range of 98–103% and 99–102%, respectively. Measured values for Sb and B in three standard reference materials were within the 95% confidence limit of the certified values. Also, the method was used for the speciation of inorganic antimony. Sb(III), Sb(V) and total Sb were measured in the presence of excess boron before and after pre-reduction with an acidic mixture of KI-ascorbic acid. The method was successfully applied to the simultaneous determination of total Sb and B in selected beverage and dairy products.     

Electrochemical Performance of Na3V2(PO4)2F3 Electrode Material in a Symmetric Cell

A NASICON-based Na₃V₂(PO₄)₂F₃ (NVPF) cathode material is reported herein as a potential symmetric cell electrode material. The symmetric cell was active from 0 to 3.5 V and showed a capacity of 85 mAh/g at 0.1 C. With cycling, the NVPF symmetric cell showed a very long and stable cycle life, having a capacity retention of 61% after 1000 cycles at 1 C. The diffusion coefficient calculated from cyclic voltammetry (CV) and the galvanostatic intermittent titration technique (GITT) was found to be ~10⁻⁹–10⁻¹¹, suggesting a smooth diffusion of Na⁺ in the NVPF symmetric cell. The electrochemical impedance spectroscopy (EIS) carried out during cycling showed increases in bulk resistance, solid electrolyte interphase (SEI) resistance, and charge transfer resistance with the number of cycles, explaining the origin of capacity fade in the NVPF symmetric cell. Finally, the postmortem analysis of the symmetric cell after 1000 cycles at a 1 C rate indicated that the intercalation/de-intercalation of sodium into/from the host structure occurred without any major structural destabilization in both the cathode and anode. However, there was slight distortion in the cathode structure observed, which resulted in capacity loss of the symmetric cell. The promising electrochemical performance of NVPF in the symmetric cell makes it attractive for developing long-life and cost-effective batteries.     

Cost optimization of submersible motors using a genetic algorithm and a finite element method

This paper presents an optimal design method to optimize cost of three-phase submersible motors. The optimally designed motor is compared with an industrial motor having the same ratings. The motor design procedure consists of a system of non-linear equations, which imposes induction motor characteristics, motor performance, magnetic stresses, and thermal limits. The genetic algorithm (GA) is used for cost optimization, and a software algorithm has been developed. As a result of the realized optimization, besides the improvements on the motor cost, motor torque improvements have also been acquired. The 2-D finite element method (FEM) is then used to confirm the validity of the optimal design. Computer simulation results are given to show the effectiveness of the proposed design process that can achieve a good prediction of the motor performance. Through the studies accomplished, it has been observed that submersible induction motors’ torques and efficiencies improve, their length reduces, and hence some material savings are obtained.     

Exergoeconomic evaluation on the optimum heating circuit system of Simav geothermal district heating system

Simav is one of the most important 15 geothermal areas in Turkey. It has several geothermal resources with the mass flow rate ranging from 35 to 72 kg/s and temperature from 88 to 148 °C. Hence, these geothermal resources are available to use for several purposes, such as electricity generation, district heating, greenhouse heating, and balneological purposes. In Simav, the 5000 residences are heated by a district heating system in which these geothermal resources are used. Beside this, a greenhouse area of 225,000 m² is also heated by geothermal. In this study, the working conditions of the Simav geothermal district heating system have been optimized. In this paper, the main characteristics of the system have been presented and the impact of the parameters of heating circuit on the system are investigated by the means of energy, exergy, and life cycle cost (LCC) concepts. As a result, the optimum heating circuit has been determined as 60/49 °C.     

Effect of carbon black silanization on isothermal curing kinetics of epoxy nanocomposites

The present study was carried out to determine the effect of carbon black (CB) nanofiller silanization and loading on isothermal curing kinetics of epoxy nanocomposites. The epoxy resin specimens incorporated with 2, 4, and 8 wt% pristine CB and silanized CB were cured at isothermal temperatures of 43, 60, and 104°C. Differential scanning calorimetry was used to characterize the curing kinetics, Fourier transform infrared spectroscopy was employed to confirm silanization of CB nanofillers, and scanning electron microscopy was utilized to study the morphology of nanocomposite specimens. It was also observed that the silanization did not change the curing kinetics of CB nanocomposites significantly as compared to the neat epoxy resin. However, the curing reactions of the pristine CB nanocomposites were slower than the neat epoxy resin marked by an average 10 and 4% decrease in the final degree of cure for the nanocomposite specimens cured at 43 and 60°C, respectively. The morphological studies revealed that the silanized CB particles exhibited a more stable and homogeneous dispersion in the epoxy resin than the pristine CB particles. Potential applications for the fabricated nanocomposites include sensors, actuators, and conductive coatings for electrostatic dissipation control in plastic parts.     

Modeling preferential CO oxidation over promoted Au/Al2O3 catalysts using decision trees and modular neural networks

In this work, the experimental data for CO oxidation over promoted Au/Al₂O₃ catalysts were analyzed using decision trees and modular neural networks. The full dataset was first classified by decision trees to identify and select the conditions for high catalytic activity; then the reduced dataset containing only the promising data were modeled using neural networks, at which the compositional and operating variables were processed in a modular manner to be able to model their effects together but treat them separately. It was found that operating variables were more influential on catalytic activity than catalyst compositional variables. The temperature was found to be the most significant operating variable while Mg and Mn were the best performing promoters. It was also concluded that decision trees and neural networks can complement each other to extract easily comprehensible knowledge, and they can be used for similar catalytic systems for the same purpose.     

Simple and fast spectrophotometric determination of low levels of thiabendazole residues in fruit and vegetables after pre-concentration with ionic liquid phase microextraction

There is a great importance of monitoring thiabendazole (TBZ) residues in fruits and vegetables to ensure food safety. Therefore, a new ionic liquid (IL) phase microextraction method using IL, 1-butyl-3-methylimidazoliumhexafluorophosphate [C₄mim][PF₆], as extracting solvent is proposed for simple and fast determination of low levels of TBZ in fruits and vegetables by spectrophotometry. The method is based on selective complex formation of TBZ with Cu(II) ions in presence of PF₆^– as counter ion at pH 5.5, and then microextraction of the complex into the fine micro-drops of IL phase. After optimisation of variables affecting microextraction efficiency, the analytical parameters of the method were determined by calibration curves. The method exhibits a linear relationship (0.3–280 μg L^?1), low detection limit (0.1 μg L^?1), good intra- and inter-day precision (2.4–4.5% as RSD_r%, 2.1–5.6% as RSD_R%), good recovery (≥95.1–98.2%) and high sensitivity enhancement factor (150) by solvent-based calibration curve. It allows a detection limit of 0.24 μg L^?1 and a range of 0.8–250 μg L^?1 by the matrix-matched calibration curve. After validation, the method was successfully applied to the determination of TBZ residues with method quantification limits in fruit and vegetables of 2.0 and 2.5 µg kg^?1 with and without adding polyvinylpyrrolidone (PVP-15) solution. Recoveries range from 85.5% to 98.2% after spiking (10, 50 and 100 µg kg^?1, n: 3).     

Investigation of the inhibition effect of 5-((E)-4-phenylbuta-1,3-dienylideneamino)-1,3,4-thiadiazole-2-thiol Schiff base on mild steel corrosion in hydrochloric acid

The inhibition effect of 5-((E)-4-phenylbuta-1,3-dienylideneamino)-1,3,4-thiadiazole-2-thiol (PDTT) Schiff base on mild steel corrosion in 0.5 M HCl was studied for both short and long immersion time. For this purpose, potentiodynamic polarization, electrochemical impedance spectroscopy, linear polarization resistance, hydrogen gas evolution, the change of open circuit potential as a function of immersion time, SEM and AFM techniques were utilized. The PDTT Schiff base has shown remarkable inhibition on the corrosion of mild steel in 0.5 M HCl solution. The high inhibition efficiency was attributed to the blocking of active sites by adsorption of inhibitor molecules on the steel surface.     

Mining truck scheduling with stochastic maintenance cost

Open pit mining operations utilize large scale and expensive equipment. For the mines implementing shovel and truck operation system, trucks constitute a large portion of these equipment and are used for hauling the mined materials. In order to have sustainable and viable operation, these equipment need to be utilized efficiently with minimum operating cost. Maintenance cost is a significant proportion of the overall operating costs. The maintenance cost of a truck changes non-linearly depending on the type, age and truck types. A new approach based on stochastic integer programming (SIP) techniques is used for annually scheduling a fixed fleet of mining trucks in a given operation, over the life of mine (multi-year time horizon) to minimize maintenance cost. The maintenance cost data in mining usually has uncertainty caused from the variability of the operational conditions at mines. To estimate the cost, usually historic data from different operations for new mines, and/or the historic data at the operating mines are used. However, maintenance cost varies depending on road conditions, age of equipment and many other local conditions at an operation. Traditional models aim to estimate the maintenance cost as a deterministic single value and financial evaluations are based on the estimated value. However, it does not provide a confidence on the estimate. The proposed model in this study assumes the truck maintenance cost is a stochastic parameter due to the significant level of uncertainty in the data and schedules the available fleet to meet the annual production targets. The scheduling has been performed by applying both the proposed stochastic and deterministic approaches. The approach provides a distribution for the maintenance cost of the optimized equipment schedule minimizing the cost.     

World oil prices,precious metal prices and macroeconomy in Turkey

We examine the long- and short-run transmissions of information between the world oil price, Turkish interest rate, Turkish lira–US dollar exchange rate, and domestic spot gold and silver price. We find that the world oil price has no predictive power of the precious metal prices, the interest rate or the exchange rate market in Turkey. The results also show that the Turkish spot precious metals, exchange rate and bond markets do not also provide information that would help improve the forecasts of world oil prices in the long run. The findings suggest that domestic gold is also considered a safe haven in Turkey during devaluation of the Turkish lira, as it is globally. It is interesting to note that there does not seem to be any significant influence of developments in the world oil markets on Turkish markets in the short run either. However, transitory positive initial impacts of innovations in oil prices on gold and silver markets are observed. The short-run price transmissions between the world oil market and the Turkish precious metal markets have implications for policy makers in emerging markets and both local and global investors in the precious metals market and the oil market.