Preparation and characterization of conductive polypyrrole/kaolinite composites

Conductive polypyrrole (PPy)/kaolinite clay composites were prepared by in situ chemical polymerization of pyrrole in the presence of kaolinite using FeCl₃ as oxidant. The PPy content and conductivity of the composites reached 32.8% and 8.3×10^?2 S/cm at HCl concentrations of 1.5 M and 0.5 M, respectively. The microhardness of the composites containing different amounts of PPy was higher than that of the PPy and kaolinite components. The highest microhardness observed was 30.17 kg/mm² for the composite containing 9.6% PPy. The electrical resistance of the composites was monitored during heating–cooling cycles over the range 5–120 °C. The change in resistance with temperature was more repeatable for the composite than for PPy. The composites were characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). The humidity-sensing properties were also examined.     

Innovative hydrogen release from sodium borohydride hydrolysis using biocatalyst-like Fe2O3 nanoparticles impregnated on Bacillus simplex bacteria

For the first time in this innovative study, microorganisms such as Bacillus simplex bacteria, mostly used in biological activity studies, are used as a bio-supporter agent of iron to release hydrogen from sodium borohydride hydrolysis at 25.0 ± 0.1 °C. The goal is to investigate thoroughly sodium borohydride hydrolysis catalyzed by Fe₂O₃ nanoparticles impregnated on microorganism such as Bacillus simplex (BS) bacteria (Fe₂O₃@BS NPs) known with strong antibacterial properties, which makes innovative them a candidate for hydrolysis reaction. This study was focused on the preparation, identification, and catalytic use of biocatalyst-like Fe₂O₃@BS NPs for hydrogen release from the sodium borohydride hydrolysis at 25.0 ± 0.1 °C. The characterization results made after and before hydrolysis reaction using by SEM/SEM-EDX, FT-IR, XRD, UV–vis, XPS, DLS, ELS Zeta potential, ESR, and TEM techniques reveal the formation of highly active, stable, durable, and long-lived biocatalysts-like Fe₂O₃@BS NPs.     

Thermal–economic–environmental analysis and multi-objective optimization of an internal-reforming solid oxide fuel cell–gas turbine hybrid system

In this article, an internal-reforming solid oxide fuel cell–gas turbine (IRSOFC–GT) hybrid system is modeled and analyzed from thermal (energy and exergy), economic, and environmental points of view. The model is validated using available data in the literature. Utilizing the genetic algorithm optimization technique, multi-objective optimization of modeled system is carried out and the optimal values of system design parameters are obtained. In the multi-objective optimization procedure, the exergy efficiency and the total cost rate of the system (including the capital and maintenance costs, operational cost (fuel cost), and social cost of air pollution for CO, NO_x, and CO₂) are considered as objective functions. A sensitivity analysis is also performed in order to study the effect of variations of the fuel unit cost on the Pareto optimal solutions and their corresponding design parameters. The optimization results indicate that the final optimum design chosen from the Pareto front results in exergy efficiency of 65.60% while it leads to total cost of 3.28 million US$ year⁻¹. It is also demonstrated that the payback time of the chosen design is 6.14 years.     

Blood supply chain network design considering blood group compatibility under uncertainty

This paper addresses the design of a blood supply chain (SC) network considering blood group compatibility. To this aim, a bi-objective mathematical programming model is developed which minimises the total cost as well as the maximum unsatisfied demand. Due to uncertain nature of some input parameters, two novel robust possibilistic programming models are proposed based on credibility measure. The data of a real case study are then used to illustrate the applicability and performance of the proposed models as well as validating the proposed robust possibilistic programming approach. The obtained results show the superiority of the developed models and significant cost savings compared to current existed blood SC network.     

Simple preparation and characterization of molecularly imprinted nylon 6 nanofibers for the extraction of bisphenol A from wastewater

Nylon 6 nanofibers incorporated with molecularly imprinted polymers (MIPs) were successfully fabricated by electrospinning with fiber diameters in the range 80–145 nm. Then, they were used as a new material for the extraction of selected bisphenol A (BPA) in water samples. Field emission scanning electron microscopy images revealed that the nanofibers had a smooth morphology with a good incorporation of MIPs. The Fourier transform infrared and energy-dispersive X-ray spectroscopy results also confirmed the formation of the MIPs in the nanofibers. Furthermore, Raman spectroscopy showed that the crystalline structure of the pristine nylon 6 nanofiber was a kind of α form, and the incorporation of MIPs led to a γ-form structure in the nanofibers; this proved the interactions between nylon 6 and the MIPs. Adsorption studies also confirmed that the adsorption efficiency of BPA onto the molecularly imprinted polymer nanofibers (MIP-NFs; 83.5%) was much greater than that onto nonimprinted polymer nanofibers (NIP-NFs; 36.8%). Also, the imprinting factor was 3.4; this strongly implied the successful formation of molecularly imprinted cavities on the MIP-NFs with a strong affinity to BPA. The maximum adsorption capacity of the MIP-NFs was 103.8 mg/g. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47112.     

Selective molecularly imprinted polymer nanofiber sorbent for the extraction of bisphenol A in a water sample

Novel molecularly imprinted polymer nanofibers (MIP‐NFs) were prepared for the adsorption of bisphenol A (BPA) in a water sample using the sol–gel process and the electrospinning technique. The effects of a number of synthesis parameters on the adsorption efficiency were investigated. The successful removal of BPA from MIP‐NFs was studied using UV–visible spectroscopy. The prepared MIP‐NFs were characterized by Fourier transform infrared, field emission SEM, TEM and energy dispersive X‐ray analysis. The results showed that the required molar ratio of 3‐aminopropyltriethoxysilane (APTES) to BPA was 15:1, which indicates a good performance in the rebinding test. Likewise, the molar ratio of APTES:acid:water was 1:2:9. The nylon 6 polymer solution, with a concentration of 12 wt%, showed a maximum adsorption capacity for BPA due to a decrease in the nanofiber diameter and an increase in the accessible sites. Furthermore, the maximum adsorption capacity of BPA was achieved at pH 7. Concerning the binding of BPA on MIP‐NFs, the experimental data matched well with the pseudo‐second‐order kinetics data and the Sips isotherm model. The saturated binding capacity for MIP‐NFs was predicted to be 115.1 mg g^?1, which was more than twice as high as that for non‐imprinted polymer nanofibers (46.82 mg g^?1). The results obtained in this study confirmed that the prepared MIP‐NFs showed considerable binding specificity for BPA in comparison with similar structural compounds such as phenol, naphthol and Naphthol AS, in aqueous solution. The binding capacity of MIP‐NFs remained almost constant after five cycles of reuse. The real sample analysis indicated that MIP‐NFs could be utilized as a useful sorbent material for the extraction of BPA from a water sample.     

Photo-electrochemistry of metallic titanium/mixed phase titanium oxide

In this study, the effect of potassium hydroxide concentration in anodization bath, anodization time, and calcination temperature on the photo-electrochemical behavior of metallic titanium/mixed phase titanium oxide is investigated. Further, the phase structure of a titanium oxide photocatalyst prepared on a titanium electrode through a high-voltage anodization method is examined. The study exploits photo-electrochemical, Fourier transform infrared spectroscopy attenuated total reflectance (FTIR–ATR), X-ray diffraction, and Raman spectroscopic methods to obtain better insights into the mechanism of mixed-phase titanium oxide formation. In this regard, the photo-electrochemical properties of the photocatalysts prepared in single excitation energy, violet light (410 nm), were investigated. The anodization time and the potassium hydroxide concentration in the anodization bath have significant effects on the photo-electrochemical properties of the photocatalysts. The experiments show that the effect of potassium hydroxide concentration is a function of the anodization potential applied, demonstrating different patterns as the anodization potential changes. Furthermore, FTIR-ATR, X-ray diffraction, and Raman spectroscopic studies reveal that the extended anodization times decrease the population of OH-containing groups, leading to lower photo-electrochemical performance. On the other hand, the formation of anatase phases becomes more favorable only in the extended anodization times before application of the calcination process. Additionally, the calcination temperature has a significant impact on the anatase to rutile ratio. Finally, increasing potassium hydroxide concentration leads to the formation of an amorphous titanium oxide layer. It can be concluded that the obtained information might have a significant impact on the preparation of titanium oxide and other metal oxide photocatalysts through the high voltage anodization process.     

Speaker independent feature selection for speech emotion recognition: A multi-task approach

Nowadays, automatic speech emotion recognition has numerous applications. One of the important steps of these systems is the feature selection step. Because it is not known which acoustic features of person’s speech are related to speech emotion, much effort has been made to introduce several acoustic features. However, since employing all of these features will lower the learning efficiency of classifiers, it is necessary to select some features. Moreover, when there are several speakers, choosing speaker-independent features is required. For this reason, the present paper attempts to select features which are not only related to the emotion of speech, but are also speaker-independent. For this purpose, the current study proposes a multi-task approach which selects the proper speaker-independent features for each pair of classes. The selected features are then given to the classifier. Finally, the outputs of the classifiers are appropriately combined to achieve an output of a multi-class problem. Simulation results reveal that the proposed approach outperforms other methods and offers higher efficiency in terms of detection accuracy and runtime.