Polyester with durable UV protection properties through using nano TiO2 and polysiloxane softener optimized by RSM

In this paper, durable ultraviolet (UV) protection properties were obtained on polyester fabric by the treatment with nano titanium dioxide (NTO_P) as UV absorber and polysiloxane (PS) as stabilizer. The cross-linkable PS softener was applied to enhance NTO_P durability creating soft handle. The UV protection (UP) properties of the samples were monitored by evaluating the color differences (ΔE ^?) on the stained methylene blue mounted under the treated samples during the UV irradiation. The response surface methodology was used to design the experiments and also central composite design was utilized for different variables based on Design of Expert software. Diverse UV irradiations were used including daylight for 24?h, UV-A (400?W) for 2?h, and UV-C (20?W) for 6?h. The appropriate model was utilized for each condition to create optimum polyester with UP properties. The results demonstrated that treated sample with 1.42% NTO_P and 3.61% PS had the lowest ΔE ^??=?0.13. Also, transmission spectra analyses (200–800?nm) of the treated polyester samples were in complete agreement and consequently desirable properties of UP were reported. The X-ray diffraction analyses of NTO_P and treated samples indicated the presence of anatase crystal structure in NTO_P which significantly absorbed irradiation with wavelengths of lower than 400?nm and inhibited significant discoloration of methylene blue.     

Derivation of an instrumentally based geometric appearance index for the automotive industry

In the present study, attempts were made to develop an index of geometric appearance capable of accurately predicting and quantifying the visually perceived geometric aspects of appearance of achromatic automotive finishes. To this end, three previously prepared individual scales for the three most significant geometric appearance attributes, namely specular gloss, distinctness of image (DOI), and orange peel for each of a series of metallic black, metallic gray, metallic silver, and solid white automotive finishes were utilized. The differences in each attribute were quantified visually by a panel of 16 observers, in terms of a lightness difference of an also previously prepared lightness scale. The innovative use of a common lightness scale showed that there is a surprisingly good correlation between the instrumentally measured specular gloss, DOI, and the LW parameter of the Wave scan instrument and the corresponding visually evaluated equivalents at the four investigated achromatic levels through minimizing observer errors and enhancing accuracy of the perceptibility procedure. These high accuracies made provisions for the implementation of the principle of additivity which led to the derivation of a geometric appearance index (GAI). However, before its derivation, one instrumentally measured parameter was remodeled exponentially to define an innovative parameter chosen to be named “percent absence of orange peel.” The proposed GAI illustrates high correlation with visual assessments and is herewith recommended as a stand-alone index for predicting the geometric appearance of automotive finishes. Furthermore, this index together with a chromatic appearance index could form the foundation for deriving a total appearance index for the automotive industry.     

Toughening of epoxy matrices with reduced single-walled carbon nanotubes

Reduced single-walled carbon nanotubes (r-SWCNT) are shown to react readily at room temperature under inert atmosphere conditions with epoxide moieties, such as those in triglycidyl p-amino phenol (TGAP), to produce a soft covalently bonded interface around the SWCNT. The soft interface is compatible with the SWCNT-free cross-linked cured matrix and acts as a toughener for the composite. Incorporation of 0.2 wt % r-SWCNT enhances the ultimate tensile strength, toughness and fracture toughness by 32, 118, and 40%, respectively, without change in modulus. A toughening rate (dK(IC)/dwt(f)) of 200 MPa m(0.5) is obtained. The toughening mechanism is elucidated through dynamic mechanical analyses, Raman spectroscopy and imaging, and stress-strain curve analyses. The method is scalable and applicable to epoxy resins and systems used commercially.     

Synthesis and application of Fe3O4@nanocellulose/TiCl as a nanofiller for high performance of quasisolid‐based dye‐sensitized solar cells

In this research, to optimize the surface of the photoanode, two different types of surface coatings were used and their effects on the photovoltaic parameters were investigated. Also, to compare the two different electrolytic systems based on liquid and gel‐state electrolyte, the novel magnetic core‐shell nanocellulose/titanium chloride (Fe₃O₄@)NCs/TiCl) nanocomposite was introduced into a polymeric system as a nanofiller to decrease the crystallinity of the polymer and enhance the diffusion of triiodide ions in quasisolid‐state dye‐sensitized solar cells (QS‐DSSCs). For this purpose, Fe₃O₄@)NCs/TiCl was synthesized by coprecipitation of Fe³⁺ and Fe²⁺ ions in the presence of nanocellulose and then used as magnetic support for bonding TiCl₄ to prepare QS‐DSSCs. Containing a 10.0 wt% magnetic nanocomposite, it displayed a higher apparent diffusion coefficient (D_app) for I₃^? ions (4.10 × 10^?6 cm²/s) than the gel polymeric electrolyte (GPE) did (1.35 × 10^?6 cm²/s). GPEs were characterized using various techniques including current density‐voltage curves, AC impedance measurements, and linear sweep voltammetry (LSV). The photovoltaic values for the short‐circuit current density (J_sc), open‐circuit voltage (V_OC), and fill factor (FF) and the energy conversion efficiency (η) of the novel Fe₃O₄@NCs/TiCl nanocomposite–based QS‐DSSCs were 14.90 mA cm^?2, 0.757 V, 64%, and 7.22%, respectively.     

Optimized Ensemble Algorithm for Predicting Metamaterial Antenna Parameters

Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance. Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas. Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas. Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today's technology. The accuracy of the forecast is mostly determined by the model used. The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the Metamaterial Antenna. Support Vector Machines (SVM), Random Forest, K-Neighbors Regressor, and Decision Tree Regressor were utilized as the basic models. The Adaptive Dynamic Polar Rose Guided Whale Optimization method, named AD-PRS-Guided WOA, was used to pick the optimal features from the datasets. The suggested model is compared to models based on five variables and to the average ensemble model. The findings indicate that the presented model using Random Forest results in a Root Mean Squared Error (RMSE) of (0.0102) for bandwidth and RMSE of (0.0891) for gain. This is superior to other models and can accurately predict antenna bandwidth and gain.     

Modified cotton gauze with nano-Ag decorated alginate microcapsules and chitosan loaded with PVP-I

This study was aimed at improving the conventional cotton gauze for achieving advanced wound dressing specifications. Firstly, microcapsules of alginate (Alg-MC) were formed and silver nanoparticles (AgNPs) were synthesized in situ inside (Method I: Ag/Alg-MC) or on (Method II: Ag@Alg-MC) Alg-MC. A solution of chitosan (CS) containing already prepared povidone-iodine (PVP-I) was loaded with Ag/Alg-MC or with Ag@Alg-MC. Finally, conventional cotton gauze substrate was impregnated with these two prepared dispersions and dried. Both samples showed antibacterial properties against gram-negative (Escherichia coli) and gram-positive bacterium (Staphylococcus aureus). Their water absorbency, water holding capacity, and vertical wicking increased by 55, 28, and 33%, respectively, in comparison with the control sample. Ag@Alg-MC showed burst release in comparison with Ag/Alg-MC. The conventional properties of cotton gauze were greatly improved by the introduced method and it was regarded as a proper candidate for application as an advanced wound dress.     

The modified dynamic‐based pushover analysis of steel moment resisting frames

A modified dynamic‐based pushover (MDP) analysis is proposed to properly consider the effects of higher modes and the nonlinear behavior of the structural systems. For this purpose, first, a dynamic‐based story force distribution (DSFD) load pattern is constructed using a linear dynamic analysis, either time history (THA) or response spectrum (RSA). Performing an initial pushover analysis with the DSFD load pattern, a nonlinearity modification factor (NMF) is calculated to modify the DSFD load pattern. The envelope of the peak responses of the structure obtained from 2 pushover analyses with the modified DSFD load pattern as well as the code suggested first mode load pattern are considered as the final demand parameters of the structural system. The efficiency of the proposed MDP procedure is investigated using the results of nonlinear THA besides some existing pushover procedures. For this purpose, the 2‐dimensional 9‐, 15‐, and 20‐story, SAC steel frame building models are considered for parametric studies using OpenSees program. The results indicate that the proposed MDP‐THA and MDP‐RSA methods can significantly improve the performance of the pushover analysis. Considering the accuracy and calculation efforts, the MDP‐RSA method is strongly suggested as an efficient and applicable method to estimate the nonlinear response demands of steel moment resisting frames.     

Studies on the leaching of an arsenic–uranium ore

Preliminary leaching studies were carried out to develop a suitable method for the recovery of uranium and the elimination of arsenic from a low grade carbonate/silicate ore containing 64 ppm U and 2446 ppm As, as well as some Cu, Pb, Ni and Zn. An examination of the mineralogy found mostly uranium(VI) minerals, such as uraninite, and various base metal sulfides and arsenates in veins and fissures. Roasting the ore at 500–800 °C to volatilize arsenic proved to be unsuitable. Therefore, the ground ore was subjected to direct leaching with sulfuric acid, sodium sulfide and ferric chloride at 80–90 °C with a liquid to solid ratio of 1:1. With sulfuric acid at a concentration of 180 kg/t ore, complete recovery of both uranium and arsenic was achieved giving undesirable arsenic in the leach liquor. The maximum recovery of uranium and arsenic by leaching with sodium sulfide was only 20% and 18%, respectively. However, 3 M ferric chloride leached approximately 92% U(VI) and precipitated arsenic as ferric arsenate. Therefore, maximum uranium can be extracted and arsenic eliminated as impurity by selective leaching with ferric chloride.     

Nodes placement in wireless mesh networks using optimization approaches: a survey

Neural Computing and Applications - Wireless mesh networks (WMNs) have grown substantially and instigated numerous deployments during the previous decade thanks to their simple implementation, easy...     

Synthesis of 2, 3-dihydroquinazolin-4(1H)-ones promoted by an efficient,inexpensive and reusable heterogeneous Lewis acid catalyst

Journal of Polymer Research - Hydrogels possessing advantages such as low friction coefficient and high-water absorption are analogous to the mucous layer of the epidermis of large marine...