Adaptive investigation of the optical properties of polymer fibers from mixing noisy phase shifting microinterferograms using deep learning algorithms

In this article, an adaptive denoising method is suggested to accurate investigate the optical and structural features of polymeric fibers from noisy phase shifting microinterferograms. The mixed class of noise that may produce in the phase-shifting interferometric techniques is established. To our knowledge, this is an early study considered the mixing noises that may occur in microinterferograms. The suggested method utilized the convolution neural networks to detect the noise class and then denoising, it according to its class. Four convolution neural networks (Googlenet, VGG-19, Alexnet, and Alexnet–SVM) are refined to perform the automatic classification process for the noise class in the established data set. The network with the highest validation and testing accuracy of these networks is considered to apply the suggested method on realistic noisy microinterferograms for polymeric fibers, polypropylene and antimicrobial polyethylene terephthalate)/titanium dioxide, recoded using interference microscope. Also, the suggested method is applied on noisy microinterferograms include crazing and nanocomposite material. The demodulated phase maps and the three-dimensional birefringence profiles are calculated for tested fibers according to the suggested method. The obtained results are compared with the published data for these fibers and found to be in good agreements.     

ZnO·2.7Al2O3 nanocomposite with high optical transparency

Here we report a transparent dual-phase ZnO·2.7Al₂O₃ ceramic. The composite is pore-free and consists of thin nanosheets with a spinel phase and a hexagonal phase, while the two phases match closely in both lattice and refractive index. Such features result in excellent optical transmittance (maximum value >80% in the visible spectrum) at comparable phase volume. This work may provide a new thought for the rational structural design of optical nanocomposites.     

Micromembrane absorber with deep-permeation nanostructure assembled by flowing synthesis

A micromembrane adsorber with deep-permeation nanostructure (DPNS) has been successfully fabricated by flowing synthesis. The nanoparticles are in-situ assembled in membrane pores and immobilized in each membrane pore along the direction of membrane thickness. The nanoparticles with a lower size and thinner size distribution can be achieved owing to the confined space effect of the membrane pores. As a concept-of-proof, the nano ZIF-8 and ZIF-67 are fabricated in porous membrane pores for methyl orange (MO) and rhodamine B (RhB) adsorption. The adsorption rate is increased significantly owing to the enhanced contact and mass transfer in the confined space. The adsorption capacity for the RhB is also increased, since the size of the nanoparticles assembled in membrane pores is smaller with more active sites exposed. This micromembrane adsorber with DPNS has good reusability and can provide a promising prospect for industrial application.     

Enhanced dielectric and piezoelectric properties in potassium sodium niobate/polyvinylidene fluoride composites using nano-silicon carbide as an additive

Piezoelectric materials are an indispensable part of modern life. Yet the existing environmental issues with conventional lead-based piezoelectrics has motivated scientist to develop novel substitutes including lead-free piezoelectric polymer composites. Following this path, the present research has focused on the fabrication of ternary composites of Polyvinylidene fluoride (PVDF)/Potassium Sodium Niobate (KNN)/nano-Silicon carbide (SiC) via hot compression molding and studying the effect of additives on the PVDF structure and the electrical properties of the composite. The obtained scanning electron micrographs and density measurements showed that the fabrication method provided dense samples. The activated polarization phenomena in the prepared samples enhanced dielectric permittivity and dielectric loss at a constant frequency with increasing KNN and SiC contents. Besides the expected dipole polarization, the presence of interfaces in the composites gave rise to the Maxwell–Wagner–Sillars effect and its corresponding polarization phenomenon. The semiconductive nature of SiC also promoted space charge polarization. However, these properties were frequency-dependent because the first two polarization mechanisms are deactivated at high frequencies. XRD patterns showed that SiC addition can alter the primary crystalline structure of PVDF and promote β-phase formation in the poled samples. Piezoelectric measurements confirmed the significant role of SiC addition to PVDF-KNN composites. The most significant increase in the piezoelectric properties was observed in PVDF-60KNN-1SiC, with a 183% increase in d₃₃ value. The PVDF-80KNN-1SiC had the highest d₃₃ value of 30.5 pC/N. It also had the best piezoelectric voltage coefficient and hence the highest figure of merit. Higher SiC contents restrict the efficiency of poling by forming a conductive path across the sample which would deteriorate the piezoelectric performance of the material. The present findings show that PVDF-KNN-SiC composites can be considered as a potential flexible piezoelectric material for future applications.     

Effect of lattice structure evolution and stacking fault energy on the properties of Cu–ZrO2/GNP nanocomposites

A hybrid nanocomposite comprising nanosized ZrO₂ and graphene nanoplatelet (GNP)-reinforced Cu matrix was synthesised via powder metallurgy. The influence of sintering temperature and GNP content on the electrical and mechanical behaviour of the Cu–ZrO₂/GNP nanocomposite was investigated. The ZrO₂ concentration was fixed at 10% for all the composites. Upon increasing the GNP concentration up to 0.5%, a significant improvement was observed in the compressive strength, microhardness, and electrical conductivity of the composite. Furthermore, the properties were significantly improved by increasing the sintering temperature from 900 to 1000 °C. The compressive strength, hardness, and electrical conductivity of Cu–10%ZrO₂/0.5%GNP were higher than those of the Cu–ZrO₂ nanocomposite by 60, 21, and 23.8%, respectively. This improvement in the mechanical properties is because of the decrease in the crystallite size and dislocation spacing, which increases the dislocation density, thereby increasing the impedance towards dislocation movement. The lower stacking fault energy of the hybrid nanocomposites enables easier electron transfer within and between the Cu grains, resulting in an improved electrical conductivity. The enhancement in strength and electrical conductivity were aided by the GNPs and ZrO₂ nanoparticles that were dispersed widely in the Cu matrix.     

Implication of Size-Controlled Graphite Nanosheets as Building Blocks for Thermal Conductive Three-Dimensional Framework Architecture of Nanocarbons

Preparation of three-dimensional (3D) networks has received significant attention as an effective approach for applications involving transport phenomena, such as thermal management materials, and several nanomaterials have been examined as potential building blocks of 3D networks for the improvement of heat conduction in polymer nanocomposites. For that purpose, nanocarbons such as graphene and graphite nanoplatelets have been spotlighted as suitable filler materials because of their excellent thermal conductivities (ca. 10²–10³ W·(m·K)^?1 along their lateral axes) and morphological merits. However, the implications of morphological features such as the lateral length and thickness of graphene or graphene-like materials have not yet been identified. In this study, a controlled dissociation of bulk graphite to graphite nanosheets (GNSs) using a low-cost, ecofriendly bead mill process was extensively examined and, when configured in a 3D framework architecture formation, the size-controlled GNSs demonstrated that the thermal conductivities of a 3D interconnected framework of GNSs and the corresponding polymer nanocomposite were intimately correlated with the size of the GNSs, thus demonstrating the successful preparation of an efficient thermal management material without highly sophisticated efforts. The capability of controlling the lateral size and thickness of the GNSs as well as the use of a 3D interconnected framework architecture should greatly assist the commercialization of high-quality graphene-based thermal management materials in a scalable production process.     

Hemocompatibility,cytotoxicity, and genotoxicity of poly(methylmethacrylate)/nanohydroxyapatite nanocomposites synthesized by melt blending method

The aim of this study was to show the hemocompatibility, cytotoxicity, and genotoxicity of nanocomposites that were synthesized with different molecular weights of poly(methyl methacrylate) (PMMA) and different concentrations of nanohydroxyapatite (nHAp). Different techniques to characterize the nanocomposites were used. The cytotoxicity and genotoxic effects of the polymers and nanocomposites on human lymphocytes were determined by acid phosphatase assay, viability test, and comet assay. Moreover, hemocompatibility test was performed. It was found that all of the PMMA/nHAp nanocomposites are highly hemocompatible and biocompatible, none of the nanocomposites showed a cytotoxic effect, and nHAp addition decreased the genotoxicity.     

Sintering of WC-Ni nanocomposite powder: Experimental and artificial neural networks modeling study

The sintering behavior of WC-Ni nanocomposite powder was evaluated through experimental and statistical approaches to study the contribution of involving parameters of chemical composition (Ni wt. %) and sintering temperature on sinterability of system by assessing the resulted densification and microhardness. The experimental process was designed based on factorial experimental design for independent effective parameters of Ni percentage (12, 18 and 23 wt %), and sintering temperature (8 different values within 1350–1485 °C). The resulted products of experimental testing after compaction and sintering were analyzed by FESEM and EDX to image the microstructure and evaluate the chemical composition and elemental distribution. The density and microhardness were measured as well. An artificial neural network (ANN) was applied to describe the corresponding individual and mutual impacts on sintering. The ANN model was developed by feed-forward back propagation network including topology 2:5:2 and trainlm algorithm to model and predict density and microhardness. A great agreement was observed between the predicted values by the ANN model and the experimental data for density and microhardness (regression coefficients (R²) of 0.9983 and 0.9924 for target functions of relative density and microhardness, respectively). Results showed that the relative importance of operating parameters on target functions (relative density and microhardness) was found to be 62% and 38% for sintering temperature and Ni percentage, respectively. Also, ANN model exhibited relatively high predictive ability and accuracy in describing nonlinear behavior of the sintering of WC-Ni nanocomposite powder. The experimental results confirmed that the appropriate sintering temperature was influenced by Ni content. The optimum parameters were found to be 12 wt % Ni sintered at 1460 °C with the highest microhardness and relative density.     

A mixed phase lanthanum vanadate in situ induced by graphene oxide/graphite carbon nitride for efficient photocatalytic hydrogen generation

A mixed phase LaVO₄ with high dispersion was in situ induced and implanted in graphene oxide-graphite carbon nitride composite. The obtained nanocomposite (GO–C₃N₄–LaVO₄) showed high and stable photocatalytic activity for hydrogen evolution, which significantly benefited from the improved charge separation and light absorption in the special composite photocatalyst as evidenced by UV–vis spectra, fluorescence spectrum, photocurrent response and electrochemical impedance. The fabrication strategy of mixed phase LaVO₄ in the GO-C₃N₄ provides a new idea for constructing cheap and active organic-inorganic semiconductor photocatalysts for hydrogen generation.