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Herein, we demonstrate an optimization of dye-sensitized solar cells (DSSCs) through the development of single-layer and double-layer configurations. Focusing on the incorporation of brookite and anatase phases in varying ratios, the study aims to determine the optimal composition for enhanced photovoltaic performance. The active layer, composed of anatase- and brookite-TiO2 nanoparticles, is further modified with a scattering layer comprising a mixture of anatase nanoparticles and brookite-TiO2 in the form of nanocube or rice-like particles. The synthesis of TiO2 nanostructures with various morphologies and phase compositions and their subsequent application in single-layer and double-layer DSSCs are presented. The results highlight the superior light-harvesting capabilities achieved through the strategic incorporation of brookite phase into the anatase phase, emphasizing the importance of optimizing the anatase: brookite ratio. The single-layer DSSCs exhibit a peak efficiency of 8.73%, achieved with a composition of 30 wt.% brookite and 70 wt.% anatase at a thickness of 15 μ ms. In the context of double-layer DSSCs, the combined optimization of the active layer composition, scattering layer morphology, and utilization of anatase nanoparticles leads to a remarkable efficiency of 9.18%. These findings underscore the critical role of composition and morphology in enhancing the performance of DSSCs, showcasing the potential for brookite-based DSSCs in solar energy conversion. [ABSTRACT FROM AUTHOR]

Speckle noise is an inherent artifact appearing in medical images that significantly lowers the quality and accuracy of diagnosis and treatment. Therefore, speckle reduction is considered as an essential step before processing and analyzing the ultrasound images. In this paper, we propose an ultrasound speckle reduction method based on speckle noise model estimation using a deep learning architecture called "speckle noise-based inception convolutional denoising neural network" (SNICDNN). Regarding the complicated nature of speckle noise, an inception module is added to the first layer to boost the power of feature extraction. Reconstruction of the despeckled image is performed by introducing a mathematical method based on solving a quadratic equation and applying an image-based inception convolutional denoising autoencoder (IICDAE). The results of various quantitative and qualitative evaluations on real ultrasound images demonstrate that SNICDNN outperforms the state-of-the-art methods for ultrasound despeckling. SNICDNN achieves 0.4579 dB and 0.0100 additional gains on average for PSNR and SSIM, respectively, compared to other methods. Denoising ultrasound based on its noise model estimation is not only a novel approach in comparison to traditional denoising autoencoder models but also due to the fact that it uses mathematical solutions to recover denoised images, SNICDNN shows a greater power in ultrasound despeckling. [ABSTRACT FROM AUTHOR]

Improvement of the photoconversion efficiency and operational stability under environmental conditions is a principal challenge confronted to move forward toward commercialization of dye-sensitized solar cell (DSSC) devices the world over. Herein, enhancement of sunlight harvesting by increasing light scattering via embedding mesoporous TiO2 beads in a photoanode matrix and delaying electrolyte leakage using gel polymer electrolyte, regarded as two approaches to address this challenge, respectively. Photoanodes with various thicknesses and architectures of mesoporous TiO2 beads and nanoparticles are employed in the assembly of DSSC devices in the presence of gel polymer electrolyte. Optical and microstructural analysis showed submicron spherical beads with suitable monodispersity consisting of pure anatase TiO2 nanocrystals and very fine pores. Compared to TiO2 nanoparticles, such a 3D hierarchical structure showed a higher specific surface area (85 m2 g−1) and sunlight scattering (∼20%) but a lower amount of dye-sensitizer adsorption. The photovoltaic characteristics of the assembled devices with various architectures of photoanodes were recorded under simulated AM 1.5 sunlight. The highest photoconversion efficiency of 9.8% was achieved for the photoanode based on mesoporous TiO2 beads in the presence of gel polymer electrolyte, which was comparable to that in liquid electrolyte. Furthermore, it showed a longer operational stability under realistic ambient conditions. [ABSTRACT FROM AUTHOR]

The MWCNTs are decorated by Pd nanoparticles via various techniques including laser ablation in liquid, chemical reduction, and simultaneously both of them. To study the hydrogen adsorption mechanism, Pd K-edge X-ray absorption spectroscopy (XAS) is carried out via heating/cooling processes under He/H2 exposure. The Fourier transform X-ray absorption fine structure (FT-EXAFS) simulation indicates the presence of the Pd–Pd and Pd–C(O) bonds. Furthermore, during the successive cycles of He/H2 exposure, bond restructuring takes place. Moreover, the heating process under He/H2 exposure induces a destructive effect on the Pd–C(O) links. Furthermore, the Pd–Pd bond distance enlarges due to the hydrogen adsorption for all samples, however, in the case of PLAL, the change in the bond distances becomes dominant. XRD and XPS are applied to support the findings. [ABSTRACT FROM AUTHOR]

Heavy metals are stable and persistent pollutants of the environment, and can cause both natural and anthropogenic pollution in the environment. Therefore, they are regarded as a serious risk for survival of living organisms. In order to reduce environmental problems of these metals, we need to identify natural and anthropogenic resources of them. Indeed, identifying the risk factors and awareness of the amount and effects of pollutants on the one hand, and accurate ranking of the polluting units on the other are essential steps for proper evaluation and timely and appropriate response to these risks, resulting in reduced damage due to them. The purpose of this study is to identify potential pollution sources of heavy metals of mercury, arsenic, lead, cadmium and chromium in Zanjan Province of Iran and their sampling, in order to present an index for ranking polluting units using appropriate scientific approaches like multi criteria decision making for a more accurate and quantitative assessment of risks and planning response to them in due time. The results of this study indicate that among 26 sites sampled, Mineral Processing Corporation of Iran is the most critical place of environmental risk in Zanjan province.

National project of Important Heavy Metals Identification of Iran (IHMI), following the UNDP and supported by Department of Environment of Iran (DOE), has been completed by Modares Environmental Research Center (MERC). Due to this project the pollution potential sources was investigated by overall distribution maps of any parameters that may cause the lead pollution. Then the sampling points was determined by some geo-statistical analysis and the sampling process was done according to standard methods of sampling, preserving, transferring to lab, measuring and analyzing etc through the 3 months in three phases of materials (effluent and discharges, solid waste, water, soil and sediment samples from natural sources like river etc.). After gathering the final results, overlaying the potential sources and polluted positions (according to violation of national and international standards of sampled points) by Geographic Information Systems (GIS) led the research to closing to the pollutant sources in north west provinces (Eastern Azerbaijan, Western Azerbaijan, Ardabil and Zanjan). The synthetic and natural pollution sources observed were 17 and 20 respectively. Abir River, Niroo Gostar Taban Industrial Complex and Copper Industries were the most important pollution sources in material phases of Natural, effluent and solid waste respectively.

Herein, we report a new strategy for improving the efficiency and reducing the fabrication cost of dye-sensitized solar cells (DSCs) by elimination of the three- or four-fold layer deposition of TiO2. This is performed by replacing a single layer deposition of mesoporous TiO2 beads, with sub-micrometer size, high surface area and tunable pore size, synthesized by a combination of sol–gel and solvothermal methods. Furthermore, superior electronic properties gained by a reduction in electronic trap states are achieved through doping of pristine TiO2 beads with lithium. The beads have a spherical shape with monodispersed texture consisting of anatase-TiO2 nanocrystals and ultra-fine pores. The outstanding light scattering and harvesting characteristics of the beads emerge from a combination of tailored morphology and crystal structures. These have resulted in a 40% increase in solar to electric power conversion efficiency, for a single spin-coated film without an additional scattering layer and pre- and post-treatment with TiCl4 solution, compared to the reference nanoparticulate TiO2 device. [ABSTRACT FROM AUTHOR]

The aim of this work is providing a suitable method based on the Theory of Critical Distance (TCD) to estimate the fatigue life of notched components in the presence of residual stress induced by the overload cycle. Presented method is relied on a virtual stress field to equalize the effects of real stress distribution in the hot spot around the notch root. This method is noted as Equivalent Virtual Stress (EVS) method. The EVS method combined with some versions of the TCD method, such as the Point Method (PM) and Line Method (LM), were applied for two types of notched samples. Samples were made with U- and V-notches with axial stress concentration factors as 2.45 and 5.55, respectively. The test material was AA 2024-T3 due to its considerable resistance to fatigue failures. The PM was found more conservative, while LM showed more accuracy, especially when the critical distance parameter locates far from critical regions. A good agreement was observed between experimental and predicted results. [ABSTRACT FROM AUTHOR]