Asma Moradi; Ali Mokhtari
Abstract
A B S T R A C TIn the present work, the structural, electronic and optical properties of the lead-free double perovskites Cs2AgBiX6 (X=Br or Cl) are analyzed in the framework of density functional theory (DFT) using the local density and generalized gradient approximations (LDA and GGA) by the Abinit ...
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A B S T R A C TIn the present work, the structural, electronic and optical properties of the lead-free double perovskites Cs2AgBiX6 (X=Br or Cl) are analyzed in the framework of density functional theory (DFT) using the local density and generalized gradient approximations (LDA and GGA) by the Abinit computational package. These compounds are good alternative to lead halide perovskites due to their good stability and non-toxicity. The optical excitations of the double perovskites are important due to their optimal band gap in the visible light spectrum and low excitonic binding energy. The optical properties including: absorption, refraction, extinction and reflection coefficients and loss function are obtained using random phase approximation in the Kohn-Sham (RPA-KS) and Green (RPA-GW) approaches. The results of the Green's function approach are in better agreement with the results of experimental works respect to the RPA-KS approach. In the visible region, there are not volume plasmons and the amount of energy loss is low.
Morteza Pishbini; Sara Mohammadi Bilankohi; Tooraj Ghaffary
Abstract
The phenomenon of localized surface plasmon resonance (LSPR) can be utilized to enhance the light absorption of nanofluids. Core/shell (silica/silver) nanoparticles of various sizes are among the compounds that can be used to increase absorption in nanofluids. Therefore, the optical properties of a hybrid ...
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The phenomenon of localized surface plasmon resonance (LSPR) can be utilized to enhance the light absorption of nanofluids. Core/shell (silica/silver) nanoparticles of various sizes are among the compounds that can be used to increase absorption in nanofluids. Therefore, the optical properties of a hybrid plasmonic nanofluid composed of silica/silver core/shell nanoparticles were studied. The results indicate that the combination of silica/silver core/shell nanostructures of different sizes results in broadband absorption, particularly with core radii ranging from 20 to 50 nanometers. Additionally, as the core radius of the silica increases, the absorption band of the nanofluid extends to longer wavelengths, making the hybrid nanofluid capable of overcoming the limitations of conventional nanofluids with narrowband absorption. Compared to nanofluids containing particles of a single size, the hybrid nanofluid exhibits broadband absorption in the visible to infrared wavelength range. As the particle size increases, the plasmon resonance peak shifts to longer wavelengths. Therefore, larger particles in the hybrid nanofluid enhance the light absorption at longer wavelengths.
Pegah Davrpanah; Somayeh Saraf Esmaili
Abstract
Liver cancer is the fifth most common cancer in men and the seventh most common cancer in women, and is the third leading cause of cancer-related deaths worldwide. In general, the disease is less common in women, and in most regions of the world, the rate of liver cancer in men is two to three times ...
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Liver cancer is the fifth most common cancer in men and the seventh most common cancer in women, and is the third leading cause of cancer-related deaths worldwide. In general, the disease is less common in women, and in most regions of the world, the rate of liver cancer in men is two to three times higher than in women, which is probably due to the higher prevalence of risk factors in men and gender differences. In this regard, the aim of this research was to detect liver cancer from CT scan images using convolutional neural network and support vector machine. In this research, a new lightweight CNN neural network with seven layers and only one conventional layer is proposed for segmented liver classification. This proposed model was used in two different ways. The first path used deep learning classification and achieved 83.7% and 95.9% accuracy. Meanwhile, the second route used automatically extracted features together with a support vector machine (SVM) classifier and achieved 95.9% and 97.9% accuracy. The proposed network is lightweight, fast, reliable and accurate. This approach can be used by an oncologist, making detection a simple task. In addition, the proposed network achieves high accuracy without adjusting images, which reduces time and cost.
noushin dadashzadeh
Abstract
This research explores the fundamental mechanisms underlying electrical discharges in dielectric barrier discharge (DBD) reactors. Specifically, we investigate how voltage parameters, such as amplitude, frequency, and waveform, affect plasma characteristics .Numerical simulations reveal that alterations ...
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This research explores the fundamental mechanisms underlying electrical discharges in dielectric barrier discharge (DBD) reactors. Specifically, we investigate how voltage parameters, such as amplitude, frequency, and waveform, affect plasma characteristics .Numerical simulations reveal that alterations in these parameters can significantly impact the spatial distribution of energy within the plasma. These findings demonstrate that precise control over plasma properties can be achieved through fine-tuning voltage parameters, thereby optimizing DBD reactor performance for applications such as treating water contaminated with volatile organic compounds, generating high-purity ozone for medical purposes, and depositing thin polymer films. This research represents a significant step forward in the design and operation of DBD reactors across various industries.
Masoumeh Talebi; Ali Mokhtari
Abstract
In the present work, we have simulated the vacancy-ordered double perovskites Cs2TiX6 (X = Cl, Br or I) using ab initio calculations. The structural and electronic properties of the Ti-based perovskites show high stability and suitable band gap for them. The direct band gap predicted by the calculations ...
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In the present work, we have simulated the vacancy-ordered double perovskites Cs2TiX6 (X = Cl, Br or I) using ab initio calculations. The structural and electronic properties of the Ti-based perovskites show high stability and suitable band gap for them. The direct band gap predicted by the calculations decreases with enhancing the atomic radius of the halide and is relatively in good agreement with the reported theoretical and experimental values. Also, by calculating the absorption spectrum, several optical properties for these materials have been studied, which show the excellent optical absorption for these compounds, especially iodide perovskite. These properties make this group of halide perovskites suitable candidates for photovoltaic applications.