Achieving above 24% efficiency with non-toxic CsSnI3 perovskite solar cells by harnessing the potential of the absorber and charge transport layers.

Lead toxicity is a barrier to the widespread commercial manufacture of lead halide perovskites and their use in solar photovoltaic (PV) devices. Eco-friendly lead-free perovskite solar cells (PSCs) have been developed using certain unique non- or low-toxic perovskite materials. In this context, Sn-based perovskites have been identified as promising substitutes for Pb-based perovskites due to their similar characteristics. However, Sn-based perovskites suffer from chemical instability, which affects their performance in PSCs. This study employs theoretical simulations to identify ways to improve the efficiency of Sn-based PSCs. The simulations were conducted using the SCAPS-1D software, and a lead-free, non-toxic, and inorganic perovskite absorber layer (PAL), i.e. CsSnI3 was used in the PSC design. The properties of the hole transport layer (HTL) and electron transport layer (ETL) were tuned to optimize the performance of the device. Apart from this, seven different combinations of HTLs were studied, and the best-performing combination was found to be ITO/PCBM/CsSnI3/CFTS/Se, which achieved a power conversion efficiency (PCE) of 24.73%, an open-circuit voltage (VOC) of 0.872 V, a short-circuit current density (JSC) of 33.99 mA cm-2 and a fill factor (FF) of 83.46%. The second highest PCE of 18.41% was achieved by the ITO/PCBM/CsSnI3/CuSCN/Se structure. In addition to optimizing the structure of the PSC, this study also analyzes the current density-voltage (J-V) along with quantum efficiency (QE), as well as the impact of series resistance, shunt resistance, and working temperature, on PV performance. The results demonstrate the potential of the optimized structure identified in this study to enhance the standard PCE of PSCs. Overall, this study provides important insights into the development of lead-free absorber materials and highlights the potential of using CsSnI3 as the PAL in PSCs. The optimized structure identified in this study can be used as a base for further research to improve the efficiency of Sn-based PSCs.

Harnessing the potential of CsPbBr3-based perovskite solar cells using efficient charge transport materials and global optimization.

Perovskite solar cells (PSCs) have become a possible alternative to traditional photovoltaic devices for their high performance, low cost, and ease of fabrication. Here in this study, the SCAPS-1D simulator numerically simulates and optimizes CsPbBr3-based PSCs under the optimum illumination situation. We explore the impact of different back metal contacts (BMCs), including Cu, Ag, Fe, C, Au, W, Pt, Se, Ni, and Pd combined with the TiO2 electron transport layer (ETL) and CFTS hole transport layer (HTL), on the performance of the devices. After optimization, the ITO/TiO2/CsPbBr3/CFTS/Ni structure showed a maximum power conversion efficiency (PCE or η) of 13.86%, with Ni as a more cost-effective alternative to Au. After the optimization of the BMC the rest of the investigation is conducted both with and without HTL mode. We investigate the impact of changing the thickness and the comparison with acceptor and defect densities (with and without HTL) of the CsPbBr3 perovskite absorber layer on the PSC performance. Finally, we optimized the thickness, charge carrier densities, and defect densities of the absorber, ETL, and HTL, along with the interfacial defect densities at HTL/absorber and absorber/ETL interfaces to improve the PCE of the device; and the effect of variation of these parameters is also investigated both with and without HTL connected. The final optimized configuration achieved a VOC of 0.87 V, JSC of 27.57 mA cm-2, FF of 85.93%, and PCE of 20.73%. To further investigate the performance of the optimized device, we explore the impact of the temperature, shunt resistance, series resistance, capacitance, generation rate, recombination rate, Mott-Schottky, JV, and QE features of both with and without HTL connected. The optimized device offers the best thermal stability at a temperature of 300 K. Our study highlights the potential of CsPbBr3-based PSCs and provides valuable insights for their optimization and future development.

Numerical Study of Titanium Dioxide and MXene Nanomaterial-Based Surface Plasmon Resonance Biosensor for Virus SARS-CoV-2 Detection.

A novel surface plasmon resonance-based biosensor for SARS-CoV-2 virus is proposed in this article. The biosensor is a Kretschmann configuration-based structure that consists of CaF2 prism as base, at which silver (Ag), TiO2, and MXene nanolayers are used to enhance the performance. Theoretically, the performance parameters have been investigated by means of Fresnel equations and transfer matrix method (TMM). The TiO2 nanolayer not only prevents oxidation of Ag layer but also enhances the evanescent field in its vicinity. The sensor provides an ultrahigh angular sensitivity of 346°/RIU for the detection of SARS-CoV-2 virus. Some other performance parameters, including FWHM (full width at half maxima), detection accuracy (DA), limit of detection (LOD), and quality factor (QF) have also been calculated for proposed SPR biosensor with their optimized values 2.907°, 0.3439 deg-1, 1.445 × 10-5, and 118.99 RIU-1, respectively. The obtained results designate that the proposed surface plasmon resonance (SPR) based biosensor has notably enhanced angular sensitivity as compared to previous results reported in the literatures till date. This work may facilitate a significant biological sample sensing device for fast and accurate diagnosis at early stage of SARS-CoV-2 virus.

High Power-Conversion Efficiency of Lead-Free Perovskite Solar Cells: A Theoretical Investigation.

Solar cells based on lead-free perovskite have demonstrated great potential for next-generation renewable energy. The SCAPS-1D simulation software was used in this study to perform novel device modelling of a lead-free perovskite solar cell of the architecture ITO/WS2/CH3NH3SnI3/P3HT/Au. For the performance evaluation, an optimization process of the different parameters such as thickness, bandgap, doping concentration, etc., was conducted. Extensive optimization of the thickness and doping density of the absorber and electron transport layer resulted in a maximum power-conversion efficiency of 33.46% for our designed solar cell. Because of the short diffusion length and higher defect density in thicker perovskite, an absorber thickness of 1.2 µm is recommended for optimal solar cell performance. Therefore, we expect that our findings will pave the way for the development of lead-free and highly effective perovskite solar cells.

Numerical Study to Enhance the Sensitivity of a Surface Plasmon Resonance Sensor with BlueP/WS2-Covered Al2O3-Nickel Nanofilms.

In the traditional surface plasmon resonance sensor, the sensitivity is calculated by the usage of angular interrogation. The proposed surface plasmon resonance (SPR) sensor uses a diamagnetic material (Al2O3), nickel (Ni), and two-dimensional (2D) BlueP/WS2 (blue phosphorous-tungsten di-sulfide). The Al2O3 sheet is sandwiched between silver (Ag) and nickel (Ni) films in the Kretschmann configuration. A mathematical simulation is performed to improve the sensitivity of an SPR sensor in the visible region at a frequency of 633 nm. The simulation results show that an upgraded sensitivity of 332°/RIU is achieved for the metallic arrangement consisting of 17 nm of Al2O3 and 4 nm of Ni in thickness for analyte refractive indices ranging from 1.330 to 1.335. The thickness variation of the layers plays a curial role in enhancing the performance of the SPR sensor. The thickness variation of the proposed configuration containing 20 nm of Al2O3 and 1 nm of Ni with a monolayer of 2D material BlueP/WS2 enhances the sensitivity to as high as 374°/RIU. Furthermore, it is found that the sensitivity can be altered and managed by means of altering the film portions of Ni and Al2O3.

2D Nanomaterial-Based Surface Plasmon Resonance Sensors for Biosensing Applications.

The absorption and binding energy of material plays an important role with a large surface area and conductivity for the development of any sensing device. The newly grown 2D nanomaterials like black phosphorus transition metal dichalcogenides (TMDCs) or graphene have excellent properties for sensing devices' fabrication. This paper summarizes the progress in the area of the 2D nanomaterial-based surface plasmon resonance (SPR) sensor during last decade. The paper also focuses on the structure of Kretschmann configuration, the sensing principle of SPR, its characteristic parameters, application in various fields, and some important recent works related to SPR sensors have also been discussed, based on the present and future scope of this field. The present paper provides a platform for researchers to work in the field of 2D nanomaterial-based SPR sensors.

Zinc and selenium combination treatment protected diabetes-induced testicular and epididymal damage in rat.

Diabetes increases the possibility of germ cell damage, hypogonadism, and male infertility. Diabetic condition negatively impacts zinc (Zn) and selenium (Se) levels in the body. Zn and Se are among the most important trace elements involved in the regulation of redox reaction, antioxidants enzymes activities, and DNA expression in a germ cell. The present study aimed to elucidate the combined effects of Zn and Se treatment on diabetes-induced germ cell damage in male Sprague Dawley rats. Type 1 diabetes was induced by the single intraperitoneal (i.p.) injection of streptozotocin (55 mg/kg). Zn (3 mg/kg, i.p.) and Se (0.5 mg/kg, i.p.) were administered daily for 8 consecutive weeks. All the animals were provided with normal feed and water throughout the study. The effects on germ cell damage were evaluated by body weight, feed-water intake, organ weight, sperm count, motility, sperm head morphology, biochemical analysis, histology, immunohistochemistry, halo assay, germ cell comet assay, testes terminal deoxynucleotidyl transferase deoxyuridine triphosphate nick end-labeling (TUNEL) assay, sperm TUNEL assay, serum protein pattern analysis, and subcellular analysis using transmission electron microscopy. Further, the expressions of nuclear erythroid-derived related factor 2, catalase, glutathione peroxidase 4, and glutathione peroxidase 5 were carried out to ascertain the mechanism of protection. The present results demonstrated that 8 weeks combined treatment of Zn (3 mg/kg, i.p.) and Se (0.5 mg/kg, i.p.) reduced diabetes-induced germ cell damage. This study further highlighted that Zn and Se combination treatment might be a better strategy for the germ cell protection in diabetes and deserve further investigation.

Ethanol-induced gastric ulcer in rats and intervention of tert-butylhydroquinone: Involvement of Nrf2/HO-1 signalling pathway.

Gastric ulcer (GU) is the most common health concern that occurs due to alcohol consumption, smoking and physiological stress. Ethanol-induced GU in animal model resembles the pathophysiology of human ulcer. The present study was designed to investigate the cytoprotective and anti-inflammatory properties of tert-butylhydroquinone (tBHQ), a nuclear factor erythroid 2-related factor 2 (Nrf2) activator, against gastric mucosal damage induced by acute exposure of ethanol (5 ml/kg). The intervention of tBHQ (25 and 50 mg/kg, per os (po)) and omeprazole (20 mg/kg, po) was done for 10 consecutive days. Omeprazole was chosen as a standard drug because it is prescribed for the treatment of GU. Pretreatment of tBHQ decreased gastric mucosal lesion, ulcer index, apoptotic cells and lipid peroxidation level induced by ethanol. Furthermore, the intervention of tBHQ increased gastric mucosa integrity, pH, reduced glutathione, collagen and mucus-producing goblet cells. Intervention of tBHQ increased the expression of antioxidant markers such as Nrf2, haeme oxygenase-1 and catalase and decreased the expressions of inflammatory markers such as nuclear factor kappa-light-chain-enhancer of activated B cells and cyclooxygenase-2. The cytoprotective potential of tBHQ against gastric mucosal damage might be due to its ability to enhance cellular antioxidants and anti-inflammatory responses.

Predictive Models in Differentiating Vertebral Lesions Using Multiparametric MRI.

BACKGROUND AND PURPOSE: Conventional MR imaging has high sensitivity but limited specificity in differentiating various vertebral lesions. We aimed to assess the ability of multiparametric MR imaging in differentiating spinal vertebral lesions and to develop statistical models for predicting the probability of malignant vertebral lesions. MATERIALS AND METHODS: One hundred twenty-six consecutive patients underwent multiparametric MRI (conventional MR imaging, diffusion-weighted MR imaging, and in-phase/opposed-phase imaging) for vertebral lesions. Vertebral lesions were divided into 3 subgroups: infectious, noninfectious benign, and malignant. The cutoffs for apparent diffusion coefficient (expressed as 10-3 mm2/s) and signal intensity ratio values were calculated, and 3 predictive models were established for differentiating these subgroups. RESULTS: Of the lesions of the 126 patients, 62 were infectious, 22 were noninfectious benign, and 42 were malignant. The mean ADC was 1.23 ± 0.16 for infectious, 1.41 ± 0.31 for noninfectious benign, and 1.01 ± 0.22 mm2/s for malignant lesions. The mean signal intensity ratio was 0.80 ± 0.13 for infectious, 0.75 ± 0.19 for noninfectious benign, and 0.98 ± 0.11 for the malignant group. The combination of ADC and signal intensity ratio showed strong discriminatory ability to differentiate lesion type. We found an area under the curve of 0.92 for the predictive model in differentiating infectious from malignant lesions and an area under the curve of 0.91 for the predictive model in differentiating noninfectious benign from malignant lesions. On the basis of the mean ADC and signal intensity ratio, we established automated statistical models that would be helpful in differentiating vertebral lesions. CONCLUSIONS: Our study shows that multiparametric MRI differentiates various vertebral lesions, and we established prediction models for the same.