Numerical simulation to optimize power conversion efficiency of an FTO/GO/Cs2AgBiBr6/Cu2O solar cell.

Efficient conversion of solar power to electrical power through the development of smart, reliable, and environmentally friendly materials is a key focus for the next-generation renewable energy sector. The involvement of degradable and toxic elements present in hybrid perovskites presents serious concerns regarding the commercial viability of these materials for the solar cell industry. In this study, a solar cell with a stable, nondegradable, and lead-free halide-based double perovskite Cs2AgBiBr6 as the absorber layer, Cu2O as a hole transport layer, and GO as the electron transport layer has been simulated using SCAPS 1D. The thickness of the absorber, electron transport, and hole transport layers are tuned to optimize the performance of the designed solar cell. Notably, perovskite solar cells functioned most efficiently with an electron affinity value of 4.0 eV for Cu2O. In addition, the effect of variation of series resistance and temperature on generation and recombination rates, current density, and quantum efficiency has been elaborated in detail. The findings of this study provide valuable insight and encouragement toward the realization of a non-toxic, inorganic perovskite solar device and will be a significant step forward in addressing environmental concerns associated with perovskite solar cell technology.

Negative Poisson's ratio polyethylene matrix and 0.5Ba(Zr0.2 Ti0.8) O3-0.5(Ba0.7 Ca0.3)TiO3 based piezocomposite for sensing and energy harvesting applications.

Finite element studies were conducted on 0.5Ba(Zr0.2 Ti0.8) O3-0.5(Ba0.7 Ca0.3)TiO3 (BCZT) piezoelectric particles embedded in polyethylene matrix to create a piezocomposite having a positive and negative Poisson's ratio of -0.32 and 0.2. Polyethylene with a positive Poisson's ratio is referred to as non-auxetic while those with negative Poisson's ratio are referred to as auxetic or inherently auxetic. The effective elastic and piezoelectric properties were calculated at volume fractions of (4%, 8% to 24%) to study their sensing and harvesting performance. This study compared lead-free auxetic 0-3 piezocomposite for sensing and energy harvesting with non-auxetic one. Inherently auxetic piezocomposites have been studied for their elastic and piezoelectric properties and improved mechanical coupling, but their sensing and energy harvesting capabilities and behavior patterns have not been explored in previous literatures. The effect of Poisson's ratio ranging between -0.9 to 0.4 on the sensing and energy harvesting performance of an inherently auxetic lead free piezocomposite composite with BCZT inclusions has also not been studied before, motivating the author to conduct the present study. Auxetic piezocomposite demonstrated an overall improvement in performance in terms of higher sensing voltage and harvested power. The study was repeated at a constant volume fraction of 24% for a range of Poisson's ratio varied between -0.9 to 0.4. Enhanced performance was observed at the extreme negative end of the Poisson's ratio spectrum. This paper demonstrates the potential improvements by exploiting auxetic matrices in future piezocomposite sensors and energy harvesters.

Effect of Poling on Multicatalytic Performance of 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Sr0.3)TiO3 Ferroelectric Ceramic for Dye Degradation.

Ferroelectric materials with a spontaneous polarization are proven to be potential multicatalysts in water remediation applications. The composition of 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Sr0.3)TiO3 (BST-BZT) was examined for photocatalysis, piezocatalysis, and piezo-photocatalysis processes by degrading an azo dye named methylene blue (MB). Generally, dis-aligned dipoles restrict the catalytic activities due to which the BST-BZT powder sample was poled by the corona poling technique. Coupled piezocatalysis and photocatalysis process, i.e., the piezo-photocatalysis process has shown maximum dye degradation. There was a significant improvement in degradation efficiency by using a poled BST-BZT sample compared to the unpoled sample in all processes, thus the results suggest an extensive scope of poled ferroelectric ceramic powder in the catalysis field.

In-silico Investigations of quinine and quinidine as potential Inhibitors of AKR1B1 and AKR1B10: Functional and structural characterization.

The aberrant expression of aldo keto reductases (AKR1B1 & AKR1B10) has been extensively studied in different types of cancer especially the colon cancer but a very few studies have yet been reported regarding the discovery of inhibitors for the treatment of colon cancer by targeting these isozymes. Therefore, there is a need of selective inhibitors of both targets for the eradication of colon cancer. Currently, the study is focused on the exploration of two quinolone compounds i.e., (S)-(6-Methoxyquinolin-4-yl)[(1S,2R,4S,5R)-5-vinylquinuclidin-2-yl]methanol (Quinidine) and (R)-(6-Methoxyquinolin-4-yl)[(1S,2S,4S,5R)-5-vinylquinuclidin-2-yl]methanol (Quinine) as the potential inhibitors of AKR1B1 and AKR1B10 via detailed in-silico approach. The structural properties including vibrational frequencies, dipole moment, polarizability and the optimization energies were estimated using density functional theory (DFT) calculations; where both compounds were found chemically reactive. After that, the optimized structures were used for the molecular docking studies and here quinidine was found more selective towards AKR1B1 and quinine exhibited maximum inhibition of AKR1B10. The results of molecular docking studies were validated by molecular dynamics simulations which provided the deep insight of stability of protein ligand complex. At the end, the ADMET properties were determined to demonstrate the druglikeness properties of both selected compounds. These findings suggested further exploration of both compounds at molecular level using different in-vivo and in-vitro approaches that will lead to the designing of potential inhibitor of AKR1B1/AKR1B10 for curing colon cancer and related malignancies.

Machine Learning Assisted Prediction of Power Conversion Efficiency of All-Small Molecule Organic Solar Cells: A Data Visualization and Statistical Analysis.

Organic solar cells are famous for their cheap solution processing. Their industrialization needs fast designing of efficient materials. For this purpose, testing of large number of materials is necessary. Machine learning is a better option due to cheaper prediction of power conversion efficiencies. In the present work, machine learning was used to predict power conversion efficiencies. Experimental data were collected from the literature to feed the machine learning models. A detailed data visualization analysis was performed to study the trends of the dataset. The relationship between descriptors and power conversion efficiency was quantitatively determined by Pearson correlations. The importance of features was also determined using feature importance analysis. More than 10 machine learning models were tried to find better models. Only the two best models (random forest regressor and bagging regressor) were selected for further analysis. The prediction ability of these models was high. The coefficient of determination (R2) values for the random forest regressor and bagging regressor models were 0.892 and 0.887, respectively. The Shapley additive explanation (SHAP) method was used to identify the impact of descriptors on the output of models.

Photonics with Gallium Nitride Nanowires.

The surface plasmon resonance in low-dimensional semiconducting materials is a source of valuable scientific phenomenon which opens widespread prospects for novel applications. A systematic study to shed light on the propagation of plasmons at the interface of GaN nanowire is reported. A comprehensive analysis of the interaction of light with GaN nanowires and the propagation of plasmons is carried out to uncover further potentials of the material. The results obtained on the basis of calculations designate the interaction of light with nanowires, which produced plasmons at the interface that propagate along the designed geometry starting from the center of the nanowire towards its periphery, having more flux density at the center of the nanowire. The wavelength of light does not affect the propagation of plasmons but the flux density of plasmons appeared to increase with the wavelength. Similarly, an increment in the flux density of plasmons occurs even in the case of coupled and uncoupled nanowires with wavelength, but more increment occurs in the case of coupling. Further, it was found that an increase in the number of nanowires increases the flux density of plasmons at all wavelengths irrespective of uniformity in the propagation of plasmons. The findings point to the possibility of tuning the plasmonics by using a suitable number of coupled nanowires in assembly.