A qualitative Design and optimization of CIGS-based Solar Cells with Sn2S3 Back Surface Field: A plan for achieving 21.83 % efficiency.

Conventional Copper Indium Gallium Di Selenide (CIGS)-based solar cells are more efficient than second-generation technology based on hydrogenated amorphous silicon (a-Si: H) or cadmium telluride (CdTe). So, herein the photovoltaic (PV) performance of CIGS-based solar cells has been investigated numerically using SCAPS-1D solar simulator with different buffer layer and less expensive tin sulfide (Sn2S3) back-surface field (BSF). At first, three buffer layer such as cadmium sulfide (CdS), zinc selenide (ZnSe) and indium-doped zinc sulfide ZnS:In have been simulated with CIGS absorber without BSF due to optimized and non-toxic buffer. Then the optimized structure of Al/FTO/ZnS:In/CIGS/Ni is modified to become Al/FTO/ZnS:In/CIGS/Sn2S3/Ni by adding a Sn2S3 BSF to enhanced efficiency. The detailed analysis have been investigated is the influence of physical properties of each absorber and buffer on photovoltaic parameters including layer thickness, carrier doping concentration, bulk defect density, interface defect density. This study emphasizes investigating the reasons for the actual devices' poor performance and illustrates how each device's might vary open-circuit voltage (VOC), short-circuit current density (JSC), fill factor (FF), power conversion efficiency (PCE), and quantum efficiency (QE). The optimized structure offers outstanding power conversion efficiency (PCE) of 21.83 % with only 0.80 µm thick CIGS absorber. The proposed CIGS-based solar cell performs better than the previously reported conventional designs while also reducing CIGS thickness and cost.

Phyllanthus emblica (Amla) methanolic extract regulates multiple checkpoints in 15-lipoxygenase mediated inflammopathies: Computational simulation and in vitro evidence.

Amla (Phyllanthus emblica) has long been used in traditional folk medicine to prevent and cure a variety of inflammatory diseases. In this study, the antioxidant activity (DPPH scavenging and reducing power), anti-inflammatory activity (RBC Membrane Stabilization and 15-LOX inhibition), and anticoagulation activity (Serin protease inhibition and Prothrombin Time assays) of the methanolic extract of amla were conducted. Amla exhibited a substantial amount of phenolic content (TPC: 663.53 mg GAE/g) and flavonoid content (TFC: 418.89 mg GAE/g). A strong DPPH scavenging effect was observed with an IC50 of 311.31 µg/ml as compared to standard ascorbic acid with an IC50 of 130.53 µg/ml. In reducing power assay, the EC50 value of the extract was found to be 196.20 µg/ml compared to standard ascorbic acid (EC50 = 33.83 µg/ml). The IC50 value of the RBC membrane stabilization and 15-LOX assays was observed as 101.08 µg/ml (IC50 of 58.62 µg/ml for standard aspirin) and 195.98 µg/ml (IC50 of 19.62 µg/ml for standard quercetin), respectively. The extract also strongly inhibited serine protease (trypsin) activity with an IC50 of 505.81 µg/ml (IC50 of 295.44 µg/ml for standard quercetin). The blood coagulation time (PTT) was found to be 11.91 min for amla extract and 24.11 min for standard Warfarin. Thus, the findings of an in vitro study revealed that the methanolic extract of amla contains significant antioxidant, anti-inflammatory, and anticoagulation activity. Furthermore, in silico docking and simulation of reported phytochemicals of amla with human 15-LOXA and 15-LOXB were carried out to validate the anti-inflammatory activity of amla. In this analysis, epicatechin and catechin showed greater molecular interaction and were considerably stable throughout the 100 ns simulation with 15-lipoxygenase A (15-LOXA) and 15-lipoxygenase B (15-LOXB) respectively.

Molecular optimization, docking, and dynamic simulation profiling of selective aromatic phytochemical ligands in blocking the SARS-CoV-2 S protein attachment to ACE2 receptor: an in silico approach of targeted drug designing.

OBJECTIVES: The comprehensive in silico study aims to figure out the most effective aromatic phytochemical ligands among a number from a library, considering their pharmacokinetic efficacies in blocking "angiotensin-converting enzyme 2 (ACE2) receptor-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S protein" complex formation as part of a target-specific drug designing. MATERIALS AND METHODS: A library of 57 aromatic pharmacophore phytochemical ligands was prepared from where the top five ligands depending on Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) and quantitative structure-activity relationship (QSAR)-based pharmacokinetic properties were considered. The selected ligands were optimized for commencing molecular docking and dynamic simulation as a complex with the ACE2 receptor to compare their blocking efficacy with the control drug. The ligand-receptor complexes' accuracy in preventing the Spike (S) protein of SARS-CoV-2 penetration inside the host cells has been analyzed through hydrogen-hydrophobic bond interactions, principal component analysis (PCA), root mean square deviation (RMSD), root mean square fluctuation (RMSF), and B-Factor. Advanced in silico programming language and bioanalytical software were used for high throughput and authentic results. RESULTS: ADMET and QSAR revealed Rhamnetin, Lactupicrin, Rhinacanthin D, Flemiflavanone D, and Exiguaflavanone A as the ligands of our interest to be compared with the control Cassiarin D. According to the molecular docking binding affinity to block ACE2 receptor, the efficiency mountings were Rhinacanthin D > Flemiflavanone D > Lactupicrin > Exiguaflavanone A > Rhamnetin. The binding affinity of the Cassiarin D-ACE2 complex was (-10.2 KJ/mol) found inferior to the Rhinacanthin D-ACE2 complex (-10.8 KJ/mol), referring to Rhinacanthin D as a more stable candidate to use as drugs. The RMSD values of protein-ligand complexes evaluated according to their structural conformation and stable binding pose ranged between 0.1~2.1 Å. The B-factor showed that very few loops were present in the protein structure. The RMSF peak fluctuation regions ranged 5-250, predicting efficient ligand-receptor interactions. CONCLUSION: The experiment sequentially measures all the parameters required in referring to any pharmacophore as a drug, considering which all aromatic components analyzed in the study can strongly be predicted as target-specific medication against the novel coronavirus 2019 infection.