Low-Dimensional Halide Perovskites and Their Advanced Optoelectronic Applications

Nano-Micro Letters - A NiFe2O4/expanded graphite (NiFe2O4/EG) nanocomposite was prepared via a simple and inexpensive synthesis method. Its lithium storage properties were studied with the goal of...     

Laminar convection in the annulus of a double-pipe with triangular fins

A steady and laminar convective flow has been numerically simulated in the fully-developed annular region of a finned double-pipe subjected to the constant heat flux boundary condition imposed at the inner-pipe wall. Finite element method has been employed in this study. Friction factor and Nusselt number have been studied as flow characteristics against variations in the ratio of radii of the inner and the outer pipes, the fin height, the fin half angle and the number of fins. The results show significant enhancement in the heat transfer rate in both the cases when sufficient pumping power is available and when it is not. The minimum and maximum increase in the product of friction factor and Reynolds number relative to the finless geometry is more than one time and more than 40 times respectively while gain in the relative value of Nusselt number lies in the range 1–177. This provides an evidence of more than four times enhancement in the heat transfer coefficient relative to that in the pressure loss as a result of extended fin surfaces.     

Association Mechanism and Conformational Changes in Trypsin on Its Interaction with Atrazine: A Multi- Spectroscopic and Biochemical Study with Computational Approach

Atrazine (ATR) is a herbicide globally used to eliminate undesired weeds. Herbicide usage leads to various adverse effects on human health and the environment. The primary source of herbicides in humans is the food laced with the herbicides. The ATR binding to trypsin (TYP) was investigated in this study to explore its binding potential and toxicity. In vitro interaction of ATR with TYP was studied using multi-spectroscopic methods, molecular docking, and enzyme kinetics to explore the mechanism of binding for the TYP-ATR system. The TYP-ATR complex revealed binding constants (10³ M⁻¹), suggesting a moderate binding. The free energy for the TYP-ATR complexes was negative, suggesting a spontaneous interaction. Thermodynamic parameters enthalpy (ΔH) and entropy (ΔS) obtained positive values for the TYP-ATR system suggesting hydrophobic interactions in the binding process. Micro-environmental and conformational changes in TYP molecules were induced on interaction with ATR. Reduced catalytic activity of TYP was observed after interaction with ATR owing to the changes in the secondary structure of the TYP.     

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence.     

Influence of metal‐oxide‐supported bentonites on the pyrolysis behavior of polypropylene and high‐density polyethylene

In this article, we report on the pyrolysis of polypropylene (PP) and high‐density polyethylene (HDPE) in the absence and presence of plain and metal‐oxide‐impregnated bentonite clays [BCs; acid‐washed bentonite clay (AWBC), Zn/AWBC, Ni/AWBC, Co/AWBC, Fe/AWBC, and Mn/AWBC] into useful products. Thermal and catalytic runs were performed at 300°C in the case of PP and at 350°C in the case of HDPE for a contact time of 30 min. The effects of different catalysts and their concentrations on the overall yields and the yields of liquid, gas, and residue were studied. The efficacy of each catalyst is reported on the basis of the highest liquid yields (in weight percentage). The derived liquid products were analyzed by Fourier transform infrared spectroscopy and gas chromatography–mass spectroscopy; this confirmed the presence of paraffins, olefins, and naphthenes. The results indicate the catalytic role of impregnated BCs compared to plain BC with the optimum efficiency shown by Co/AWBC in the case of PP and Zn/AWBC in the case of HDPE toward the formation of liquid products in a desirable C range with the enrichment of olefins and naphthenes in the case of PP and paraffins and olefins in the case of HDPE compared to the thermal run. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41221.     

Κ‐CN gene polymorphism in Nili‐ravi buffalo,Achai and Sahiwal cattle of Pakistan

Kappa‐casein (κ‐CN) is the subtype of casein protein, an important constituent of bovine milk protein. The current study was undertaken to investigate the genetic polymorphism in κ‐CN gene of Nili‐ravi buffalo, Achai and Sahiwal cattle of Pakistan using polymerase chain reaction–restriction fragment length polymorphism (PCR‐RFLP) technique. The Nili‐ravi buffalo was found to be monomorphic (genotype BB only) for κ‐CN gene. Achai cattle were polymorphic for κ‐CN (having three genotypes AA, AB and BB) with a frequency of 0.70, 0.18 and 0.12, respectively, while in Sahiwal cattle, both the genotypes AA and AB were found with genotypic frequencies of 0.92 and 0.08, respectively. The presence of genotype BB in Achai cattle is surprising as it is absent in most of the cattle breeds worldwide.     

Three-dimensional quantitative structure-activity relationship study of nonsteroidal estrogen receptor ligands using the comparative molecular field analysis/cross-validated r2-guided region selection approach

A newly developed comparative molecular field analysis (CoMFA) technique, the cross-validated r2-guided region selection (CoMFA/q2-GRS) method, has been used to build a quantitative structure-activity relationship (3D-QSAR) for nonsteroidal estrogen receptor (ER) ligands. Ligands included in this study belong to a series of diethylstilbestrol (DES) and indenestrol analogues whose affinities for the mouse ER (mER) have been determined in our laboratory. The final model utilized 30 compounds and yielded a q2GRS (cross-validated r2, guided region selection) of 0.796, as compared to a q2 of 0.720 for conventional CoMFA, with a standard error of prediction of 0.594 at 3 principal components. This model was used to visualize steric and electrostatic features of the ligands that correspond with ER binding affinity. Results obtained from the CoMFA steric and electrostatic plots of this model have also been compared to information from the ER binding affinities of substituted estradiol analogues. This is in an effort to determine structural features of compounds in the CoMFA analysis that may correspond to those of the estradiol analogues and to further clarify the mode of binding of nonsteroidal ER ligands.     

Controllable Double Gradient Bandgap Strategy Enables High Efficiency Solution-Processed Kesterite Solar Cells

The double gradient bandgap absorber has the potential to enhance carrier collection, improve light collection efficiency, and make the performance of solar cells more competitive. However, achieving the double gradient bandgap structure is challenging due to the comparable diffusion rates of cations during high-temperature selenization in kesterite Cu₂ZnSn(S,Se)₄ (CZTSSe) films. Here, it has successfully achieved a double gradient bandgap in the CZTSSe absorber by spin-coating the K₂S solution during the preparation process of the precursor film. The K₂S insertion serves as an additional S source for the absorber, and the high-affinity energy of K-Se causes the position of the spin-coated K₂S solution locally Se-rich and S-poor. More importantly, the position of the bandgap minimum (notch) and the depth of the notch can be controlled by varying the concentration of K₂S solution and its deposition stage, thereby avoiding the electronic potential barrier produced by an inadvertent notch position and depth. In addition, the K─Se liquid phase expedites the selenization process to the elimination of the fine grain layer. The champion CZTSSe device achieved an efficiency of 13.70%, indicating the potential of double gradient bandgap engineering for the future development of high-efficiency kesterite solar cells.