Within this work, to promote the efficiency of organic-based solar cells, a series of novel A-π-D type small molecules were scrutinised. The acceptors which we designed had a moiety of N, N-dimethylaniline as the donor and catechol moiety as the acceptor linked through various conjugated π-linkers. We performed DFT (B3LYP) as well as TD-DFT (CAM-B3LYP) computations using 6-31G (d,p) for scrutinising the impact of various π-linkers upon optoelectronic characteristics, stability, and rate of charge transport. In comparison with the reference molecule, various π-linkers led to a smaller HOMO–LUMO energy gap. Compared to the reference molecule, there was a considerable red shift in the molecules under study (A1–A4). Therefore, based on the analysis of energy level, A4 and A3 were shown to be promising non-fullerene acceptors with the designed donors for applications in solar cells. It is hoped that the current study would provide theoretical insights into the design and amplification of optoelectronic characteristics of suggested frameworks on a grand scale in comparison with the reference molecules.
Mycotoxins are secondary by-products of mold metabolism and are accountable for human and animal mycotoxicosis. The most serious trichothecenic mycotoxin is the fungal T-2 mycotoxin. T-2 mycotoxin impaired nutrient absorption, metabolism, and then, eliciting severe oxidoreductive stress. Diet plays a key role beyond the supply of nutrients in order to promote animal and human health. Organic acids have been commonly used to exert antioxidative stress capacity in the liver and gut ecosystem. This study is planned to explore, the competence of using (X-MoldCid®) during chronic T-2 mycotoxicosis course in rat. Rats were allocated into 4 main groups, (CN-Gr), negative control and was allowed for the free access to the normal rats chow and the
... Show MoreChlorinated volatile organic compounds (CVOCs) are toxic chemical entities emitted invariably from stationary thermal operations when a trace of chlorine is present. Replacing the high-temperature destruction operations of these compounds with catalytic oxidation has led to the formulation of various potent metal oxides catalysts; among them are ceria-based materials. Guided by recent experimental measurements, this study theoretically investigates the initial steps operating in the interactions of ceria surface CeO2(111) with three CVOC model compounds, namely chloroethene (CE), chloroethane (CA) and chlorobenzene (CB). We find that, the CeO2(111) surface mediates fission of the carbon–chlorine bonds in the CE, CA and CB molecules via mo
... Show MoreThis work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camadulensis leaves) by organic solvents. the effects of the main operating parameters were studied; type of solvent (n-hexane and ethanol), time to reach equilibrium, the temperature (45°C to 65°C) for n-hexane and (45°C to 75°C) for ethanol, solvent to solid ratio (5:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm) and the particle size (0.5 to 2.5 cm) of fresh leaves to find the best processing conditions for the achieving maximum oil yield. The concentration of eucalyptus oil in solvent was measured by using UV-spectrophotometer. The results (for n-hexane) showed that the agitation speed of 900 rpm, temperature 65°C with solvent to soli
... Show MoreHigh-power density supercapacitors and high-energy–density batteries have gotten a lot of interest since they are critical for the power supply of future electric cars, portable electronic gadgets, unmanned aircraft, and so on. The electrode materials used in supercapacitors and batteries have a significant impact on the practical energy and power density. Metal–organic frameworks (MOFs) have the outstanding electrochemical ability because of their ultrahigh porous structure, ease of functionalization, and great specific surface area. These features make it an intriguing electrode material with good electrochemical efficiency for high-storage batteries. Thus, this review summarizes current developments in MOFs-based materials as an elec
... Show MoreThis study compared in vitro the microleakage of a new low shrink silorane-based posterior composite (Filtek™ P90) and two methacrylate-based composites: a packable posterior composite (Filtek™ P60) and a nanofill composite (Filtek™ Supreme XT) through dye penetration test. Thirty sound human upper premolars were used in this study. Standardized class V cavities were prepared at the buccal surface of each tooth. The teeth were then divided into three groups of ten teeth each: (Group 1: restored with Filtek™ P90, Group 2: restored with Filtek™ P60, and Group 3: restored with Filtek™ Supreme XT). Each composite system was used according to the manufacturer's instructions with their corresponding adhesive systems. The teeth were th
... Show MoreWith the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
... Show MoreSpatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati
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