In recent years, development in organic solar cells speeds up and performance continuously increases. From the last few years, machine learning gains fame among scientists who are researching on organic solar cells. Herein, machine learning is used to screen the small‐molecule donors for organic solar cells. Molecular descriptors are used as input to train machine models. A variety of machine‐learning models are tested to find the suitable one. Random forest model shows best predictive capability (Pearson's coefficient = 0.93). New small‐molecule donors are also designed from easily synthesizable building units. Their power conversion efficiencies (PCEs) are predicted. Potential candidates with PCE > 11% are selected. The approach presented herein helps to select the efficient materials in short time with ease.

Recent advances in aircraft materials and their manufacturing technologies have enabled progressive growth in innovative materials such as composites. Al-based, Mg-based, Ti-based alloys, ceramic-based, and polymer-based composites have been developed for the aerospace industry with outstanding properties. However, these materials still have some limitations such as insufficient mechanical properties, stress corrosion cracking, fretting wear, and corrosion. Subsequently, extensive studies have been conducted to develop aerospace materials that possess superior mechanical performance and are corrosion-resistant. Such materials can improve the performance as well as the life cycle cost. This review introduces the recent advancements in the development of composites for aircraft applications. Then it focuses on the studies conducted on composite materials developed for aircraft structures, followed by various fabrication techniques and then their applications in the aircraft industry. Finally, it summarizes the efforts made by the researchers so far and the challenges faced by them, followed by the future trends in aircraft materials.

Antioxidants work by interacting with free radicals and converting them into harmless chemicals, interfering with the progression of potentially hazardous chain reactions. Antioxidants are useful in treating illnesses induced by free radicals because they help minimize oxidative stress. Antioxidants, whether natural or synthetic, have a limited effect on cellular health and function because of their low absorption, inability to traverse cellular membrane, and disintegration during delivery. The benefits of antioxidants, both natural and synthetic, are comparable. The use of antioxidants that are covalently attached to nanoparticles, or encased in particles with a hollow center, or feature the nanomaterial encapsulation of various origins has been employed to solve these challenges to provide improved stability, slow and slow sustained release, biocompatibility, and targeted administration. This review examines the importance of metal-based antioxidants and methods for enhancing antioxidant activities based on recent studies.

Synthesis of 5-aryl-N-(pyrazin-2-yl)thiophene-2-carboxamides (4a–4n) by a Suzuki cross-coupling reaction of 5-bromo-N-(pyrazin-2-yl)thiophene-2-carboxamide (3) with various aryl/heteroaryl boronic acids/pinacol esters was observed in this article. The intermediate compound 3 was prepared by condensation of pyrazin-2-amine (1) with 5-bromothiophene-2-carboxylic acid (2) mediated by TiCl4. The target pyrazine analogs (4a–4n) were confirmed by NMR and mass spectrometry. In DFT calculation of target molecules, several reactivity parameters like FMOs (EHOMO, ELUMO), HOMO–LUMO energy gap, electron affinity (A), ionization energy (I), electrophilicity index (ω), chemical softness (σ) and chemical hardness (η) were considered and discussed. Effect of various substituents was observed on values of the HOMO–LUMO energy gap and hyperpolarizability. The p-electronic delocalization extended over pyrazine, benzene and thiophene was examined in studying the NLO behavior. The chemical shifts of 1H NMR of all the synthesized compounds 4a–4n were calculated and compared with the experimental values.

In recent years, research on the development of organic solar cells has increased significantly. For the last few years, machine learning (ML) has been gaining the attention of the scientific community working on organic solar cells. Herein, ML is used to screen small molecule donors for organic solar cells. ML models are fed by molecular descriptors. Various ML models are employed. The predictive capability of a support vector machine is found to be higher (Pearson's coefficient = 0.75). The best small donors with fullerene acceptors are selected to pair with Y6. New small molecule donors are also designed taking into account quantum chemistry principles, using building units that are searched through similarity analysis. Their energy levels and power conversion efficiencies (PCEs) are predicted. Efficient small molecule donors with PCE > 13% are selected. This design and discovery pipeline provides an easy and fast way to select potential candidates for experimental work.

Although the first synthesis of benzotriazole was performed in the 19th century still new methods for their preparation have developed. In this micro review authors focus mostly on the various synthetic strategies developed so far to synthesize benzotriazole and its derivatives by different strategies, such as metal‐free, metal‐assisted [3 + 2] cycloaddition reactions, cyclocondensations, flow methods, heterocyclizations, and so forth. This micro review combines recent (2005–2022 till date) information on the strategies used for the synthesis of benzotriazoles. Moreover, a brief overview of the bio applications of the benzotriazole scaffold along with pharmacological activity is also discussed.

The Covid-19 pandemics caused by SARS-CoV-19, and the inadequacy of targeted medications, compelled scientists to seek new antiviral drugs. We present our current understanding of plant extracts containing polyphenols that inhibit Covid-19. Natural phytochemicals (polyphenols) derived from plants have the potential to establish research using extracts and/or individual compounds in the treatment and prevention of coronavirus. The polyphenolic drugs (antivirus) capable of inhibiting the coronavirus protein, that are vital for infection and virus replication. The benefit of phytochemicals is that they promote patient well-being while causing minimal side effects. To understand the antiviral behavior of isolated phytochemicals 1-6 , various molecular descriptors, molecular electrostatic potential (MEP), and frontier molecular orbitals (FMO) were investigated. A systematic analysis of isolated phytochemicals was accomplished then molecular descriptors, docking score, active sites, and FMOs energies were compared to the commonly used drugs recently to treat COVID19, namely favipiravir, remdesivir dexamethasone and hydroxychloroquine. Using a molecular docking technique, we demonstrate for the first time that these plant phytochemicals can be inhibited by the core protease (6LU7) protein of COVID19.

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