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Heterostructures comprising two-dimensional (2D) nanomaterials of dissimilar lattice constants govern the interfacial interactions, induce structural strain, and influence the mechanical properties, resulting in a low shear strength to minimize friction. The present work addresses a facile hydrothermal approach to synthesize an ammonium surfactant-stabilized 1T/2H-MoS2heterostructure comprising van der Waals interaction-driven interfacially stacked 1T metallic and 2H semiconducting phases of MoS2. The high mole ratios of the ammonium surfactant facilitated the formation of 1T-MoS2beside the 2H phase, yielding the 1T/2H-MoS2heterostructure. Raman, X-ray photoelectron spectroscopy (XPS), high-resolution transmission electron microscopy (HRTEM), and X-ray diffraction (XRD) analyses explicitly confirmed both the 1T and 2H phases in the 1T/2H-MoS2heterostructures. The long alkyl chain of the ammonium surfactant grafted on the surface of the 1T/2H-MoS2heterostructure extended its dispersibility in fully formulated 10W40 engine lube oil. A minute quantity of 1T/2H-MoS2in engine lube oil (optimum dose: 0.3 mg·mL–1) improved the lubrication performance of the steel tribopair by minimizing friction (24%) and wear volume (76%). Raman analyses of the worn area after the lubrication test with the 1T/2H-MoS2heterostructure revealed the tribo-induced transformation of 1T into the 2H phase and formed a 2H-MoS2-based tribo thin film on contact surfaces of steel balls for enhancement of lubrication properties. The significantly low weak van der Waals interaction between interfacially stacked lamellae of 1T and 2H phases in the 1T/2H-MoS2heterostructure furnished a lower coefficient of friction than that of 2H-MoS2under identical tribological conditions. These findings promise the use of 2D heterostructures for tribological applications to enhance lubrication properties.

Knowledge of variability in phenological traits is of utmost importance in breeding new almond cultivars in the context of impending climate change. The Northwestern Himalayan region is characterized by extreme winters, and phenological studies of fruit crops in relation to environmental variables in this region are scant. Flowering time being an important trait governing agricultural productivity, the objectives of this study were the evaluation of local and exotic almond cultivars for blooming initiation and other associated parameters. This study also aimed at deciphering the association between bloom dates in almonds and prevailing temperatures. Field phenological observations were performed during seven growing seasons (2012–2018) in Kashmir. Phenological traits like endodormancy breaking were estimated using the correlation model. The heat requirements for blooming were estimated using the growing degree days (GDD) method. The association between average temperatures and days to flowering was studied using partial least squares (PLS) regression. Local cultivars ‘Makhdoom’ and ‘Shalimar’ were earliest to bloom within 80 days, while the exotic cultivars were late bloomers, requiring 87 days. Cultivars ‘Makhdoom’, ‘Shalimar’, ‘Drake’ and ‘Pranyaj’ broke their endodormancy on the same date, i.e. December 26, although another group including ‘Waris’, ‘California Paper Shell’ and ‘Merced’ exhibited endo- to ecodormancy transition on January 21. In general, Himalayan-origin almond cultivars revealed low heat requirements for flowering compared to the exotic ones. PLS regression analysis identified four major periods in which average temperatures successfully explained variation in days to blooming in almonds. In conclusion, a phenological prediction model is presented here that explains variation in blooming dates in almond cultivars as a function of average temperatures. This model addresses the almond cultivars growing in the Himalayan region and is expected to be of great practical utility to the farming community to efficiently plan their orchard management practices.

Immunotherapy has become increasingly popular in recent years for treating a variety of diseases including inflammatory, neurological, oncological, and auto-immune disorders. The significant interest in antibody development is due to the high binding affinity and specificity of an antibody against a specific antigen. Recent advances in antibody engineering have provided a different view on how to engineer antibodies in silicofor therapeutic and diagnostic applications. In order to improve the clinical utility of therapeutic antibodies, it is of paramount importance to understand the various molecular properties which impact antigen targeting and its potency. In antibody engineering, antibody numbering (AbN) systems play an important role to identify the complementarity determining regions (CDRs) and the framework regions (FR). Hence, it is crucial to accurately define and understand the CDR, FR and the crucial residues of heavy and light chains that aid in the binding of the antibody to the antigenic site. Detailed understanding of amino acids positions are useful for modifying the binding affinity, specificity, physicochemical features, and half-life of an antibody. In this review, we have summarized the different antibody numbering systems that are widely used in antibody engineering and highlighted their significance. Here, we have systematically explored and mentioned the various tools and servers that harness different AbN systems.