Shiv Nadar University

About: Shiv Nadar University is a education organization based out in Dadri, Uttar Pradesh, India. It is known for research contribution in the topics: Population & Graphene. The organization has 1015 authors who have published 1924 publications receiving 18420 citations.

Enhanced cavitation erosion resistance of a friction stir processed high entropy alloy

Abstract: Friction stir processing of an Al0.1CoCrFeNi high entropy alloy (HEA) was performed at controlled cooling conditions (ambient and liquid submerged). Microstructural and mechanical characterization of the processed and as-cast HEAs was evaluated using electron backscat-ter diffraction, micro-hardness testing and nanoindentation. HEA under the submerged cooling condition showed elongated grains (10 µm) with fine equiaxed grains (2 µm) along the boundary compared to the coarser grain (∼2 mm) of as-cast HEA. The hardness showed remarkable improvements with four (submerged cooling condition) and three (ambient cooling condition) times that of as-cast HEA (HV ∼150). The enhanced hardness is attributed to the significant grain refinement in the processed HEAs. Cavitation erosion behavior was observed for samples using an ultrasonication method. All of the HEAs showed better cavitation erosion resistance than the stainless steel 316L. The sample processed under a submerged liquid condition showed approximately 20 and 2 times greater erosion resistance than stainless steel 316L and as-cast HEA, respectively. The enhanced erosion resistances of the processed HEAs correlate to their increased hardness, resistance to plasticity, and better yield strength than the as-cast HEA. The surface of the tested samples showed nucleation and pit growth, and plastic deformation of the material followed by fatigue-controlled disintegration as the primary material removal mechanism.

An Efficient Jaya Algorithm for Multi-objective Permutation Flow Shop Scheduling Problem

Abstract: The Jaya algorithm is a novel, simple, and efficient meta-heuristic optimization technique and has received a successful application in the various fields of engineering and sciences. In the present paper, we apply the Jaya algorithm to permutation flow shop scheduling problem (PFSP) with the multi-objective of minimization of maximum completion time (makespan) and tardiness cost under due date constraints. PFSP is a well-known NP-hard and discrete combinatorial optimization problem. Firstly, to retrieve a job sequence, a random preference is allocated to each job in a permutation schedule. Secondly, a job preference vector is transformed into a job permutation vector by means of largest order value (LOV) rule. To deal with the multi-objective criteria, we apply a multi-attribute model (MAM) based on Apriori approach. The correctness of the Jaya algorithm is verified by comparing the results with the total enumeration method and simulated annealing (SA) algorithm. Computational results reveal that the proposed optimization technique is well efficient in solving multi-objective discrete combinatorial optimization problems such as the flow shop scheduling problem in the present study.

Molecular-Shape-Induced Efficiency Enhancement in PC61BM and PC71BM Based Ternary Blend Organic Solar Cells

Abstract: Evolution of a self-organized molecular packing at the microscopic scale in a bulk heterojunction active layer is critical for improving the performance of organic solar cells. We demonstrate that the molecular-shape-induced effects improve the morphology of the ternary thin films as PC61BM molecules were added to the host binary blend, PTB7-Th:PC71BM. Compared to the binary PTB7-Th:PC71BM devices, the ternary devices with 20% PC61BM content (relative to PC71BM) exhibited an enhanced efficiency, from 6.4% to 8.5%. In particular, we find that the spherical PC61BM molecules with better precipitation kinetics than ellipsoidal PC71BM alter the morphology of ternary thin film and modulate interfaces to expedite charge transport and collection by reducing various recombination losses.

Triazole Linked N-Acetylglucosamine Based Gelators for Crude Oil Separation and Dye Removal

Abstract: Marine oil-spills have a long-lasting impact on the environment; therefore, it is a major concern in the scientific community to find a solution for remediation. Recently, phase selective organo-gelators emerged as potential materials for removal of oil from water through selective gelation. Herein, we report synthesis of a series of C-6 triazole linked N-acetylglucosamine derivatives, among which three have shown excellent selective gelation of organic solvents, diesel, petrol, and crude oils in water and seawater. We have studied phase selective gelation against different API grade crude oils (from light to heavy), and the gelation was achieved using nontoxic carrier solvent at room temperature in less than 15 min, and gelators were found useful for recovering crude oils. Critical gel concentration (CGC) of crude oil gelators was found to be 2.3-12% (w/v). The variable temperature NMR and FTIR experiments reveal that intermolecular hydrogen bonding was responsible for gel formation. Furthermore, a gelator was utilized for selective dye removal from water.