Influence of surface modification by 2-aminothiophenol on optoelectronics properties of ZnO nanoparticles

In this study, a precipitation method was used to synthesise ZnO nanoparticles using suitable precursors. An efficient surface modification method was proposed in order to reduce the agglomeration among synthesised small sized ZnO nanoparticles using 2-aminothiophenol as a capping agent. This article briefly investigated the effects of capping agent like 2-aminothiophenol on the optoelectronic properties of ZnO nanoparticles. The modified effectivity of 2-aminothiophenol has been examined on the nanosized ZnO nanoparticle for fluorescence and UV–visible (UV–vis) studies. The mechanism was studied for ZnO nanoparticles light emitting capability under different conditions. By facilitating the capping of ZnO with 2-aminothiophenol, fluorescence emission of the surface defects vanishes and ultraviolet (UV) emission increases. Surface capping by 2-aminothiophenol effectively covers most of the surface defects of ZnO and results in quenching of the visible region. The UV–vis absorption spectra of modified ZnO nanoparticles has been influenced by modified ZnO nanoparticles as a result of surface modification; where marked blue shift in absorption edge results. By surface modification of ZnO nanoparticles, change in optoelectronics properties has opened the new scope and possibilities to explore and fine tune the optical character of the modified ZnO for various optoelectronics applications such as UV laser.     

The effect of inulin as a fat replacer on the quality of low‐fat ice cream

The influence of different levels of inulin as fat replacer on the quality of ice cream was investigated. Inulin was added at 2, 4 and 6% to replace milk fat and the experimental ice creams were compared to a control with 10% milk fat. The chemical composition, overrun, water activity, viscosity, melting rate, hardness and colour value were determined. Sensory properties of the ice cream samples were evaluated during storage. The overall acceptability of ice creams prepared with 2 and 4% substitution were similar to the control.     

Non-Newtonian blood flow with magnetic nanoparticles in a W-shaped stenosed arterial segment: A numerical study

Flow of blood, infused with magnetic nanoparticles, in a W-shaped stenosed human arterial segment is studied numerically using a realistic non-Newtonian blood rheology model. It is observed that the Newtonian model predicts less time to reach a steady state than the non-Newtonian blood rheology model. An increased drug retention time at the target site with an increase in nanoparticle concentration is predicted. Detailed simulations further reveal that the skin friction coefficient does not increase significantly with the increase in nanoparticle concentration. Hence, it is anticipated from our study that the infusion of drug-carrying nanoparticles in blood flow does not excessively enhance wall shear stress that may lead to arterial wall damage. An overall increase in heat transfer rates and wall shear stress at the stenosed section is seen with an increase in Reynolds number. The present study provides valuable information for designing computer-assisted drug delivery systems.     

Hybrid approach to implement multi-robotic navigation system using neural network,fuzzy logic,and bio-inspired optimization methodologies

Mobile robots have been increasingly popular in a variety of industries in recent years due to their ability to move in variable situations and perform routine jobs effectively. Path planning, without a dispute, performs a crucial part in multi-robot navigation, making it one of the very foremost investigated issues in robotics. In recent times, meta-heuristic strategies have been intensively investigated to tackle path planning issues in the similar way that optimizing issues were handled, or to design the optimal path for such multi-robotics to travel from the initial point to such goal. The fundamental purpose of portable multi-robot guidance is to navigate a mobile robot across a crowded area from initial point to target position while maintaining a safe route and creating optimum length for the path. Various strategies for robot navigational path planning were investigated by scientists in this field. This work seeks to discuss bio-inspired methods that are exploited to optimize hybrid neuro-fuzzy analysis which is the combination of neural network and fuzzy logic is optimized using the particle swarm optimization technique in real-time scenarios. Several optimization approaches of bio-inspired techniques are explained briefly. Its simulation findings, which are displayed for two simulated scenarios reveal that hybridization increases multi-robot navigation accuracy in terms of navigation duration and length of the path.