Electrospun one-dimensional (1D) nanostructures are rapidly emerging as key enabling components in gas sensing due to their unique electrical, optical, magnetic, thermal, mechanical and chemical properties. 1D nanostructures have found applications in numerous areas, including healthcare, energy storage, biotechnology, environmental monitoring, and defence/security. Their enhanced specific surface area, superior mechanical properties, nanoporosity and improved surface characteristics (in particular, uniformity and stability) have made them important active materials for gas sensing applications. Such highly sensitive and selective elements can be embedded in sensor nodes for internet-of-things applications or in mobile systems for continuous monitoring of air pollutants and greenhouse gases as well as for monitoring the well-being and health in everyday life. Herein, we review recent developments of gas sensors based on electrospun 1D nanostructures in different sensing platforms, including optical, conductometric and acoustic resonators. After explaining the principle of electrospinning, we classify sensors based on the type of materials used as an active sensing layer, including polymers, metal oxide semiconductors, graphene, and their composites or their functionalized forms. The material properties of these electrospun fibers and their sensing performance toward different analytes are explained in detail and correlated to the benefits and limitations for every approach.

No abstract

Porous WO3 nanofibers have been synthesized by electrospinning polyvinylpyrrolidone (PVP) nanofibers embedded with semiconducting WO3 nanoparticles followed by annealing in air and have been tested toward acetone.

No abstract

Micro-manufacturing is one of the growing technologies of near future. Non-traditional machining processes have been found to be beneficial for micro manufacturing using low density of energy for metal removal. To overcome environment related problems of chemical machining, biomachining has been developed over several years by making use of the metabolic activity of microorganisms. Besides many advantages of biomachining such as environmental friendly, low consumption of energy and no heat affected zone generation during machining; one of the common short comings reported by early researchers is a low metal removal rate. In this study, firstly effect of process parameters variation on SMRR and MRR is investigated. Secondly taguchi design of experiment (DOE) approach is used to establish rank of most influential process parameters for maximum metal removal rate. Finally optimal values of selected parameters are predicted and verified. It is observed that process parameters can be optimized to obtain a higher metal removal rate. Micro features are fabricated using optimum process parameters to show the impact of fine tuning on the metal removal rate.

Electric Discharge Machining (EDM) is widely used for manufacturing complex metal parts. The machining parameters like dielectric fluid, electrode material, current, voltage and pulse rate during EDM are controlled to obtain desired Material Removal Rate (MRR) and it also affects the surface morphology of manufactured components. In this research, effect of changing machining parameters, dielectric fluid (distilled water and kerosene) and electrode materials (copper and graphite) on surface morphology of Al 6061 T6 alloy during EDM is investigated. It is observed that the distilled water reacts with the molten aluminum and produces deep pits / voids on the surface due to liberation of hydrogen gas. A micro crack network is seen radiating from the edge of these pits. It is believed that the very high thermal conductivity of distilled water is responsible for the micro crack network and reduced material removal rate when compared with non-reactive kerosene oil.

We report enhanced amperometric sensing response of electrospun tungsten oxide (WO3-x) nanofibers towards acetone with low concentrations (1.2 – 12.5 ppm) at 350 ˚C. Scanning and transmission electron microscopy (SEM...

No abstract