Indian Institute of Technology Bhubaneswar

About: Indian Institute of Technology Bhubaneswar is a education organization based out in Bhubaneswar, India. It is known for research contribution in the topics: Large Hadron Collider & Higgs boson. The organization has 1185 authors who have published 3132 publications receiving 48832 citations.

On the Performance of Graphene-Based D-Shaped Photonic Crystal Fibre Biosensor Using Surface Plasmon Resonance

Abstract: We propose a D-shaped photonic crystal fibre-based surface plasmon resonance sensor considering graphene on silver for sensing of refractive index of analyte and thickness of biolayer. The different structural and material parameters associated with sensor have been optimised. Graphene not only helps in adsorption of biomolecules due to π-π stacking interaction but at the same time prevents oxidation of metal-like silver. Numerical simulation shows that amplitude sensitivity of the proposed structure for chemical analytes is 216 RIU−1 (refractive index unit) with a resolution of 4.6 × 10−5 RIU while the wavelength sensitivity of the proposed sensor is found to be as high as 3700 nm RIU−1 with resolution of 2.7 × 10−5 RIU. Further, the proposed sensor can also be used for the detection of biolayer thickness in both amplitude and wavelength interrogations. An amplitude sensitivity of 0.26 nm−1 with resolution of 39 pm and wavelength sensitivity of 2 nm nm−1 with resolution of 50 pm is achievable for the determination of biolayer thickness. The proposed structure is easy to use as there is no need of filling of voids, and the analytes can be placed easily on the flat surface of photonic crystal fibre (PCF).

Solving multiobjective problems using cat swarm optimization

Abstract: Highlights? A new multiobjective cat swarm optimization (MOCSO) algorithm is proposed. ? MOCSO is more efficient than MOPSO and NSGA-II. ? This algorithm is tested using benchmark functions. ? Sensitivity analysis of different parameters of MOCSO algorithm is carried out. This paper proposes a new multiobjective evolutionary algorithm (MOEA) by extending the existing cat swarm optimization (CSO). It finds the nondominated solutions along the search process using the concept of Pareto dominance and uses an external archive for storing them. The performance of our proposed approach is demonstrated using standard test functions. A quantitative assessment of the proposed approach and the sensitivity test of different parameters is carried out using several performance metrics. The simulation results reveal that the proposed approach can be a better candidate for solving multiobjective problems (MOPs).

Electron Transfer Directed Antibacterial Properties of Graphene Oxide on Metals.

Abstract: Nanomaterials such as silver nanoparticles and graphene-based composites are known to exhibit biocidal activities. However, interactions with surrounding medium or supporting substrates can significantly influence this activity. Here, it is shown that superior antimicrobial properties of natural shellac-derived graphene oxide (GO) coatings is obtained on metallic films, such as Zn, Ni, Sn, and steel. It is also found that such activities are directly correlated to the electrical conductivity of the GO-metal systems; the higher the conductivity the better is the antibacterial activity. GO-metal substrate interactions serve as an efficient electron sink for the bacterial respiratory pathway, where electrons modify oxygen containing functional groups on GO surfaces to generate reactive oxygen species (ROS). A concerted effect of nonoxidative electron transfer mechanism and consequent ROS mediated oxidative stress to the bacteria result in an enhanced antimicrobial action of naturally derived GO-metal films. The lack of germicidal effect in exposed cells for GO supported on electrically nonconductive substrates such as glass corroborates the above hypothesis. The results can lead to new GO coated antibacterial metal surfaces important for environmental and biomedical applications.