Motilal Nehru National Institute of Technology Allahabad

About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.

Fractal characterization and wettability of ion treated silicon surfaces

Abstract: Fractal characterization of surface morphology can be useful as a tool for tailoring the wetting properties of solid surfaces. In this work, rippled surfaces of Si (100) are grown using 200 keV Ar+ ion beam irradiation at different ion doses. Relationship between fractal and wetting properties of these surfaces are explored. The height-height correlation function extracted from atomic force microscopic images, demonstrates an increase in roughness exponent with an increase in ion doses. A steep variation in contact angle values is found for low fractal dimensions. Roughness exponent and fractal dimensions are found correlated with the static water contact angle measurement. It is observed that after a crossover of the roughness exponent, the surface morphology has a rippled structure. Larger values of interface width indicate the larger ripples on the surface. The contact angle of water drops on such surfaces is observed to be lowest. Autocorrelation function is used for the measurement of ripple wavelength.

Influence of graphene’s chemical potential on SPR biosensor using ZnO for DNA hybridization

Abstract: This article presents an SPR biosensor (Structure: SF10 prism-Au-ZnO-Graphene-PBS solution) to sense DNA hybridization using angular interrogation method at an operating wavelength of 633 nm. Its performance parameters, i.e., sensitivity (S), detection accuracy (DA), and figure of merit (FoM) are evaluated for different values of graphene’s chemical potential at room temperature. Sensitivity (141.9 °/RIU), DA (0.64 Degree−1) and FoM (9.14 RIU−1) are achieved for the proposed SPR biosensor at 0 eV chemical potential of graphene at the room temperature. The maximum sensitivity of 156.33°/RIU is obtained for the proposed SPR biosensor at 1.25 eV graphene’s chemical potential. The present article utilizes biocompatibility, chemical stability, and unique electrical and optical properties of both graphene and ZnO in SPR sensor for DNA hybridization.

Optimization of extraction and purification of glucoamylase produced by Aspergillus awamori in solid-state fermentation

Abstract: Various parameters such as solvent selection, concentration, soaking time, and temperature were tested in a single bioreactor in order to determine optimum extraction conditions of glucoamylase, when produced simultaneously with protease by Aspergillus awamari nakazawa MTCC 6652. Optimum conditions were achieved in a 10% glycerol solution soaked for 2 h at 40°C, followed by concentration of extracted glucoamylase (9,157 U/gds) by acetone precipitation (1:2, v/v), which yielded 51.9% recovery. Ion exchange chromatography and gel filtration showed specific activities of 270.5 and 337.5 U/mg, respectively, while SDS-PAGE and zymogram analysis of glucoamylase indicated the presence of three starch-hydrolyzing isoforms with molecular weights of approximately 109.6, 87.1, and 59.4 kDa, respectively

Groundwater System Modeling for Simultaneous Identification of Pollution Sources and Parameters with Uncertainty Characterization

Abstract: Contamination of groundwater poses serious threat to the human health and environment. It is difficult and expensive to clean up contaminated aquifers. Identification of unknown pollution sources is vital for adopting any remediation strategy. Groundwater flow and transport simulation model is used to generate necessary data for Artificial Neural Networks (ANN) model building processes. Breakthrough curves obtained for specified pollution scenario are characterized to reduce the inputs to ANN model. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics, flow parameters and transport parameters are outputs for ANN model. Identification of sources is performed with considerations of three cases—simultaneous estimation of unknown sources and flow parameter; simultaneous estimation of unknown sources, flow and transport parameters; and simultaneous estimation of unknown sources and boundary head. Characterization of uncertainty in source identification due to uncertainty in flow parameter, uncertainty in transport parameter and uncertainty in constant head boundary estimation is performed using fuzzy vertex alpha-cut techniques.