Intermediate Frequency AC Signal Analysis for Bionanosensor

Nanobiosensors are devices which incorporate nanomaterials to detect miniscule quantities of biological and chemical agents. The authors have already developed a novel bionanosensor (BNS) for quick, efficient, and precise detection of bacterial pathogens using the principles of CNT-DNA interaction a...

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Main Authors: Vishal Desai, Srisowmya Sanisetty, Benjamin Steber, Eva Sapi, Bouzid Aliane, Saion Sinha, Prabir Patra
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Journal of Nanotechnology
Online Access:http://dx.doi.org/10.1155/2011/617196
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spelling doaj-5bc70b69e1fe4fe58dd27fe05f2c15cf2020-11-24T23:45:21ZengHindawi LimitedJournal of Nanotechnology1687-95031687-95112011-01-01201110.1155/2011/617196617196Intermediate Frequency AC Signal Analysis for BionanosensorVishal Desai0Srisowmya Sanisetty1Benjamin Steber2Eva Sapi3Bouzid Aliane4Saion Sinha5Prabir Patra6Department of Electrical and Computer Engineering, University of New Haven, 300 Boston Post Road, West Haven, CT 06516, USADepartment of Biology and Environmental Science, University of New Haven, 300 Boston Post Road, West Haven, CT 06516, USADepartment of Biology and Environmental Science, University of New Haven, 300 Boston Post Road, West Haven, CT 06516, USADepartment of Biology and Environmental Science, University of New Haven, 300 Boston Post Road, West Haven, CT 06516, USADepartment of Electrical and Computer Engineering, University of New Haven, 300 Boston Post Road, West Haven, CT 06516, USADepartment of Physics, University of New Haven, 300 Boston Post Road, West Haven, CT 06516, USADepartment of Biomedical Engineering, University of Bridgeport, 126 Park Avenue, Bridgeport, CT 06604, USANanobiosensors are devices which incorporate nanomaterials to detect miniscule quantities of biological and chemical agents. The authors have already developed a novel bionanosensor (BNS) for quick, efficient, and precise detection of bacterial pathogens using the principles of CNT-DNA interaction and DNA hybridization. The detection ability of the (BNS) was observed to be independent of the device resistance. Two new methods (low-pass filter (LPF) and curve fitting (CF)) were developed for better analysis of the BNS. These methods successfully model the BNS. Evidence is provided to elucidate the success of the model, which can explain the DNA hybridization on the sensor surface. These models successfully demonstrated the detection of DNA hybridization versus nonhybridization. Thus, the models can not only help in better and efficient design and operation of the BNS, but can also be used to analyze other similar nanoscale devices.http://dx.doi.org/10.1155/2011/617196
collection DOAJ
language English
format Article
sources DOAJ
author Vishal Desai
Srisowmya Sanisetty
Benjamin Steber
Eva Sapi
Bouzid Aliane
Saion Sinha
Prabir Patra
spellingShingle Vishal Desai
Srisowmya Sanisetty
Benjamin Steber
Eva Sapi
Bouzid Aliane
Saion Sinha
Prabir Patra
Intermediate Frequency AC Signal Analysis for Bionanosensor
Journal of Nanotechnology
author_facet Vishal Desai
Srisowmya Sanisetty
Benjamin Steber
Eva Sapi
Bouzid Aliane
Saion Sinha
Prabir Patra
author_sort Vishal Desai
title Intermediate Frequency AC Signal Analysis for Bionanosensor
title_short Intermediate Frequency AC Signal Analysis for Bionanosensor
title_full Intermediate Frequency AC Signal Analysis for Bionanosensor
title_fullStr Intermediate Frequency AC Signal Analysis for Bionanosensor
title_full_unstemmed Intermediate Frequency AC Signal Analysis for Bionanosensor
title_sort intermediate frequency ac signal analysis for bionanosensor
publisher Hindawi Limited
series Journal of Nanotechnology
issn 1687-9503
1687-9511
publishDate 2011-01-01
description Nanobiosensors are devices which incorporate nanomaterials to detect miniscule quantities of biological and chemical agents. The authors have already developed a novel bionanosensor (BNS) for quick, efficient, and precise detection of bacterial pathogens using the principles of CNT-DNA interaction and DNA hybridization. The detection ability of the (BNS) was observed to be independent of the device resistance. Two new methods (low-pass filter (LPF) and curve fitting (CF)) were developed for better analysis of the BNS. These methods successfully model the BNS. Evidence is provided to elucidate the success of the model, which can explain the DNA hybridization on the sensor surface. These models successfully demonstrated the detection of DNA hybridization versus nonhybridization. Thus, the models can not only help in better and efficient design and operation of the BNS, but can also be used to analyze other similar nanoscale devices.
url http://dx.doi.org/10.1155/2011/617196
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