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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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 |
work_keys_str_mv |
AT vishaldesai intermediatefrequencyacsignalanalysisforbionanosensor AT srisowmyasanisetty intermediatefrequencyacsignalanalysisforbionanosensor AT benjaminsteber intermediatefrequencyacsignalanalysisforbionanosensor AT evasapi intermediatefrequencyacsignalanalysisforbionanosensor AT bouzidaliane intermediatefrequencyacsignalanalysisforbionanosensor AT saionsinha intermediatefrequencyacsignalanalysisforbionanosensor AT prabirpatra intermediatefrequencyacsignalanalysisforbionanosensor |
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1725496187000193024 |