Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/293586
Title: | Ultra Sensitive Nano Structured Plasmonic Devices for Sensing Bio Functional Applications |
Researcher: | Sharma, Divya |
Guide(s): | Dwivedi, Ram Prakash |
Keywords: | Engineering Engineering and Technology Engineering Electrical and Electronic |
University: | Shoolini University of Biotechnology and Management Sciences |
Completed Date: | 2020 |
Abstract: | newline xvi newlineABSTRACT newlineThe manipulation of light at the nanoscale is achieved by the potentiality possessed by the noble metal nanostructures. This has led to the technology which is a bridging link between the nanoelectronics and microphotonics, termed as Plasmonics. The ongoing pursuit to scale down the electronics and photonics has witnessed many challenges to cater the high-speed data transportation and Plasmonics serves as the platform to overcome the restraints faced by Photonics and Electronics. It holds the advantage of working over the diffraction limit for the localization of light into the subwavelength dimensions. The ease of nanofabrication techniques like e-beam lithography, ion beam milling etc. and characterization facilities like near field microscopy has paved the way for the development of nano-plasmonic devices like nano-antennas, plasmonic solar cells. The applications of Plasmonic are widespread in the area of medicine, environment, high-speed data communication, defense, etc. newlineThis dissertation work emphasizes the field of Plasmonic biosensor, targeting the immunodiagnostics. The surface plasmon resonance (SPR) phenomenon have been extensively used by the Optical biosensors from a long time to study the biomolecular kinetics. They possess the capability to deliver high sensitivity and analysis of cellular data in the real time environment without the need for expensive fluorescent labelling but the complex circuitry like SPR prism coupling geometry of these biosensors makes them bulky and creates hassles for scaling up its throughput. Also, the integration of such biosensors with other technologies like microfluidics is a dauting task, preventing the portability which is a pre-requisite for the point-of-care-diagnostics. Currently, the medical diagnostics is a very laborious and expensive process and to cater the rural health care, it is very difficult because of the high-end use of optical instrumentation. So, a customize Plasmonic biosensor device is proposed to address the needs of the people in a long run. newlineThe research starts with the investigation of current solutions available for the medical diagnostics and their limitations. In the process of investigation, other emerging areas of Plasmonics are studied for cost effective label-free diagnostics. The complete end to end design and development takes into account the underlying principles of Plasmonics and its properties are being explored thoroughly. The newlinexvii newlinecomplete understanding of the cancer diagnostics and detection specifically AML CD33 is understood to finalize the focus of research application in Plasmonics. newlineTo reduce the cost of development all the simulation of structural and behavioral were carried using the MEEP open source software and also different FSM model were explored to reduce the designing complexity apart from the FDTD method. A customized biosensor device model was fabricated after investigating several design models using different approaches like transmission loss, Signal-to-Noise Ratio, Intensity mean of the Image. The biosensor chip is tested using the AML biomarker CD33 and applying Dark field imaging approach, the quantification is done using intensity mean calculation which provides as an approach to identify antigen and antibody reaction. newlineThe custom BioVisionPC Suite is developed, which supports the AI based on ANN engine along with image transformation operations to remove the noise in the training images. Here the dark field imaging-based intensity images are used as the data point to train the AI based ANN engine and classification of AML biomarker CD33. Along with the BioVisionPC suite, the android based BioVisionSuite reporter app is developed to patients to access the diagnostic reports remotely. |
Pagination: | 225p., |
URI: | http://hdl.handle.net/10603/293586 |
Appears in Departments: | Faculty of Engineering and Technology |
Files in This Item:
File | Description | Size | Format | |
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001 front page.pdf | Attached File | 73.81 kB | Adobe PDF | View/Open |
002 certificates.pdf | 127.05 kB | Adobe PDF | View/Open | |
003 table of contents.pdf | 107.01 kB | Adobe PDF | View/Open | |
004 acknowledgement.pdf | 71.91 kB | Adobe PDF | View/Open | |
005 abbriviations.pdf | 127.3 kB | Adobe PDF | View/Open | |
006 list of tables.pdf | 10.73 kB | Adobe PDF | View/Open | |
007 list of figurees.pdf | 116.46 kB | Adobe PDF | View/Open | |
008 abstract.pdf | 14.86 kB | Adobe PDF | View/Open | |
009 introduction.pdf | 713.12 kB | Adobe PDF | View/Open | |
010 literature review.pdf | 580.69 kB | Adobe PDF | View/Open | |
011 methodlogy.pdf | 2.02 MB | Adobe PDF | View/Open | |
012 results and discussion.pdf | 3.91 MB | Adobe PDF | View/Open | |
013 summary and conclusion.pdf | 73.76 kB | Adobe PDF | View/Open | |
014 future recommendations.pdf | 69.72 kB | Adobe PDF | View/Open | |
015 refrences.pdf | 294.76 kB | Adobe PDF | View/Open | |
016 appendix.pdf | 1.24 MB | Adobe PDF | View/Open | |
017 patent and publications.pdf | 92.81 kB | Adobe PDF | View/Open | |
018 patent letter.pdf | 90.07 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 11.44 kB | Adobe PDF | View/Open |
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