東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Nanotube Spectral Fingerprinting and...

Nadeem, Aceer,

Linked to FindBook

Google Book

Amazon

博客來

Nanotube Spectral Fingerprinting and Machine Learning for Optimized Bioimaging/Sensing Applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nanotube Spectral Fingerprinting and Machine Learning for Optimized Bioimaging/Sensing Applications // Aceer Nadeem.
Author:	Nadeem, Aceer,
Description:	1 electronic resource (249 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
Contained By:	Dissertations Abstracts International86-07B.
Subject:	Chemical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31637565
ISBN:	9798302164155

Nanotube Spectral Fingerprinting and Machine Learning for Optimized Bioimaging/Sensing Applications /
Nadeem, Aceer,

Nanotube Spectral Fingerprinting and Machine Learning for Optimized Bioimaging/Sensing Applications /Aceer Nadeem. - 1 electronic resource (249 pages)

Source: Dissertations Abstracts International, Volume: 86-07, Section: B.

This thesis presents a multifaceted exploration of the optimization and application of single-walled carbon nanotubes (SWCNTs) in biomedical contexts, with a specific focus on enhancing their stability, functionality, and use as optical biosensors. The research spans several key areas, including the development of innovative techniques that couple machine learning with spectral fingerprinting for advanced diagnostics, the investigation of SWCNT chirality and its implications for cellular interactions, and the optimization of lyophilization processes to improve long-term stability and reproducibility.The first section of the thesis delves into the fundamental properties of SWCNTs, emphasizing their unique electronic and optical characteristics. These properties, largely dictated by the chiral indices of the nanotubes, make SWCNTs particularly suitable for biosensing and imaging applications. The research highlights the critical role that chirality plays in determining the optical behavior of SWCNTs and how this can be exploited to design advanced biosensors capable of multiplexed imaging and precise biomarker detection.A significant portion of the research is devoted to understanding how chiral pure SWCNT species interact with cells compared to multi-chiral samples. This study was motivated by the widespread use of chiral pure species in biosensor applications, despite a limited understanding of their behavior relative to multi-chiral mixtures. The findings revealed that chiral pure SWCNTs exhibit a higher rate of exocytosis and produce significantly brighter and more stable intracellular fluorescence. These insights underscore the potential for advancing biosensor technologies through the adoption of chiral pure SWCNT-based platforms, which could lead to more sensitive and reliable diagnostic tools.The thesis also introduces a novel approach that integrates machine learning with near-infrared spectral fingerprinting of SWCNTs to accurately identify different macrophage phenotypes. This method not only achieved highly accurate phenotypical identification but also demonstrated performance comparable to traditional techniques. The success of this technique highlights its potential to revolutionize early disease diagnostics by offering a powerful tool for real-time monitoring, personalized medicine, and more efficient healthcare delivery.In addressing the challenge of SWCNT stability during storage, the research developed an optimized lyophilization protocol combined with the strategic use of cryoprotectants. This protocol effectively preserved the optical properties and prevented aggregation of DNA-functionalized SWCNTs over extended periods, even at room temperature. The study identified glucose and polyethylene glycol (PEG) as the most effective cryoprotectants, with an 80:20 ratio of glucose to PEG providing the best long-term stability and performance. These advancements are particularly significant for the practical deployment of SWCNT-based sensors in clinical and research settings, where consistency and reliability are crucial.

English

ISBN: 9798302164155Subjects--Topical Terms:

560457
Chemical engineering.
Subjects--Index Terms:

Biosensors

Nanotube Spectral Fingerprinting and Machine Learning for Optimized Bioimaging/Sensing Applications /
LDR:04596nmm a22004453i 4500 001 2428803
005 20250414022030.5
006 m o d
007 cr|nu||||||||
008 261011s2024 miu||||||m |||||||eng d
020 $a 9798302164155
035 $a (MiAaPQD)AAI31637565
035 $a AAI31637565
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Nadeem, Aceer, $e author. $3 3816245
245 1 0 $a Nanotube Spectral Fingerprinting and Machine Learning for Optimized Bioimaging/Sensing Applications / $c Aceer Nadeem.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (249 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
500 $a Advisors: Roxbury, Daniel Committee members: Meenach, Samantha; Reshetnyak, Yana K.
502 $b Ph.D. $c University of Rhode Island $d 2024.
520 $a This thesis presents a multifaceted exploration of the optimization and application of single-walled carbon nanotubes (SWCNTs) in biomedical contexts, with a specific focus on enhancing their stability, functionality, and use as optical biosensors. The research spans several key areas, including the development of innovative techniques that couple machine learning with spectral fingerprinting for advanced diagnostics, the investigation of SWCNT chirality and its implications for cellular interactions, and the optimization of lyophilization processes to improve long-term stability and reproducibility.The first section of the thesis delves into the fundamental properties of SWCNTs, emphasizing their unique electronic and optical characteristics. These properties, largely dictated by the chiral indices of the nanotubes, make SWCNTs particularly suitable for biosensing and imaging applications. The research highlights the critical role that chirality plays in determining the optical behavior of SWCNTs and how this can be exploited to design advanced biosensors capable of multiplexed imaging and precise biomarker detection.A significant portion of the research is devoted to understanding how chiral pure SWCNT species interact with cells compared to multi-chiral samples. This study was motivated by the widespread use of chiral pure species in biosensor applications, despite a limited understanding of their behavior relative to multi-chiral mixtures. The findings revealed that chiral pure SWCNTs exhibit a higher rate of exocytosis and produce significantly brighter and more stable intracellular fluorescence. These insights underscore the potential for advancing biosensor technologies through the adoption of chiral pure SWCNT-based platforms, which could lead to more sensitive and reliable diagnostic tools.The thesis also introduces a novel approach that integrates machine learning with near-infrared spectral fingerprinting of SWCNTs to accurately identify different macrophage phenotypes. This method not only achieved highly accurate phenotypical identification but also demonstrated performance comparable to traditional techniques. The success of this technique highlights its potential to revolutionize early disease diagnostics by offering a powerful tool for real-time monitoring, personalized medicine, and more efficient healthcare delivery.In addressing the challenge of SWCNT stability during storage, the research developed an optimized lyophilization protocol combined with the strategic use of cryoprotectants. This protocol effectively preserved the optical properties and prevented aggregation of DNA-functionalized SWCNTs over extended periods, even at room temperature. The study identified glucose and polyethylene glycol (PEG) as the most effective cryoprotectants, with an 80:20 ratio of glucose to PEG providing the best long-term stability and performance. These advancements are particularly significant for the practical deployment of SWCNT-based sensors in clinical and research settings, where consistency and reliability are crucial.
546 $a English
590 $a School code: 0186
650 4 $a Chemical engineering. $3 560457
650 4 $a Nanotechnology. $3 526235
650 4 $a Nanoscience. $3 587832
653 $a Biosensors
653 $a Confocal Raman microscopy
653 $a Cytotoxicity
653 $a Near infrared fluorescence
653 $a Single Walled Carbon Nanotubes
653 $a Stability
690 $a 0542
690 $a 0652
690 $a 0565
710 2 $a University of Rhode Island. $b Chemical Engineering. $e degree granting institution. $3 3816246
720 1 $a Roxbury, Daniel $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-07B.
790 $a 0186
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31637565