Optical Fiber-based Sensing Method for Nanoparticles Detection through Back-Scattering Signal Analysis

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Joana Isabel Paiva (Author) Other; R. S. R. Ribeiro (Author) Other; Pedro Jorge (Author) FCUP; Carla Rosa (Author) FCUP; P. Sampaio (Author) Other; João Cunha (Author) FEUP

Conference proceedings International

Title: OPTICAL FIBERS AND SENSORS FOR MEDICAL DIAGNOSTICS AND TREATMENT APPLICATIONS XIX

Conference on Optical Fibers and Sensors for Medical Diagnostics and Treatment Applications XIX

San Francisco, CA, FEB 02-03, 2019

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Authenticus ID: P-00Q-GY4

DOI: 10.1117/12.2505728

Abstract (EN): In view of the growing importance of nanotechnologies, the detection of nanoparticles type in several contexts has been considered a relevant topic. Several organisms, including the National Institutes of Health, have been highlighting the urge of developing nanoparticles exposure risk assessment assays, since very little is known about their physiological responses. Although the identi fi cation/characterization of synthetically produced nanoparticles is considered a priority, there are many examples of \ naturally" generated nanostructures that provide useful information about food components or human physiology. In fact, several nanoscale extracellular vesicles are present in physiological fluids with high potential as cancer biomarkers. However, scientists have struggled to fi nd a simple and rapid method to accurately detect/identify nanoparticles, since their majority have diameters between 100-150 nm -far below the di ff raction limit. Currently, there is a lack of instruments for nanoparticles detection and the few instrumentation that is commonly used is costly, bulky, complex and time consuming. Thus, considering our recent studies on particles identi fi cation through back-scattering, we examined if the time/frequency-domain features of the back-scattered signal provided from a 100 nm polystyrene nanoparticles suspension are able to detect their presence only by dipping a polymeric lensed optical fi ber in the solution. This novel technique allowed the detection of synthetic nanoparticles in distilled water versus \ blank solutions" (only distilled water) through Multivariate Statistics and Arti fi cial Intelligence (AI)-based techniques. While the state-of-the-art methods do not o ff er a ff ordable and simple approaches for nanoparticles detection, our technique can contribute for the development of a device with innovative characteristics.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15