University:
Boston University
Course:
SAR HP 151 | Introduction to Health Professions
Academic year:

2024
Views:

393

Pages:

14
Author:

gotejatsgrr7

Experimental Results Active delivery in plasmonic sensors -Sensitivity reaches 610 nm/RIU ! -14-fold improvement in analyte delivery kinetics Yanik et. al, Appl. Phys. Lett . 2010 (cover of 11 January 2010) Experimental Results Bulk measurement with photonic crystal - Sensitivity reaches 510 nm/RIU Huang et. al, Optics Express 2009 Multi-Layered Plasmonic Structures 1. Multi-Layered nanohole arrays Valentine et. al. Nature (2008) Resulting in metamaterials 2. Multi-Layered nanoparticle arrays 3. Multi-Layered hybrid structures Multi-layered Plasmonic NanoStructures Studied multi-layered structures Demonstrated for the first time EOT in multi-layer structures i) Through Fabry-Perot Resonances ii) Through grating based SPP resonance Artar et. al, Appl. Phys. Lett. 2009 (top 10 downloaded APL paper in August 2009) Enhancing Sensitivity  We show Fabry-Perot resonances offer superior field-media Resulting in much higher sensitivity to refractive index changes Introduced a simple cavity model to account the behavior of the resonances λFP = 2hneff h: spacing between layers neff : effective index As predicted: i) Increasing spacing red-shifts FP mode ii) Decreasing diameter increases effective index, thus red-shifts FP mode  while none effects SPPs Ultra-sensitive Vibration Spectroscopy Vibrational *Fingerprint* Signatures of Proteins ANTENNA ARRAY nanorod Adato and Yanik et. al, PNAS 2009 (highlighted on the cover of NSF) 500nm Water Contamination Detection and Identification using UV Intrinsic Fluorescence UV LED based Microbial Contamination Detection and Identification – Contamination in waterways is becoming increasingly significant around the world as populations grow rapidly – ~ 20 million people become ill yearly from drinking water containing bacteria and other pathogens often spread by untreated waste – Example Hudson River, during wet weather, six communities discharge raw sewage and bacteria from almost 100 individual Combined Sewer Overflows (CSO) CSO – Need to quantify large areas Treatment Plant Troy Troy Cohoes Albany Watervilet Rensselaer Green Island UV LED based Microbial Contamination Detection and Identification  UV LEDs provide compact field deployment monitoring systems using intrinsic fluorescence within the cell for identification and quantification  Fluorescence advantages – High sensitivity – Short collection time – In situ measurement (no sample contact) – Reagentless (no consumables) – Monitoring of large areas/volumes continuously  Solid state light source enables switch between modes of quantification (alarm system) and identification UV LED based Microbial Contamination Detection and Identification  Quantification: Concentration of bacteria vs. Fluorescence Intensity for Tryptophan (280 nm) and NADH (340 nm) native fluorophores 280nmLED_Photon Counting PMT E-coli dilutions 340nm LED_ Photon Counting PMT E-coli dilutions 120,000 10000 9000 100,000 8000 7000 Counts Counts 80,000 60,000 6000 5000 4000 3000 40,000 2000 20,000 1000 0 0 0 0 2 4 6 8 Dilutions (1 to 2) 10 12 2 4 6 8 10 Dilutions (1 to 2) E-coli diluted samples measured in a quartz cuvette with path length of 3 mm by 280 and 340 nm UV LEDs and PMT photon counting module. A 340 nm band pass and 400 nm long pass emission filter was placed in front of the PMT for the 280 nm and 340 nm excitation repectively. UV LED based Microbial Contamination Detection and Identification  Proof of concept: Identification on traditional system  Differentiate both species and strain of bacteria using PCA  Preliminary Computer program based on PCA – Fluorescence spectra from 280, 340, and 440 nm excitation – Small differences in spectra for each bacteria are amplified Differentiation: Three strains of E-coli Differentiation: Two strains of E-coli and Enterobacter aerogenes Biological Detection with Nanoparticle Based Detectors  Intrinsic fluorescence for identification and quantification requires high UV wavelength response (responsivity)  Traditional detectors such as PMTs and Silicon Photodiodes are limited by: – Broad spectrum of detection (requires filters) – Low UV responsivity – Non-ideal for field deployment of small sensors  Demonstrate a large area, wavelength selective UV photodetector for intrinsic fluorescence biological system  Bandpass response can be tuned by the substrate and nanoparticle material properties Biological Detection with Nanoparticle Based Detectors Biological Detection with Nanoparticle Based Detectors