Plasmon optical trapping using silicon nitride trench waveguides

Zhao, Qiancheng; Guclu, Caner; Huang, Yuewang; Capolino, Filippo; Ragan, Regina; Boyraz, Özdal

doi:10.1364/josab.33.001182

Cited by 8 publications

(2 citation statements)

References 37 publications

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“…This work uses SERS as the gas sensor in an odor compass and paves the way for its use in passive Internet of things devices and mobile odor compasses. We envision integrating this strategy with newly emerging waveguide excitation of SERS sensors for device miniaturization and continuous monitoring. , This approach will greatly benefit from the transfer learning methodology introduced in this work, which enables accurate models to be trained quickly. These devices promise to make a material impact on people’s health by identifying and locating toxic gases and VOCs produced by indoor pathogens.…”

Section: Discussionmentioning

confidence: 99%

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

et al. 2019

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Olfaction is important for identifying and avoiding toxic substances in living systems. Many efforts have been made to realize artificial olfaction systems that reflect the capacity of biological systems. A sophisticated example of an artificial olfaction device is the odor compass which uses chemical sensor data to identify odor source direction. Successful odor compass designs often rely on plume-based detection and mobile robots, where active, mechanical motion of the sensor platform is employed. Passive, diffusion-based odor compasses remain elusive as detection of low analyte concentrations and quantification of small concentration gradients from within the sensor platform are necessary. Further, simultaneously identifying multiple odor sources using an odor compass remains an ongoing challenge, especially for similar analytes. Here, we show that surface-enhanced Raman scattering (SERS) sensors overcome these challenges, and we present the first SERS odor compass. Using a grid array of SERS sensors, machine learning analysis enables reliable identification of multiple odor sources arising from diffusion of analytes from one or two localized sources. Specifically, convolutional neural network and support vector machine classifier models achieve over 90% accuracy for a multiple odor source problem. This system is then used to identify the location of an Escherichia coli biofilm via its complex signature of volatile organic compounds. Thus, the fabricated SERS chemical sensors have the needed limit of detection and quantification for diffusion-based odor compasses. Solving the multiple odor source problem with a passive platform opens a path toward an Internet of things approach to monitor toxic gases and indoor pathogens.

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Section: Discussionmentioning

confidence: 99%

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

et al. 2019

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“…10 High localization is accompanied by strong amplification of evanescent electromagnetic fields. Such functionality makes surface waves relevant for many applications from subwavelength focusing, 11,12 imaging 13,14 and high-resolution lithography 15 to onchip signal processing, [16][17][18] non-linear optics, sensing, high-performance absorbers, 19,20 , photovoltaics, 21 optical trapping 22,23 and manipulation. 24,25 For sensing and spectroscopy applications is often needed to modify the emission rate (enhance or inhibit) of emitters (quantum dots, single atoms or molecules, NVcenters etc) placed in the vicinity of a substrate.…”

Section: Introductionmentioning

confidence: 99%

Tamm-Langmuir surface waves

2016

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In this work we develop a theory of surface electromagnetic waves localized at the interface of periodic metal-dielectric structures. We have shown that the anisotropy of plasma frequency in metal layers lifts the degeneracy of plasma oscillations and opens a series of photonic band gaps. This results in appearance of surface waves with singular density of states -we refer to them as Tamm-Langmuir waves. Such naming is natural since we have found that their properties are very similar to the properties of both bulk Langmuir and surface Tamm waves. Depending on the anisotropy parameters, Tamm-Langmuir waves can be either forward or backward waves. Singular density of states and high sensitivity of the dispersion to the anisotropy of the structure makes Tamm-Langmuir waves very promising for potential applications in nanophotonics and biosensing.

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Optical trapping-assisted SERS platform for chemical and biosensing applications: Design perspectives

Yua

Lin

et al. 2017

Coordination Chemistry Reviews

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Plasmon optical trapping using silicon nitride trench waveguides

Cited by 8 publications

References 37 publications

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

Tamm-Langmuir surface waves

Optical trapping-assisted SERS platform for chemical and biosensing applications: Design perspectives

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