Flexible Plasmonic Sensors

Shir, Daniel; Ballard, Zachary S.; Ozcan, Aydogan

doi:10.1109/jstqe.2015.2507363

Cited by 17 publications

(20 citation statements)

References 67 publications

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“…Among different polymeric substrate, poly (methyl methacrylate) (PMMA), polyethylene terephthalate (PET) and polycarbonate (PC) are commonly used for creating PANTFs. Besides being inexpensive and transparent, these substrates are highly flexible [25]. It was found that depositing thin layers of TiN on PMMA and PET shows similar plasmonic response as that of TiN deposited on SiO 2 /Si [26].…”

Section: Substratesmentioning

confidence: 99%

Plasmonic-Active Nanostructured Thin Films

2020

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Plasmonic-active nanomaterials are of high interest to scientists because of their expanding applications in the field for medicine and energy. Chemical and biological sensors based on plasmonic nanomaterials are well-established and commercially available, but the role of plasmonic nanomaterials on photothermal therapeutics, solar cells, super-resolution imaging, organic synthesis, etc. is still emerging. The effectiveness of the plasmonic materials on these technologies depends on their stability and sensitivity. Preparing plasmonics-active nanostructured thin films (PANTFs) on a solid substrate improves their physical stability. More importantly, the surface plasmons of thin film and that of nanostructures can couple in PANTFs enhancing the sensitivity. A PANTF can be used as a transducer for any of the three plasmonic-based sensing techniques, namely, the propagating surface plasmon, localized surface plasmon resonance, and surface-enhanced Raman spectroscopy-based sensing techniques. Additionally, continuous nanostructured metal films have an advantage for implementing electrical controls such as simultaneous sensing using both plasmonic and electrochemical techniques. Although research and development on PANTFs have been rapidly advancing, very few reviews on synthetic methods have been published. In this review, we provide some fundamental and practical aspects of plasmonics along with the recent advances in PANTFs synthesis, focusing on the advantages and shortcomings of the fabrication techniques. We also provide an overview of different types of PANTFs and their sensitivity for biosensing.

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Section: Substratesmentioning

confidence: 99%

Plasmonic-Active Nanostructured Thin Films

2020

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“…Flexible SERS substrates have potential applications in low-cost embedded and integrated sensors for medical, environmental, and industrial markets [131]. These are mechanically flexible, low-cost, reproducible, and sensitive and can be manufactured using various advanced methods [73,95,96,[132][133][134][135][136][137][138][139][140][141] to have large areas.…”

Section: Flexible Structuresmentioning

confidence: 99%

“…Their plasmonic properties can be tuned by changing shape, size, or morphology of nanostructures and also by mechanically bending, stretching, and twisting. Flexible SERS substrates have been fabricated out of paper and polymers [131]. Electrospinning was used to obtain flexible SERS substrates with 10 9 enhancement by assembling AgNPs on poly(vinyl alcohol) [132].…”

Section: Flexible Structuresmentioning

confidence: 99%

Fundamentals and applications of SERS-based bioanalytical sensing

et al. 2017

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Abstract:Plasmonics is an emerging field that examines the interaction between light and metallic nanostructures at the metal-dielectric interface. Surface-enhanced Raman scattering (SERS) is a powerful analytical technique that uses plasmonics to obtain detailed chemical information of molecules or molecular assemblies adsorbed or attached to nanostructured metallic surfaces. For bioanalytical applications, these surfaces are engineered to optimize for high enhancement factors and molecular specificity. In this review we focus on the fabrication of SERS substrates and their use for bioanalytical applications. We review the fundamental mechanisms of SERS and parameters governing SERS enhancement. We also discuss developments in the field of novel SERS substrates. This includes the use of different materials, sizes, shapes, and architectures to achieve high sensitivity and specificity as well as tunability or flexibility. Different fundamental approaches are discussed, such as label-free and functional assays. In addition, we highlight recent relevant advances for bioanalytical SERS applied to small molecules, proteins, DNA, and biologically relevant nanoparticles. Subsequently, we discuss the importance of data analysis and signal detection schemes to achieve smaller instruments with low cost for SERS-based point-of-care technology developments. Finally, we review the main advantages and challenges of SERS-based biosensing and provide a brief outlook.

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“…8,22–32 This recent and exciting trend now extends the applications of plasmonic sensors beyond laboratory settings for use as wearable sensors or as disposable point-of-care sensors, and also permits their integration into existing medical equipment such as intravenous tubes, syringes, blood bags, bandages, or medical garments. 5,30,33–37 …”

mentioning

confidence: 99%

“…Field portability, low-cost, ease-of-use, and network connectivity are all desired features for ensuring widespread adoption of these sensing systems. 33,38,39 Currently, the most common read-out and quantification scheme for LSPR sensors employs a stable, broad-band light source for illumination and a high resolution optical spectrometer for recording the transmission or reflection spectra. 3,6,40–43 Alternatively, a tunable light source and a single photodiode can be used to obtain the same spectral information.…”

mentioning

confidence: 99%

Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning

et al. 2017

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Plasmonic sensors have been used for a wide-range of biological and chemical sensing applications. Emerging nano-fabrication techniques have enabled these sensors to be cost-effectively mass-manufactured onto various types of substrates. To accompany these advances, major improvements in sensor read-out devices must also be achieved to fully realize the broad impact of plasmonic nano-sensors. Here, we propose a machine learning framework which can be used to design low-cost and mobile multi-spectral plasmonic readers that do not use traditionally employed bulky and expensive stabilized light-sources or high-resolution spectrometers. By training a feature selection model over a large set of fabricated plasmonic nano-sensors, we select the optimal set of illumination light-emitting-diodes needed to create a minimum-error refractive index prediction model, which statistically takes into account the varied spectral responses and fabrication-induced variability of a given sensor design. This computational sensing approach was experimentally validated using a modular mobile plasmonic reader. We tested different plasmonic sensors with hexagonal and square periodicity nano-hole arrays, and revealed that the optimal illumination bands differ from those that are ‘intuitively’ selected based on the spectral features of the sensor, e.g., transmission peaks or valleys. This framework provides a universal tool for the plasmonics community to design low-cost and mobile multi-spectral readers, helping the translation of nano-sensing technologies to various emerging applications such as wearable sensing, personalized medicine, and point-of-care diagnostics. Beyond plasmonics, other types of sensors that operate based on spectral changes can broadly benefit from this approach, including e.g., aptamer-enabled nanoparticle assays and graphene-based sensors, among others.

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Flexible Plasmonic Sensors

Cited by 17 publications

References 67 publications

Plasmonic-Active Nanostructured Thin Films

Plasmonic-Active Nanostructured Thin Films

Fundamentals and applications of SERS-based bioanalytical sensing

Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning

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