Optical biosensor based on enhanced surface plasmon resonance: theoretical optimization

Meradi, K. A.; Tayeboun, Fatima; Guerinik, Amine; Zaky, Zaky A.; Aly, Arafa H.

doi:10.1007/s11082-021-03504-8

Cited by 40 publications

(14 citation statements)

References 61 publications

(52 reference statements)

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“…The Helmholtz equation investigates the propagation of the acoustic wave within the proposed sensor structure as 2 : where c L is the longitudinal speed of the acoustic wave through the tub, and P is the acoustic pressure. TMM is a standard method for studying the transmission and reflection of the incident acoustic and optic waves with multitube structures [29][30][31][32][33][34] . The following matrix describes the interplay between the proposed system and acoustic waves.…”

Section: Basic Equations and Model Designmentioning

confidence: 99%

Simulation study of gas sensor using periodic phononic crystal tubes to detect hazardous greenhouse gases

Zaky

Alamri

Zohny

et al. 2022

Sci Rep

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Here, we investigate a gas sensor model based on phononic crystals of alternating tubes using the transfer matrix method to detect hazardous greenhouse gases. The effect of the thicknesses and cross-sections of all tubes on the performance of the proposed sensor is studied. The results show that longitudinal acoustic speed is a pivotal parameter rather than the mass density variations of the gas samples on the position of the resonant peaks due to its significant impact on the propagation of the acoustic wave. The suggested sensor can be considered very simple and low-cost because it does not need a complicated process to deposit multilayers of different mechanical properties’ materials.

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Section: Basic Equations and Model Designmentioning

confidence: 99%

Simulation study of gas sensor using periodic phononic crystal tubes to detect hazardous greenhouse gases

Zaky

Alamri

Zohny

et al. 2022

Sci Rep

Self Cite

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show abstract

“…A good example is plasmonic-resonance-based technologies, where the interaction of light with metallic nanocoating is used to detect slight variations of refractive index at the interface between the metal and the surrounding media. [101,102] Metasurface-based optical resonance has also been employed to detect cancer biomarkers in microfluidic chips, [103] e.g., using functionalized silicon nanopost metasurfaces to target cancer-derived molecules. The resonance that results from the interaction between light and the functionalized nanostructures experiences a detectable shift in wavelength when biomarkers bind to the functionalization moieties, since the refractive index increases.…”

Section: Interfacing Photonics With Microfluidic Chips-optofluidicsmentioning

confidence: 99%

Shining a Light on Cancer—Photonics in Microfluidic Tumor Modeling and Biosensing

Guimarães

Cruz‐Moreira

Caballero

et al. 2022

Adv Healthcare Materials

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Microfluidic platforms represent a powerful approach to miniaturizing important characteristics of cancers, improving in vitro testing by increasing physiological relevance. Different tools can manipulate cells and materials at the microscale, but few offer the efficiency and versatility of light and optical technologies. Moreover, light‐driven technologies englobe a broad toolbox for quantifying critical biological phenomena. Herein, the role of photonics in microfluidic 3D cancer modeling and biosensing from three major perspectives is reviewed. First, optical‐driven technologies are looked upon, as these allow biomaterials and living cells to be manipulated with microsized precision and present opportunities to advance 3D microfluidic models by engineering cancer microenvironments' hallmarks, such as their architecture, cellular complexity, and vascularization. Second, the growing field of optofluidics is discussed, exploring how optical tools can directly interface microfluidic chips, enabling the extraction of relevant biological data, from single fluorescent signals to the complete 3D imaging of diseased cells within microchannels. Third, advances in optical cancer biosensing are reviewed, focusing on how light–matter interactions can detect biomarkers, rare circulating tumor cells, and cell‐derived structures such as exosomes. Photonic technologies' current challenges and caveats in microfluidic 3D cancer models are overviewed, outlining future research avenues that may catapult the field.

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“…SPR technology has been utilized to produce biosensors for a variety of uses, including plasmonic detectors, optical polarization encoding, sensing technologies, and bio-photonic sensors [ 17 ]. SPR has been employed in several biosensor applications because it is highly sensitive to the refractive index of materials nearby [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

et al. 2022

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The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.

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Optical biosensor based on enhanced surface plasmon resonance: theoretical optimization

Cited by 40 publications

References 61 publications

Simulation study of gas sensor using periodic phononic crystal tubes to detect hazardous greenhouse gases

Simulation study of gas sensor using periodic phononic crystal tubes to detect hazardous greenhouse gases

Shining a Light on Cancer—Photonics in Microfluidic Tumor Modeling and Biosensing

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

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