High Performance of a Metal Layer-Assisted Guided-Mode Resonance Biosensor Modulated by Double-Grating

Zhang, Chengrui; Zhou, Yi; Mi, Lan; Ma, Junjun; Wu, Xiang; Fei, Yiyan

doi:10.3390/bios11070221

Cited by 14 publications

(6 citation statements)

References 37 publications

(48 reference statements)

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“…The results section will discuss that despite the absence of sidewall coating, roughness profiles can improve the SPR measurement due to the LSPR. However, many studies on polymer technology [ 45 , 46 , 47 , 48 ] assist in controlling protein fabrication. Saleem et al [ 45 ] and Nuutinen et al [ 46 ] investigate the application of polymeric material on resonant wave gratings (RWG).…”

Section: Methodsmentioning

confidence: 99%

“…Mayet et al [ 47 ] published a similar study in which an oxide-nitride-oxide passivation layer evenly coated the sidewalls of the gratings. Zhang et al [ 48 ] also conducted a theoretical study involving protein sidewall coating on a metal-layer-assisted double-grating (MADG) biosensor. These indicate that the experimental and theoretical information agree well and that the protein coating behavior can be controlled.…”

Section: Methodsmentioning

confidence: 99%

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Sensing Mechanisms of Rough Plasmonic Surfaces for Protein Binding of Surface Plasmon Resonance Detection

Treebupachatsakul

Shinnakerdchoke

Pechprasarn

2023

Sensors

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Surface plasmon resonance (SPR) has been utilized in various optical applications, including biosensors. The SPR-based sensor is a gold standard for protein kinetic measurement due to its ultrasensitivity on the plasmonic metal surface. However, a slight change in the surface morphology, such as roughness or pattern, can significantly impact its performance. This study proposes a theoretical framework to explain sensing mechanisms and quantify sensing performance parameters of angular surface plasmon resonance detection for binding kinetic sensing at different levels of surface roughness. The theoretical investigation utilized two models, a protein layer coating on a rough plasmonic surface with and without sidewall coatings. The two models enable us to separate and quantify the enhancement factors due to the localized surface plasmon polaritons at sharp edges of the rough surfaces and the increased surface area for protein binding due to roughness. The Gaussian random surface technique was employed to create rough metal surfaces. Reflectance spectra and quantitative performance parameters were simulated and quantified using rigorous coupled-wave analysis and Monte Carlo simulation. These parameters include sensitivity, plasmonic dip position, intensity contrast, full width at half maximum, plasmonic angle, and figure of merit. Roughness can significantly impact the intensity measurement of binding kinetics, positively or negatively, depending on the roughness levels. Due to the increased scattering loss, a tradeoff between sensitivity and increased roughness leads to a widened plasmonic reflectance dip. Some roughness profiles can give a negative and enhanced sensitivity without broadening the SPR spectra. We also discuss how the improved sensitivity of rough surfaces is predominantly due to the localized surface wave, not the increased density of the binding domain.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Sensing Mechanisms of Rough Plasmonic Surfaces for Protein Binding of Surface Plasmon Resonance Detection

Treebupachatsakul

Shinnakerdchoke

Pechprasarn

2023

Sensors

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“…Modalities S (nm/RIU) FOM (1/RIU) [31] Silver-shell nanorods with air cores 1200 26.67 [24] 1D grating with deep grating 229. 43 31.52 [32] PR grating coated Au thin film 553 38 [33] Al 2 O 3 gratings/Si/Au/Si 440.295 50.30 [30] Si 3 N 4 grating/glass 375 68 [34] Au nanocubes/SiO 2 /Au 1002.0 417.0 [35] 1D metal grating in dielectric cavity 800 1337 [36] HfO 2 grating/Au/SiO 2 550 1571.4 [37] Si 3 N 4 gratings/SiO 2 266 1662.5 [25] UV curable resin coated TiO 2 233.35 4200 ± 600 [38] TiO 2 grating/glass 657 9112 [1] All-dielectric nano-silt array 300 12,000 [27] Sidewall gratings in dual-slot waveguide 661 12,018 [16] Different dielectric-based GMR 1427. 3 16,457 [39] 1D grating with polymer 63.9 21,300 [28] Stacked resonant compound gratings 401.8 57,404…”

Section: Referencementioning

confidence: 99%

Exploiting Thin-Film Properties and Guided-Mode Resonance for Designing Ultrahigh-Figure-of-Merit Refractive Index Sensors

Cu,

Wu,

Chen

et al. 2024

Sensors

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Guided-mode resonance (GMR) gratings have emerged as a promising sensing technology, with a growing number of applications in diverse fields. This study aimed to identify the optimal design parameters of a simple-to-fabricate and high-performance one-dimensional GMR grating. The structural parameters of the GMR grating were optimized, and a high-refractive-index thin film was simulated on the grating surface, resulting in efficient confinement of the electric field energy within the waveguide. Numerical simulations demonstrated that the optimized GMR grating exhibited remarkable sensitivity (252 nm/RIU) and an extremely narrow full width at half maximum (2 × 10−4 nm), resulting in an ultra-high figure of merit (839,666) at an incident angle of 50°. This performance is several orders of magnitude higher than that of conventional GMR sensors. To broaden the scope of the study and to make it more relevant to practical applications, simulations were also conducted at incident angles of 60° and 70°. This holistic approach sought to develop a comprehensive understanding of the performance of the GMR-based sensor under diverse operational conditions.

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“…GMR sensors have undergone thorough exploration since the late 1980s [15][16][17]. Ongoing research efforts persist in investigating novel designs to enhance sensitivity, quality, or FOM [10,[18][19][20][21][22]. Additionally, GMR sensors continue to find implementation in emerging biosensing applications [23][24][25][26].…”

Section: Design Of the Ggp-gmr Sensormentioning

confidence: 99%

Handheld Biosensor System Based on a Gradient Grating Period Guided-Mode Resonance Device

Chiang,

Tseng,

Tsai

et al. 2023

Biosensors

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Handheld biosensors have attracted substantial attention for numerous applications, including disease diagnosis, drug dosage monitoring, and environmental sensing. This study presents a novel handheld biosensor based on a gradient grating period guided-mode resonance (GGP-GMR) sensor. Unlike conventional GMR sensors, the proposed sensor’s grating period varies along the device length; hence, the resonant wavelength varies linearly along the device length. If a GGP-GMR sensor is illuminated with a narrow band of light at normal incidence, the light resonates and reflects at a specific period but transmits at other periods; this can be observed as a dark band by using a complementary metal oxide semiconductor (CMOS) underneath the sensor. The concentration of a target analyte can be determined by monitoring the shift of this dark band. We designed and fabricated a handheld device incorporating a light-emitting diode (LED) light source, the necessary optics, an optofluidic chip with an embedded GGP-GMR sensor, and a CMOS. LEDs with different beam angles and bandpass filters with different full width at half maximum values were investigated to optimize the dark band quality and improve the accuracy of the subsequent image analysis. Substrate materials with different refractive indices and waveguide thicknesses were also investigated to maximize the GGP-GMR sensor’s figure of merit. Experiments were performed to validate the proposed handheld biosensor, which achieved a limit of detection (LOD) of 1.09 × 10−3 RIU for bulk solution measurement. The sensor’s performance in the multiplexed detection of albumin and creatinine solutions at concentrations of 0–500 μg/mL and 0–10 mg/mL, respectively, was investigated; the corresponding LODs were 0.66 and 0.61 μg/mL.

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High Performance of a Metal Layer-Assisted Guided-Mode Resonance Biosensor Modulated by Double-Grating

Cited by 14 publications

References 37 publications

Sensing Mechanisms of Rough Plasmonic Surfaces for Protein Binding of Surface Plasmon Resonance Detection

Sensing Mechanisms of Rough Plasmonic Surfaces for Protein Binding of Surface Plasmon Resonance Detection

Exploiting Thin-Film Properties and Guided-Mode Resonance for Designing Ultrahigh-Figure-of-Merit Refractive Index Sensors

Handheld Biosensor System Based on a Gradient Grating Period Guided-Mode Resonance Device

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