No abstract

A geometrically asymmetric plasmonic sensor for the simultaneous and individual detection of multiple parameters with enhanced specificity and accuracy.

A compact nanosensor that explores the tie-in between stress-induced deformation and optical resonance characteristics is theoretically proposed for pressure sensing. The structure modeling, electromagnetic (EM) wave simulation, and performance evaluations were carried out using the 2D finite element method (FEM). The proposed surface plasmon resonance (SPR) based metal-insulator-metal (MIM) model responds to the pressure induced on the top-facing side of an Ag concave square ring-square disc arrangement (Concave SR-SD) in terms of a structural curve-in into the insulator cavity. These deformations alter the electromagnetic field distributions and plasmonic resonance conditions, shifting the absorption cross-section profiles towards higher wavelengths. The shift in the resonant wavelength (Δλ) for specific measured deformations (d) exhibited by the normal SR-SD hinds at the application level perspective of the designed system in pressure sensing via its optomechanical correlation. Further, multiple parameters like insulator cavity width (W I ) and structure wise modifications in the outer ring structure are investigated for performance optimization, and subline sensitivity values (maximum) of 24.496 nm/MPa and 40.46 nm/MPa are observed from normal and concave SR-SD systems respectively. The suggested nano pressure sensor of suitable sensitivity and broad sensing range promises strong applicability in biomedicine, health monitoring, nanomechanics, chip-based devices, and nanoelectronics.

A highly sensitive yet simple plasmonic refractive index (RI) sensor consisting of Au trimer hollow nanocylinders surrounded by an Ag hollow nanocylinder is proposed with a wide range of applications in the near IR range. The plasmonic behaviour of the structure is studied by analysing the absorption cross-section on illumination by electromagnetic (EM) wave using the finite element method (FEM). Nanoscale detections can be realized by using the shift in resonance wavelength of localized surface plasmon resonance (LSPR) in response to the change in RI. The optimized RI sensor gives a maximum sensitivity of 2545.4 nm/RIU, figure of merit (FOM) of 43.90 RIU−1 and sensor resolution of the order of 10−5 RIU. The proposed sensor can detect even small variations in RI of the order of 10−5 RIU with a sensitivity of 1998 nm/RIU. With the observed high sensitivity, resolution and quality, the sensor can contribute a lot to health-care applications and is found highly suitable for multiple detections covering broad range of RI including bio-analytes, chemicals, and gases.

A Surface plasmon resonance (SPR) based hybrid nanosystem with the competence of single and multiple analytes analysis is demonstrated using a symmetry modified sensory platform for promising application in biosensing. Plasmonic properties of the designed 2×2 matrix system arising from higher-order plasmonic modes generated near groove positions in the structure are analyzed numerically and calibrated for enhanced sensor performance and multi-functionality. The asymmetric defect/ percentage of asymmetry (∆) in the structure incorporated by means of a position-wise shift of Ag nanodisc exhibits pivotal results in performance parameters, including intra channel sensitivity (Sintra), channel separation factor (CHfactor), Figure of merit (FOM) and Q-factor. The pairs of sensing windows of the hybrid structure show a geometric symmetry along the x and -x direction and an asymmetry along its perpendicular (y and -y). Among the symmetric and asymmetric channels, spatially resolved plasmonic modes of asymmetric channels facilitate the multi quantification of analytes in a single stimulation, whereas symmetric ones confirm the presence of the different analytes in the given specimen. With the sensor function flexible to light incidence direction, the matrix system can be effectively employed across medical diagnostics and healthcare monitoring.