Electromagnetic surface waves have revolutionized label-free optical sensing due to their extreme sensitivity to refractive index (RI) variations at propagation interfaces. Among these, Bloch-like surface waves (BLSWs) excited in side-polished photonic crystal fibers offer a superior alternative to traditional surface plasmon resonance by providing higher figures of merit (FOM) and narrower resonance peaks.
This work proposes a novel multi-nanostrip configuration on a D-shaped PCF to optimize sensor sensitivity by analyzing the interactions of multiple TiO2 nanostrips as a function of the spatial gap between them. The spatial gap between multiple TiO2 nanostrips can act as a high-intensity focal point for the electric field. By confining the BLSW mode within these narrow regions, where the external medium is located, a stronger light-matter interaction is achieved compared to single-strip designs. This field confinement enables the detection of refractive index (RI) variations within extremely small analyte volumes, enhancing diagnostic precision in confined or complex environments.
This study employs the finite element method and eigenmode expansion to analyze how sensitivity and the figure of merit (FOM) vary as functions of the number of strips and the spacing between them (GAP). This computational analysis identifies the optimal geometry that balances sensitivity and FOM, ensuring a robust sensing configuration for real-world applications such as industrial monitoring and biological or chemical diagnostics. This advancement in nanosensor design represents a key step toward high-precision sensing technologies for non-destructive diagnostics.
The computational analysis reveals that a configuration of three 10 μm nanostrips with a 0.1 μm GAP enhances sensitivity by 17% compared to single-strip benchmarks, achieving a peak FOM of 2400 RIU-1. These results demonstrate the sensor’s capacity to detect minute RI shifts in industrial lubricants. This provides a robust NDT tool for monitoring metallic wear particles, water contamination, or thermal degradation in high-precision machinery.
