Since surface acoustic waves (SAWs) are often generated on substrates to which nanostrips are periodically attached, it is very important to consider the effect of an interface between the deposited strip and the substrate surface, which is an unavoidable issue in manufacturing. In this article, we propose a theoretical model that takes into account interface damping and calculate the dispersion relationships both for frequency and for attenuation of SAW resonance. These results show that the interface damping has an insignificant effect on resonance frequency; but, interestingly, attenuation of the SAW can decrease significantly in the high-frequency region as the interface damping increases. Using picosecond ultrasound spectroscopy, we confirm the validity of our theory; the experimental results show similar trends both for resonant frequency and attenuation in the SAW resonance. Furthermore, the resonant behavior of the SAW is simulated using the finite element method, and the intrinsic cause of interface damping on the vibrating system is discussed. These findings strongly indicate the necessity of considering interfacial damping in the design of SAW devices.

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We propose a high sensitivity biosensor based on a GHz phononic crystal (PnC) waveguide, and demonstrate its operation by numerical simulations. The geometry consists of a micron-scale freestanding PnC silica waveguide plate with embedded Au nanopillars for bioparticle attachment, the PnC plate lying between two groups of periodic metal strips for GHz Lamb-wave acoustic generation and detection with ultrashort light pulses. By precise choice of the waveguide defect width, this biosensor is designed to work using a single, isolated waveguide mode. We study the influence of the waveguide defect width on the acoustic dispersion and transmission of this mode. Bioparticle attachment is simulated by investigation of the Au nanopillar mass loading, and is shown to shift the waveguide transmission peak to lower frequencies. We thereby demonstrate femtogram detection, showing that our approach provides a new methodology for label-free ultra-sensitive biosensing.

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