Optimizing Surface Acoustic Wave Sensors For Trace Chemical Detection PDF Download

ABSTRACT: Surface acoustic wave (SAW) sensors detect chemical and biological species by monitoring the shifts in frequency of surface acoustic waves generated on piezoelectric substrates. Incorporation of nanomaterials having increased surface area as sensing layer have been effective in improving the sensitivity as well as miniaturization of SAW sensors. Selectivity, sensitivity and speed of response are the three primary aspects for any type of sensor. This dissertation focuses on design and development of SAW devices with novel transducer configurations employing nanomaterial sensing layers for enhanced sensing, improved selectivity, and speed of response. The sensing mechanism in these SAW sensors is a complex phenomenon involving interactions across several different length and time scales. Surface acoustic wave propagation at the macro-scale is influenced by several kinetic phenomena occurring at the molecular scale such as adsorption, diffusion, reaction, and desorption which in turn depend on the properties of nanomaterials. This suggests the requirement of a multi-scale model to effectively understand and manipulate the interactions occurring at different length scales, thereby improving sensor design. Sensor response modeling at multiple time and length scales forms part of this research, which includes perturbation theories, and simulation techniques from finite element methods to molecular-level simulations for interpreting the response of these surface acoustic wave chemical and biosensors utilizing alloy nanostructures as sensing layers. Molecular modeling of sensing layers such as transition metal alloy nanoclusters and nanowires is carried out to gain insights into their thermodynamic, structural, mechanical and dynamic properties. Finite element technique is used to understand the acoustic wave propagation at the macroscale for sensing devices operating at MHz frequencies and with novel transducer designs. The findings of this research provide insights into the design of efficient surface acoustic wave sensors. It is expected that this work will lead to a better understanding of surface acoustic wave devices with novel transducer configurations and employing nanomaterial sensing layers.