Design and modeling of an integrated device for acoustic resonance spectroscopy

This paper investigates the design and modelling of an integrated device for acoustic resonance spectroscopy (ARS). Miniaturisation of such platforms can be achieved using MEMS technology thereby enabling scaling of device dimensions to investigate smaller specimens while simultaneously operating at higher frequencies. We propose an integrated device where the transducers are mounted in close proximity with the specimen to be analysed (e.g. by integrating ultrasound transducers within a microfluidic channel). A finite element (FE) model and a simplified analytical model have been constructed to predict the acoustic response of a sample embedded in such a device configuration. A FE simulation is performed in COMSOL by embedding the piezoelectric transducers in representative fluid media. Resonant frequencies associated with the measurement can be extracted from this data. The response of various media modelled through FEA matches with analytical predictions for a range of biological media. A variety of biological media may be identified by using the measured resonant frequencies as a signature of relevant physical characteristics. The paper establishes the modelling basis of an integrated acoustic resonant spectrometer that is then applied to examine the impact of geometrical scaling on system resolution. © 2013 IEEE.

Measuring the kinetics of amyloid fibril elongation using quartz crystal microbalances.

Kinetic measurements of amyloid growth provide insight into the free energy landscape of this supramolecular process and are crucial in the search for potent inhibitors of the main disorders with which it is associated, including Alzheimer's and Parkinson's diseases and Type II diabetes. In recent years, a new class of surface-bound biosensor assays, e.g., those based on surface plasmon resonance (SPR) and the quartz crystal microbalance (QCM) have been established as extremely valuable tools for kinetic measurements of amyloid formation. Here we describe detailed protocols of how QCM techniques can be used to monitor the elongation of amyloid fibrils in real time and to study the influence of external factors on the kinetics of amyloid growth with unprecedented accuracy.