Abstract
In the fields of analytical and physical chemistry, medical diagnostics and biotechnology there is an increasing demand of highly selective and sensitive analytical techniques which, optimally, allow an in real-time label-free monitoring with easy to use, reliable, miniaturized and low cost devices. Biosensors meet many of the above features which have led them to gain a place in the analytical bench top as alternative or complementary methods for routine classical analysis. Different sensing technologies are being used for biosensors. Categorized by the transducer mechanism, optical and acoustic wave sensing technologies have emerged as very promising biosensors technologies. Optical sensing represents the most often technology currently used in biosensors applications. Among others, Surface Plasmon Resonance (SPR) is probably one of the better known label-free optical techniques, being the main shortcoming of this method its high cost. Acoustic wave devices represent a cost-effective alternative to these advanced optical approaches [1], since they combine their direct detection, simplicity in handling, real-time monitoring, good sensitivity and selectivity capabilities with a more reduced cost. The main challenges of the acoustic techniques remain on the improvement of the sensitivity with the objective to reduce the limit of detection (LOD), multi-analysis and multi-analyte detection (High-Throughput Screening systems-HTS), and integration capabilities. Acoustic sensing has taken advantage of the progress made in the last decades in piezoelectric resonators for radio-frequency (rf) telecommunication technologies. The so-called gravimetric technique [2], which is based on the change in the resonance frequency experimented by the resonator due to a mass attached on the sensor surface, has opened a great deal of applications in bio-chemical sensing in both gas and liquid media. Traditionally, the most commonly used acoustic wave biosensors were based on QCM devices. This was primarily due to the fact that the QCM has been studied in detail for over 50 years and has become a mature, commercially available, robust and affordable technology [3, 4]. LW acoustic sensors have attracted a great deal of attention in the scientific community during the last two decades, due to its reported high sensitivity in liquid media compared to traditional QCM-based sensors. Nevertheless, there are still some issues to be further understood, clarified and/or improved about this technology; mostly for biosensor applications. LW devices are able to operate at higher frequencies than traditional QCMs [5]; typical operation frequencies are between 80-300 MHz. Higher frequencies lead, in principle, to higher sensitivity because the acoustic wave penetration depth into the adjacent media is reduced [6]. However, the increase in the operation frequency also results in an increased noise level, thus restricting the LOD. The LOD determines the minimum surface mass that can be detected. In this sense, the optimization of the read out and characterization system for these high frequency devices is a key aspect for improving the LOD [7]. Another important aspect of LW technology is the optimization of the fluidics, specially the flow cell. This is of extreme importance for reducing the noise and increasing the biosensor system stability; aspects that will contribute to improve the LOD. The analysis and interpretation of the results obtained with LW biosensors must be deeper understood, since the acoustic signal presents a mixed contribution of changes in the mass and the viscoelasticity of the adsorbed layers due to interactions of the biomolecules. A better understanding of the transduction mechanism in LW sensors is a first step to advance in this issue; however its inherent complexity leads, in many cases, to frustration [8]. The fabrication process of the transducer, unlike in traditional QCM sensors, is another aspect under investigation in LW technology, where features such as: substrate materials, sizes, structures and packaging must be still optimized. This chapter aims to provide an updated insight in the mentioned topics focused on biosensors applications.
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