Rayleigh wave propagation in a homogeneous centrosymmetric flexoelectric half-space

Although Rayleigh waves are a research topic of constant interest, research on Rayleigh waves in flexoelectric materials is still lacking. This study reports the influences of flexoelectricity, strain gradient elasticity, micro-inertia effect and surface effect on Rayleigh waves in a homogeneous centrosymmetric flexoelectric material half-space. The nonclassical governing equations and boundary conditions are deduced with Hamilton's principle. Our findings suggest that the influence of flexoelectricity on the phase velocity depends on the flexoelectric coefficients. Strain gradient elasticity and surface elasticity can increase the phase velocity, while micro-inertia effect can decrease the phase velocity. Besides, these influences become significant for Rayleigh waves with high frequencies and short wavelengths. A mathematical foundation may be established to measure the material properties on the basis of the relationships among the material parameters, the phase velocity and the wave number. Moreover, the current work might provide guidance in developing small-scale acoustic wave devices operating at high frequencies.

A Three-Dimensional Finite Element Analysis Model for SH-SAW Torque Sensors

In this paper, a three-dimensional finite element analysis (3D-FEA) model for shear horizontal surface acoustic wave (SH-SAW) torque sensors is presented. Torque sensors play a significant role in various fields to ensure a reliable torque transmission in drivelines. Featured with the advantages of high propagation velocity, large Q-value, and good power capacity, SH-SAW based torque sensors are promising but very few studies have been carried out. In order to develop a successful sensor, understanding the characteristics of SH-SAWs produced on piezoelectric substrates and torque sensing modes is indispensable. Therefore, in this study, we first investigated the effect on the generation of waves when different Y-cut quartz substrates are engaged. Thereafter, analyses and comparisons, regarding the effect on the polarized displacement, wave guidance, and wave mode, were conducted for different configurations of wave-guide layer thickness to wavelength ratios (h_layer/λ) and materials. Results show that Y-cut quartz at an angle close to 36° with a gold (Au) layer varying from h_Au/λ = 0.02 to 0.03 thickness could be the most effective configuration for the excitation of SH-SAWs, compared to other combinations using platinum (Pt), titanium (Ti) and silicon dioxide (SiO₂). Finally, based on the FEA SH-SAW torque sensor model configuring with a Y + 36° quartz substrate and 0.025 λ-thick gold layer, the relationship between the applied torque and sensed voltage was examined, which shows a perfect linearity demonstrating the performance of the sensors.

On-chip valley topological materials for elastic wave manipulation

Valley topological materials, in which electrons possess valley pseudospin, have attracted a growing interest recently. The additional valley degree of freedom offers a great potential for its use in information encoding and processing. The valley pseudospin and valley edge transport have been investigated in photonic and phononic crystals for electromagnetic and acoustic waves, respectively. In this work, by using a micromanufacturing technology, valley topological materials are fabricated on silicon chips, which allows the observation of gyral valley states and valley edge transport for elastic waves. The edge states protected by the valley topology are robust against the bending and weak randomness of the channel between distinct valley Hall phases. At the channel intersection, a counterintuitive partition of the valley edge states manifests for elastic waves, in which the partition ratio can be freely adjusted. These results may enable the creation of on-chip high-performance micro-ultrasonic materials and devices.

Surface acoustic wave devices for chemical sensing and microfluidics: A review and perspective

Surface acoustic waves (SAWs), are electro-mechanical waves that form on the surface of piezoelectric crystals. Because they are easy to construct and operate, SAW devices have proven to be versatile and powerful platforms for either direct chemical sensing or for upstream microfluidic processing and sample preparation. This review summarizes recent advances in the development of SAW devices for chemical sensing and analysis. The use of SAW techniques for chemical detection in both gaseous and liquid media is discussed, as well as recent fabrication advances that are pointing the way for the next generation of SAW sensors. Similarly, applications and progress in using SAW devices as microfluidic platforms are covered, ranging from atomization and mixing to new approaches to lysing and cell adhesion studies. Finally, potential new directions and perspectives on the field as it moves forward are offered, with a specific focus on potential strategies for making SAW technologies for bioanalytical applications.

On-chip surface acoustic wave lysis and ion-exchange nanomembrane detection of exosomal RNA for pancreatic cancer study and diagnosis

There has been increasing evidence that micro and messenger RNA derived from exosomes play important roles in pancreatic and other cancers. In this work, a microfluidics-based approach to the analysis of exosomal RNA is presented based on surface acoustic wave (SAW) exosome lysis and ion-exchange nanomembrane RNA sensing performed in conjunction on two separate chips. Using microRNA hsa-miR-550 as a model target and raw cell media from pancreatic cancer cell lines as a biological sample, SAW-based exosome lysis is shown to have a lysis rate of 38%, and an ion-exchange nanomembrane sensor is shown to have a limit of detection of 2 pM, with two decades of linear dynamic range. A universal calibration curve was derived for the membrane sensor and used to detect the target at a concentration of 13 pM in a SAW-lysed sample, which translates to 14 target miRNA per exosome from the raw cell media. At a total analysis time of ~1.5 h, this approach is a significant improvement over existing methods that require two overnight steps and 13 h of processing time. The platform also requires much smaller sample volumes than existing technology (~100 μL as opposed to ~mL) and operates with minimal sample loss, a distinct advantage for studies involving mouse models or other situations where the working fluid is scarce.

Acoustic Wave (TSM) Biosensors: Weighing Bacteria

This chapter is focused on the development and use of acoustic wave biosensor platforms for the detection of bacteria, specifically those based on the thickness shear mode (TSM) resonator. We demonstrated the mechanical and electrical implications of bacterial positioning at the solid-liquid interface of a TSM biosensor and presented a model of the TSM with bacteria attached operating as coupled oscillators. The experiments and model provide an understanding of the nature of the signals produced by acoustic wave devices when they are used for testing bacteria. The paradox of “negative mass” could be a real threat to the interpretation of experimental results related to the detection of bacteria. The knowledge of the true nature of “negative mass” linked to the strength of bacteria attachment will contribute significantly to our understanding of the results of “weighing bacteria.” The results of this work can be used for bacterial detection and control of processes of bacterial settlement, bacterial colonization, biofilm formation, and bacterial infection in which bacterial attachment plays a role.

Neural network surface acoustic wave RF signal processor for digital modulation recognition

An architecture of a surface acoustic wave (SAW) processor based on an artificial neural network is proposed for an automatic recognition of different types of digital passband modulation. Three feed-forward networks are trained to recognize filtered and unfiltered binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals, as well as unfiltered BPSK, QPSK, and 16 quadrature amplitude (16QAM) signals. Performance of the processor in the presence of additive white Gaussian noise (AWGN) is simulated. The influence of second-order effects in SAW devices, phase, and amplitude errors on the performance of the processor also is studied.