Flexible thin-film acoustic wave devices with off-axis bending characteristics for multisensing applications

Acoustofluidic precise manipulation: Recent advances in applications for micro/nano bioparticles

Acoustofluidic technologies that integrate acoustic waves and microfluidic chips have been widely used in bioparticle manipulation. As a representative technology, acoustic tweezers have attracted significant attention due to their simple manufacturing, contact-free operation, and low energy consumption. Recently, acoustic tweezers have enabled the efficient and smart manipulation of biotargets with sizes covering millimeters (such as zebrafish) and nanometers (such as DNA). In addition to acoustic tweezers, other related acoustofluidic chips including acoustic separating, mixing, enriching, and transporting chips, have also emerged to be powerful platforms to manipulate micro/nano bioparticles (cells in blood, extracellular vesicles, liposomes, and so on). Accordingly, some interesting applications were also developed, such as smart sensing. In this review, we firstly introduce the principles of acoustic tweezers and various related technologies. Second, we compare and summarize recent applications of acoustofluidics in bioparticle manipulation and sensing. Finally, we outlook the future development direction from the perspectives such as device design and interdisciplinary.

Acoustofluidic Diversity Achieved by Multiple Modes of Acoustic Waves Generated on Piezoelectric-Film-Coated Aluminum Sheets

Excitation of multiple acoustic wave modes on a single chip is beneficial to implement diversified acoustofluidic functions. Conventional acoustic wave devices made of bulk LiNbO3 substrates generally generate few acoustic wave modes once the crystal-cut and electrode pattern are defined, limiting the realization of acoustofluidic diversity. In this paper, we demonstrated diversity of acoustofluidic behaviors using multiple modes of acoustic waves generated on piezoelectric-thin-film-coated aluminum sheets. Multiple acoustic wave modes were excited by varying the ratios between IDT pitch/wavelength and substrate thickness. Through systematic investigation of fluidic actuation behaviors and performances using these acoustic wave modes, we demonstrated fluidic actuation diversities using various acoustic wave modes and showed that the Rayleigh mode, pseudo-Rayleigh mode, and A0 mode of Lamb wave generally have better fluidic actuation performance than those of Sezawa mode and higher-order modes of Lamb wave, providing guidance for high-performance acoustofluidic actuation platform design. Additionally, we demonstrated diversified particle patterning functions, either on two sides of acoustic wave device or on a glass sheet by coupling acoustic waves into the glass using the gel. The pattern formation mechanisms were investigated through finite element simulations of acoustic pressure fields under different experimental configurations.

Achieving consistency of flexible surface acoustic wave sensors with artificial intelligence

Flexible surface acoustic wave technology has garnered significant attention for wearable electronics and sensing applications. However, the mechanical strains induced by random deformation of these flexible SAWs during sensing often significantly alter the specific sensing signals, causing critical issues such as inconsistency of the sensing results on a curved/flexible surface. To address this challenge, we first developed high-performance AlScN piezoelectric film-based flexible SAW sensors, investigated their response characteristics both theoretically and experimentally under various bending strains and UV illumination conditions, and achieved a high UV sensitivity of 1.71 KHz/(mW/cm²). To ensure reliable and consistent UV detection and eliminate the interference of bending strain on SAW sensors, we proposed using key features within the response signals of a single flexible SAW device to establish a regression model based on machine learning algorithms for precise UV detection under dynamic strain disturbances, successfully decoupling the interference of bending strain from target UV detection. The results indicate that under strain interferences from 0 to 1160 με the model based on the extreme gradient boosting algorithm exhibits optimal UV prediction performance. As a demonstration for practical applications, flexible SAW sensors were adhered to four different locations on spacecraft model surfaces, including flat and three curved surfaces with radii of curvature of 14.5, 11.5, and 5.8 cm. These flexible SAW sensors demonstrated high reliability and consistency in terms of UV sensing performance under random bending conditions, with results consistent with those on a flat surface.

Low-noise fluorescent detection of cardiac troponin I in human serum based on surface acoustic wave separation

Acute myocardial infarction (AMI) is a life-threatening disease when sudden blockage of coronary artery occurs. As the most specific biomarker, cardiac troponin I (cTnI) is usually checked separately to diagnose or eliminate AMI, and achieving the accurate detection of cTnI is of great significance to patients' life and health. Compared with other methods, fluorescent detection has the advantages of simple operation, high sensitivity and wide applicability. However, due to the strong fluorescence interference of biological molecules in body fluids, it is often difficult to obtain high sensitivity. In order to solve this problem, in this study, surface acoustic wave separation is designed to purify the target to achieve more sensitive detection performance of fluorescent detection. Specifically, the interference of background noise is almost completely removed on a microfluidic chip by isolating microbeads through acoustic radiation force, on which the biomarkers are captured by the immobilized detection probe. And then, the concentration of cTnI in human serum is detected by the fluorescence intensity change of the isolated functionalized beads. By this way, the detection limit of our biosensor calculated by 3σ/K method is 44 pg/mL and 0.34 ng/mL in PBS buffer and human serum respectively. Finally, the reliability of this method has been validated by comparison with clinical tests from the nephelometric analyzer in hospital.

Bimorph Dual-Electrode ScAlN PMUT with Two Terminal Connections

This paper presents a novel bimorph Piezoelectric Micromachined Ultrasonic Transducer (PMUT) fabricated with 8-inch standard CMOS-compatible processes. The bimorph structure consists of two layers of 20% scandium-doped aluminum nitride (Sc_0.2Al_0.8N) thin films, which are sandwiched among three molybdenum (Mo) layers. All three Mo layers are segmented to form the outer ring and inner plate electrodes. Both top and bottom electrodes on the outer ring are electrically linked to the center inner plate electrodes. Likewise, the top and bottom center plate electrodes are electrically connected to the outer ring in the same fashion. This electrical configuration maximizes the effective area of the given PMUT design and improves efficiency during the electromechanical coupling process. In addition, the proposed bimorph structure further simplifies the device's electrical layout with only two-terminal connections as reported in many conventional unimorph PMUTs. The mechanical and acoustic measurements are conducted to verify the device's performance improvement. The dynamic mechanical displacement and acoustic output under a low driving voltage (1 Vpp) are more than twice that reported from conventional unimorph devices with a similar resonant frequency. Moreover, the pulse-echo experiments indicate an improved receiving voltage of 10 mV in comparison with the unimorph counterpart (4.8 mV). The validation of device advancement in the electromechanical coupling effect by using highly doped ScAlN thin film, the realization of the proposed bimorph PMUT on an 8-inch wafer paves the path to production of next generation, high-performance piezoelectric MEMS.

Self-Powered Long-Life Microsystem for Vibration Sensing and Target Recognition

Microsystems play an important role in the Internet of Things (IoT). In many unattended IoT applications, microsystems with small size, lightweight, and long life are urgently needed to achieve covert, large-scale, and long-term distribution for target detection and recognition. This paper presents for the first time a low-power, long-life microsystem that integrates self-power supply, event wake-up, continuous vibration sensing, and target recognition. The microsystem is mainly used for unattended long-term target perception and recognition. A composite energy source of solar energy and battery is designed to achieve self-powering. The microsystem's sensing module, circuit module, signal processing module, and transceiver module are optimized to further realize the small size and low-power consumption. A low-computational recognition algorithm based on support vector machine learning is designed and ported into the microsystem. Taking the pedestrian, wheeled vehicle, and tracked vehicle as targets, the proposed microsystem of 15 cm³ and 35 g successfully realizes target recognitions both indoors and outdoors with an accuracy rate of over 84% and 65%, respectively. Self-powering of the microsystem is up to 22.7 mW under the midday sunlight, and 11 min self-powering can maintain 24 h operation of the microsystem in sleep mode.

A new strategy to minimize humidity influences on acoustic wave ultraviolet sensors using ZnO nanowires wrapped with hydrophobic silica nanoparticles

Surface acoustic wave (SAW) technology has been widely developed for ultraviolet (UV) detection due to its advantages of miniaturization, portability, potential to be integrated with microelectronics, and passive/wireless capabilities. To enhance UV sensitivity, nanowires (NWs), such as ZnO, are often applied to enhance SAW-based UV detection due to their highly porous and interconnected 3D network structures and good UV sensitivity. However, ZnO NWs are normally hydrophilic, and thus, changes in environmental parameters such as humidity will significantly influence the detection precision and sensitivity of SAW-based UV sensors. To solve this issue, in this work, we proposed a new strategy using ZnO NWs wrapped with hydrophobic silica nanoparticles as the effective sensing layer. Analysis of the distribution and chemical bonds of these hydrophobic silica nanoparticles showed that numerous C-F bonds (which are hydrophobic) were found on the surface of the sensitive layer, which effectively blocked the adsorption of water molecules onto the ZnO NWs. This new sensing layer design minimizes the influence of humidity on the ZnO NW-based UV sensor within the relative humidity range of 10-70%. The sensor showed a UV sensitivity of 9.53 ppm (mW/cm2)-1, with high linearity (R 2 value of 0.99904), small hysteresis (<1.65%) and good repeatability. This work solves the long-term dilemma of ZnO NW-based sensors, which are often sensitive to humidity changes.