Piezoelectric Acoustic Sensor Research Articles

Surface Effects Study: A continuum approach from fundamental modes to higher modes and topological polarization in Orthotropic Piezoelectric Materials

Abstract Purpose: The primary goal of the current work is to investigate how wave propagation influences the performance of surface acoustics wave (SAW) macro- and nano-sensors. Therefore, Shear Horizontal waves (SH) where it contains the surface piezoelectricity theory to explore SH waves in an orthotropic Piezoelectric quasicrystal (PQC) layer overlying an elastic framework (Model I), a Piezoelectric substrate, and an orthotropic PQC Substrate (Model II). Methodology: Study employs a variable-separable technique. The theoretical forms are constructed and used to present the wavenumber of surface waves in any direction of the piezoelectric medium, based on the differential equations and matrix formulation. In addition, we take into account surface elasticity theory in order to obtain the phase velocity equation. Findings: Two configurations are examined: an orthotropic piezoelectric material layer over an elastic framework and a piezoelectric material half-space with a nano substrate. Analytical expressions for frequency equations are derived for both symmetric and anti-symmetric waves. Study investigates the effects of surface elastic constants, surface density, anisotropic piezoelectric constant, group velocity, electromechanical coupling factors and symmetric and antisymmetric modes on phase velocity. Research Limitations: The study is confined to only linear wave propagation. Additionally, the analysis is based on idealized material properties, surface properties, and characteristic length of the material. Practical Implications: The findings of this research may be useful in designing surface acoustic wave sensors (SAW) devices and piezoelectric sensors surface acoustic wave sensors. Keywords: Multiple Modes; Surface effect; Wave Controlling; Electromechanical Coupling Factor; Group Velocity; Strain Gradient Theory.

Flexible Hair‐Like Piezoelectric Acoustic Particle Velocity Sensor with Enhanced Sensitivity for Speaker Recognition

AbstractFlexible resonant acoustic sensors exhibit enhanced sensitivity near their resonant frequencies and have attracted increasing interest as essential components for next‐generation human‐machine speech interactions. However, membrane‐based resonant acoustic sensors are bulky owing to the inherently high bending stiffness of the sensing membrane. Inspired by the tiny hair‐based sensitive acoustic receptors of spiders, this study reports a hair‐like piezoelectric resonant acoustic particle velocity sensor (HP‐APVS) that enables highly sensitive sound sensing with a significantly reduced size. The HP‐APVS device is essentially a polyimide cantilever array fabricated using Nb0.02‐Pb(Zr0.6Ti0.4)O3 (PZT) on polyimide and self‐bending processes. The experimental results demonstrate that the HP‐APVS shows a linear response to acoustic particle velocity instead of acoustic pressure, with enhanced sensitivity in the resonance mode. Additionally, the proposed HP‐APVS exhibits an outstanding speaker recognition rate of 95.3% with an error rate reduction of 75% compared with that of a reference commercial microphone, indicating many potential applications in the realms of biometric authentication, voice user interfaces, and other intelligent acoustic electronics.

Design and Optimization of a Piezoelectric Acoustic Sensor for Fluid Leak Detection Applications

Design and Optimization of a Piezoelectric Acoustic Sensor for Fluid Leak Detection Applications

Piezoelectric temperature acoustic sensor of LiNbO3 crystal fibers operating at radio frequencies

This study focuses on the growth and characterization of crystalline LiNbO3 (LN) piezoelectric fibers pulled by the Laser Heated Pedestal Growth (LHPG) technique. The electrical properties of the fibers were investigated using an impedance analyzer, which yielded values for resonance frequency, anti-resonance frequency, and phase angle. Subsequently, elastic constants and coupling factor were determined through calculations based on thickness resonance modes. The accuracy of the resonance method was validated through numerical simulations utilizing COMSOL software, demonstrating a close agreement between experimental and simulated results. Additionally, a temperature sensing was conducted, subjecting the fibers to a wide temperature range from 30 °C to 236 °C to assess their sensitivity to temperature variations. The coupling factors of K = 0.37 for LN-1 and K = 0.35 for LN-2 demonstrated efficient performance of the crystalline fibers. Furthermore, the numerical simulations exhibited strong correlation between simulated and experimental data. The sensitivity analysis revealed the potential of LN fibers for temperature sensor applications, exhibiting a sensitivity of −87 Hz.°C−1. These findings underscore the promise of LN piezoelectric fibers in advanced sensing technologies.

Design and Characterization of a Dual-Protein Strategy for an Early-Stage Assay of Ovarian Cancer Biomarker Lysophosphatidic Acid.

The overall 5-year survival rate of ovarian cancer (OC) is generally low as the disease is often diagnosed at an advanced stage of progression. To save lives, OC must be identified in its early stages when treatment is most effective. Early-stage OC causes the upregulation of lysophosphatidic acid (LPA), making the molecule a promising biomarker for early-stage detection. An LPA assay can additionally stage the disease since LPA levels increase with OC progression. This work presents two methods that demonstrate the prospective application for detecting LPA: the electromagnetic piezoelectric acoustic sensor (EMPAS) and a chemiluminescence-based iron oxide nanoparticle (IONP) approach. Both methods incorporate the protein complex gelsolin-actin, which enables testing for detection of the biomarker as the binding of LPA to the complex results in the separation of gelsolin from actin. The EMPAS was characterized with contact angle goniometry and atomic force microscopy, while gelsolin-actin-functionalized IONPs were characterized with transmission electron microscopy and Fourier transform infrared spectroscopy. In addition to characterization, LPA detection was demonstrated as a proof-of-concept in Milli-Q water, buffer, or human serum, highlighting various LPA assays that can be developed for the early-stage detection of OC.

Dependence of sensitivity loss on organic film thickness and influence of cantilever warpage in a piezoelectric wideband acoustic sensor coated with an organic film

A wideband acoustic sensor is reported, comprising a piezoelectric MEMS acoustic transducer with organic film-coated cantilevers. Considering the sensitivity reduction associated with the application of an organic film, it is necessary to optimize the material selection and thickness of the organic film. Therefore, the relationship between the thickness of the polyurethane film and the consequent loss in sensitivity is elucidated. Our findings demonstrate that the polyurethane film thickness should be approximately 0.5 μm (or less) to limit sensitivity loss to 6 dB. Additionally, both simulations and experimental results reveal that the resonant frequency of the system is significantly influenced by the warpage of the cantilever. This study provides essential insights into optimizing the performance of MEMS acoustic transducers with organic film-coated cantilevers.

Interaction of Pseudomonas aeruginosa with surface-modified silica studied by ultra-high frequency acoustic wave biosensor

Aim: This study aimed to examine the amount of surface non-specific adsorption, or fouling, observed by Pseudomonas aeruginosa (P. aeruginosa) on a quartz crystal based acoustic wave biosensor under different flow conditions with and without an anti-fouling layer. Methods: An electromagnetic piezoelectric acoustic sensor (EMPAS) based on electrode free quartz crystals was used to perform the analysis. Phosphate buffered saline (PBS) was flowed over the crystal surface at various flow rates from 50 μL/min to 200 μL/min, with measurements being taken at the 43rd harmonic (~864 MHz). The crystal was either unmodified, or modified with a monoethylene glycol [2-(3-silylpropyloxy)-hydroxy-ethyl (MEG-OH)] anti-fouling layer. Overnight culture of P. aeruginosa PAO1 (PAO1) in lysogeny broth (LB) was injected into the system, and flow maintained for 30 min. Results: The frequency change of the EMPAS crystal after injection of bacteria into the system was found to change based on the flow rate of buffer, suggesting the flow rate has a strong effect on the level of non-specific adsorption. The MEG-OH layer drastically reduced the level of fouling observed under all flow conditions, as well as reduced the amount of variation between experiments. Flow rates of 150 μL/min or higher were found to best reduce the level of fouling observed as well as experimental variation. Conclusions: The MEG-OH anti-fouling layer is important for accurate and reproducible biosensing measurements due to the reduced fouling and variation during experiments. Additionally, a flow rate of 150 μL/min may prove better for measurement compared to the current standard of 50 μL/min for this type of instrument.

Multi‐Length Engineering of (K, Na)NbO3 Films for Lead‐Free Piezoelectric Acoustic Sensors with High Sensitivity

AbstractWith increasing concerns about noise pollution, the pursuit of highly dependable piezoelectric acoustic sensors for real‐time noise monitoring has come to the forefront of scientific research. Lead‐based perovskite piezoelectric films, exemplified by lead zirconate titanate Pb(Zr,Ti)O3 (PZT), surpass traditional piezoelectric materials such as ZnO and AlN in their piezoelectric properties, promising substantial advancements in next‐generation acoustic sensor technologies. However, the toxic nature of lead in PZT materials poses formidable environmental and human health risks. In an unprecedented breakthrough, it presents the pioneering development of an environmentally benign lead‐free piezoelectric Micro‐Electro‐Mechanical System (MEMS) acoustic sensor based on potassium sodium niobate (K,Na)NbO3 (KNN) film. High‐quality <001> textured 3 µm‐thick KNN film is successfully integrated into commercially used Si substrate, rendering exceptional piezoelectricity (transverse piezoelectric coefficients e31* of ≈8.5 C m−2) with satisfactory thermal stability. The atomic‐scale Z‐contrast imaging and piezoresponse force microscopy characterizations reveal that the outstanding piezoresponse originates from the local coexistence of multiple phases and the enhancement of extrinsic piezoelectric contributions from in‐plane polarization anisotropy. Finite element simulation is employed to design the triangular cantilever structure and annular diaphragm structure, each corresponding to different operating bandwidths. The resultant MEMS acoustic sensors stand out with outstanding acoustic performance (the high sensitivity and expansive receiving field of view), which are attributed to the microstructural engineering at multi‐length scales for the excellent piezoelectric properties of KNN film. These features enable sensitive acoustic monitoring in various environments, including large‐scale power grids and urban traffic.

Theoretical Basis of Biomimetic Flexible Piezoelectric Acoustic Sensors for Future Customized Auditory Systems

AbstractFlexible piezoelectric sensors have been spotlighted as an essential human–machine interface (HMI) by obtaining high‐quality data from omnipresent biomechanical inputs. Because human voice is the most intuitive bio‐signal among them, flexible piezoelectric acoustic sensors (f‐PAS) have a potential to shift the paradigm of HMI technologies. Despite the reported outstanding performance such as high sensitivity and speaker recognition accuracy, the theoretical investigation of f‐PAS has been insufficient to realize future customized development, because sensing principles are fundamentally different from commercialized microphones. Here, a theoretical framework of self‐powered f‐PAS by using mechanical and electrical physics is introduced. First of all, the basic theory of f‐PAS is compared with the auditory system of human cochlear. Based on the biomimetic trapezoidal shape, the resonant frequencies are analyzed with various structural and material conditions. In addition, the piezoelectricity of f‐PAS is derived to predict the sensitivity and SNR prior to experiments. To investigate sensor properties under the medium condition that is similar to human ear, the acoustic responses depending on the states of matter are theoretically compared. Finally, the distance limit of f‐PAS is studied with the correlations between piezoelectricity and sound pressure, which would provide novel strategies of functional material design for future applications of f‐PAS.

Microcrack-assisted piezoelectric acoustic sensor based on f-MWCNTs/BaTiO3@PDMS nanocomposite and its self-powered voice recognition applications

Piezoelectric materials are suitable for use in wearable devices because of their simplicity and self-powering characteristics. However, before they can be used as wearable sensors, their flexibility and sensitivity need to be enhanced. Therefore, investing time and effort for improving piezoelectric materials is essential. In this study, we fabricated flexible piezoelectric nanogenerators (FPENGs) with microcracks based on a functionalized multi-walled carbon nanotubes/BaTiO3@polydimethylsiloxane composite. Then, we performed morphological and structural analyses of the fabricated composite. It was found that the presence of microcracks improved the output performance of the FPENG. The fabricated FPENG could function as an acoustic sensor with significantly enhanced frequency range sensitivity. As a proof-of-concept application, the ability of the FPENG to differentiate the loudness and melody of sound music, as well as its audio-to-text conversion capability, was demonstrated. These results validated the potential of the FPENG for a broader range of wireless communication applications on the Internet of Things.

Machine learning based flexible piezoelectric sensor

This seminar introduces flexible inorganic piezoelectric membrane that can detect the minute vibration of membrane for self-powered acoustic sensor and blood pressure monitor. Herein, we reported a machine learning-based acoustic sensor by mimicking the basilar membrane of human cochlear. Highly sensitive self-powered flexible piezoelectric acoustic sensor with a multi-resonant frequency band was employed for voice recognition. Convolutional Neural Network (CNN) were utilized for speaker recognition, resulted in a 97.5% speaker recognition rate with the 75% reduction of error rate compared to that of the reference MEMS microphone.

Optimization and fabrication of MEMS based piezoelectric acoustic sensor for wide frequency range and high SPL acoustic application

This paper reports finite element model (FEM) simulation and fabrication of a square shaped diaphragm along with microtunnel for MEMS acoustic sensor which can be used for measurement of wide operational frequency range and high sound pressure level (SPL) 100 dB–180 dB measurement in launching vehicle and aircraft. The structure consists of a piezoelectric ZnO layer sandwiched between two aluminum electrodes on a thin silicon diaphragm. There is a microtunnel in the structure which relates the cavity to the atmosphere for pressure compensation. The microtunnel decides the lower cut-off frequency of device. Analytical and simulation approaches are used to optimize microtunnel dimension and simulation approach for diaphragm structure optimization. The change in displacement, stress, sensitivity and resonance frequency due to different diaphragm sizes with diaphragm thickness variation is also analyzed. The optimized diaphragm structure of 1750 × 1750 μm2 and microtunnel of 100 μm wide and 24 μm deep have been fabricated using bulk micromachining technique. The fabricated device response has been tested using LDV and sensitivity measurement system.

Piezoelectric MEMS wideband acoustic sensor coated by organic film

In this study, we developed an acoustic sensor with a structure in which a piezoelectric cantilever array is covered with an organic film. For this, we used AlN and polyurethane as the piezoelectric material and organic film, respectively. The results suggested that the sensitivity in the low-frequency region improved, and the resonance frequency increased. We investigated the resonance frequency based on a simulation and verified that it matched the measured value. Further, we created a broadband acoustic sensor by covering the space between the cantilevers with an organic film.

Characterization of a Piezoelectric Acoustic Sensor Fabricated for Low-Frequency Applications: A Comparative Study of Three Methods.

Piezoelectric transducers are widely used for generating acoustic energy, and choosing the right radiating element is crucial for efficient energy conversion. In recent decades, numerous studies have been conducted to characterize ceramics based on their elastic, dielectric, and electromechanical properties, which have improved our understanding of their vibrational behavior and aided in the manufacturing of piezoelectric transducers for ultrasonic applications. However, most of these studies have focused on the characterization of ceramics and transducers using electrical impedance to obtain resonance and anti-resonance frequencies. Few studies have explored other important quantities such as acoustic sensitivity using the direct comparison method. In this work, we present a comprehensive study that covers the design, manufacturing, and experimental validation of a small-sized, easy-to-assemble piezoelectric acoustic sensor for low-frequency applications, using a soft ceramic PIC255 from PI Ceramic with a diameter of 10 mm and a thickness of 5 mm. We present two methods, analytical and numerical, for sensor design, followed by experimental validation, allowing for a direct comparison of measurements with simulated results. This work provides a useful evaluation and characterization tool for future applications of ultrasonic measurement systems.

Flexible Pb(Zr0.52,Ti0.48)O3 thin film acoustic emission sensor for monitoring partial discharge in power cable

Piezoelectric acoustic emission sensors can be used detect the sound emitted by the target structure when it is damaged and have important applications in the field of structure health monitoring. However, due to the mismatch of the interface acoustic impedance, it is hard for the conventional ultrasonic sensor to monitor the acoustic emission in a pipe structure. In this work, a flexible sensor by the deposition of a Pb(Zr0.52,Ti0.48)O3 thin film on a mica substrate was fabricated, and the acoustic emission generated by the partial discharge of a 110 kV power cable was detected by using the flexible sensor. The flexible sensor was designed with an electromagnetic shielding structure and, therefore, can screen most of the electromagnetic interference. The flexible sensor shows a relatively flat response in the frequency range from 100 to 1000 kHz with a sensitivity over 47.5 dB, which is beneficial for pattern recognition studies of acoustic emission. This work not only provides a flexible, anti-electromagnetic interference and broadband sensor for acoustic emission detection but also promotes the development and application of flexible ferroelectric materials.

Multichannel Gradient Piezoelectric Transducer Assisted with Deep Learning for Broadband Acoustic Sensing.

As an important part of human-machine interfaces, piezoelectric voice recognition has received extensive attention due to its unique self-powered nature. However, conventional voice recognition devices exhibit a limited response frequency band due to the intrinsic hardness and brittleness of piezoelectric ceramics or the flexibility of piezoelectric fibers. Here, we propose a cochlear-inspired multichannel piezoelectric acoustic sensor (MAS) based on gradient PVDF piezoelectric nanofibers for broadband voice recognition by a programmable electrospinning technique. Compared with the common electrospun PVDF membrane-based acoustic sensor, the developed MAS demonstrates the greatly 300%-broadened frequency band and the substantially 334.6%-enhanced piezoelectric output. More importantly, this MAS can serve as a high-fidelity auditory platform for music recording and human voice recognition, in which the classification accuracy rate can reach up to 100% in coordination with deep learning. The programmable bionic gradient piezoelectric nanofiber may provide a universal strategy for the development of intelligent bioelectronics.

Design and Modeling of Piezoelectric-AlN-based Acoustic Sensor for Sound Pressure Level Measurements

This paper illustrates the design of a piezoelectric acoustic sensor based on AlN to be used for aero-acoustic measurements. A significant prerequisite for such sensors is a large sound pressure level (SPL) and flat frequency response in the auditory band (20 Hz to 20 kHz). That is why this sensor has been designed to measure upto an SPL of 180 dB. The design of the device has been achieved through the MEMS-CAD tool Coventorware. The Si-diaphragm thickness has been optimized for the desired SPL range using Coventorware for three different sizes of the device, namely 1.5 mm × 1.5 mm, 1.75 mm × 1.75 mm and 2 mm × 2 mm. The cavity developed after the diaphragm formation is connected to the exterior environment through a microchannel. The microchannel was designed for low cut-off frequency. The complete frequency response of all the three sensor structures has been determined. Moreover, a comparison has been drawn among the three devices in terms of parameters such as low cut-off frequency, resonance frequency, and sensitivity to find the optimized device size. The low cut-off frequency, resonance frequency, and flat band sensitivity of the optimized device are 35 Hz, 83 kHz, and 170 µV/Pa, respectively. In addition to this, a proposed fabrication process flow of the device has been presented.

High-performance microcone-array flexible piezoelectric acoustic sensor based on multicomponent lead-free perovskite rods

<h2>Summary</h2> Piezoelectric materials can serve as favorable candidates for future cochlear implants. However, most piezoelectric hearing devices until now have failed to simultaneously provide high sensitivity, desired flexibility, broad frequency selectivity, and biocompatibility. Herein, inspired by human outer ear hair cells, we meet these issues by introducing a microcone patterning array strategy based on novel lead-free, multicomponent rod-shaped niobate piezoelectric materials with a morphotropic phase boundary. The output voltage of the rod-based, flexible piezoelectric acoustic sensor (FPAS) is nearly 300% of that of the isotropic particles. The microcone patterning FPAS with stable performance in harsh environments shows high sensitivity (39.22 mV Pa⁻¹⋅cm⁻²) due to the significant enhancement of sound energy absorption and can record sound signals, recognize audio signals, and realize human-computer interactions. Our work demonstrates that the FPAS holds promise for various applications, such as the Internet of Things (IoT), cochlea implants, wearable acoustic equipment, and human-computer interaction.

Multiphase Flow Analysis Using Piezoelectric Leaf-Cell Sensor Array

The composition of the multiphase flow rates from hydrocarbon reservoirs has direct impact on the programs to optimize hydrocarbon production and for the identification of problems with production. However, the accurate measurement of the flow rates of oil, brine, and gas in three-phase regimes remains an intractable problem for current state-of-the-art sensor technologies. Here, we describe a piezoelectric acoustic leaf-cell sensor array providing an in situ real-time measurement of the distribution in three-phase flow fluid density over the wellbore cross section. The sensor array measurements are evaluated from experimental three-phase flow loop test data under a range of flow regimes comprised of 0–95% gas volume fraction and water/liquid volume ratio between 0 and 100%. The experimental data include three-phase flow transitions well into the nonlinear subsonic gas velocity region predicted by the Wood equation and show an average absolute error in three-phase fluid density prediction less than 0.05 g/cc over the entire test regimen.

Deep learning-based noise robust flexible piezoelectric acoustic sensors for speech processing

Flexible piezoelectric acoustic sensors (f-PAS) have attracted significant attention as a promising component for voice user interfaces (VUI) in the era of artificial intelligence of things (AIoT). The signal distortion issue of highly sensitive biomimetic f-PAS is one of the most challenging obstacle for real-life application, due to the fundamental difference compared with the conventional microphones. Here, a noise-robust flexible piezoelectric acoustic sensor (NPAS) is demonstrated by designing the multi-resonant bands outside the noise dominant frequency range. Broad voice coverage up to 8 kHz is achieved by adopting an advanced piezoelectric membrane (Nb-doped PZT; PNZT) with the optimized polymer ratio. Deep learning-based speech processing of multi-channel NPAS is demonstrated to show the outstanding improvement in speaker recognition and speech enhancement compared to a commercial microphone. Finally, the NPAS filtered the crowd condition noises, showing independent speaker’s speeches can be identified and digitalized simultaneously.