This work reports on the first demonstration of the frequency tuning and intrinsic polarization switching of film bulk acoustic resonators (FBARs), based on sputtered AlScN piezoelectric thin films with Sc/(Al + Sc) ratio of approx. 30%. A box-like ferroelectric hysteresis behavior of 900 nm-thick Al0.7Sc0.3N sputtered films is obtained, showing a coercive electric field at ~3 MV/cm. The fundamental thickness-mode resonance of the bulk acoustic wave (BAW) resonator is measured at 3.17 GHz frequency with an excellent electromechanical coupling coefficient (kt²) of 18.1 %. The FBAR frequency response is studied, in both (i) the linear tuning regime, upon application of DC electric fields below the coercive field; as well as (ii) the polarization switching regime, upon application of electric fields above the coercive field. A large linear tuning range of 215 ppm x μm/V is obtained in case (i), resulting from the high scandium content. The series resonance frequency of the FBARs is switched ON and OFF in (ii) upon application of 350 V unipolar waveform across the Al0.7Sc0.3N thickness. This is the first demonstration of the intrinsically switchable AlN-based FBARs with a large tuning range; and record high kt² reported for AlN-based FBARs to date. Furthermore, this work paves the way for realization of tunable and switchable wideband acoustic filters operating at super high frequency ranges (SHF). [2020-0203]

This paper presents a passive temperature compensation technique that can provide full cancellation of the linear temperature coefficient of frequency (TCF1) in silicon resonators. A uniformly distributed matrix of silicon dioxide pillars is embedded inside the silicon substrate to form a homogenous composite silicon oxide platform (SilOx) with nearly perfect temperature-compensated stiffness moduli. This composite platform enables the implementation of temperature-stable microresonators operating in any desired in- and out-of-plane resonance modes. Full compensation of TCF₁ is achieved for extensional and shear modes of SilOx resonators resulting in a quadratic temperature characteristic with an overall frequency drift as low as 83 ppm over the industrial temperature range ( -40°C to 80°C). Besides a 40 times reduction in temperature-induced frequency drift in this range, SilOx resonators exhibit improved temperature stability of Q compared with their single crystal silicon counterparts.

This paper presents a digital gyroscope interface system for high-frequency bulk-acoustic-wave (BAW) gyroscopes with in-run automatic mode-matching (AMM) capability. The presented work demonstrates the design and implementation of the dual mode (DM) operation architecture on a flexible digital platform, which allows for low-cost rapid development and evaluation of new functions and architectures. Two prototype silicon BAW gyroscopes are tested on this platform using the proposed system to verify the advantages of the dual mode architecture. The AMM in dual mode showed below 4 ppb mode split accuracy and fast converge time without overshoot or oscillation. The dual mode operation with in-run AMM substantially reduced the bias drift of the gyros, leading to significantly lower rate random walk (RRW) compared to conventional single mode operation. The performance repeatability and stability over temperature of the dual mode gyro system is characterized, showing as high as 50x improvement compared to the single mode architecture.

Monitoring pathological mechano-acoustic signals emanating from the lungs is critical for timely and cost-effective healthcare delivery. Adventitious lung sounds including crackles, wheezes, rhonchi, bronchial breath sounds, stridor or pleural rub and abnormal breathing patterns function as essential clinical biomarkers for the early identification, accurate diagnosis and monitoring of pulmonary disorders. Here, we present a wearable sensor module comprising of a hermetically encapsulated, high precision accelerometer contact microphone (ACM) which enables both episodic and longitudinal assessment of lung sounds, breathing patterns and respiratory rates using a single integrated sensor. This enhanced ACM sensor leverages a nano-gap transduction mechanism to achieve high sensitivity to weak high frequency vibrations occurring on the surface of the skin due to underlying lung pathologies. The performance of the ACM sensor was compared to recordings from a state-of-art digital stethoscope, and the efficacy of the developed system is demonstrated by conducting an exploratory research study aimed at recording pathological mechano-acoustic signals from hospitalized patients with a chronic obstructive pulmonary disease (COPD) exacerbation, pneumonia, and acute decompensated heart failure. This unobtrusive wearable system can enable both episodic and longitudinal evaluation of lung sounds that allow for the early detection and/or ongoing monitoring of pulmonary disease.

Piezoelectric MEMS resonators possess favorable properties such as strong electromechanical coupling, high Q, and polarized linear transduction, making them ideal for various applications including timing, sensing, and RF communication. However, due to process nonidealities and temperature variations, these resonators characteristics may deviate from their designed frequency and resonant eigenmode, requiring careful compensation for stable and precise operation. Furthermore, certain devices like gyroscopic resonators have two eigenmodes that need to be adjusted for frequency proximity and cross-mode coupling. Therefore, mode shape manipulation can also be important in piezoelectric resonators and will be another focus of this paper. Techniques for frequency and eigenmode control are classified into device- or system-level tuning, trimming, and compensation. This paper will compare and discuss the effectiveness of these techniques in specific applications to provide a comprehensive understanding of frequency and eigenmode control in piezoelectric MEMS resonators, aiding the development of advanced MEMS devices for diverse applications.

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnosis relies on subjective lung auscultation by physicians. Enabling this capability via a low-profile, objective wearable device for remote patient monitoring (RPM) could offer pre-emptive, accurate respiratory data to patients. With this goal as our aim, we used a low-profile accelerometer-based wearable system that utilizes deep learning to objectively detect wheezing along with respiration rate using a single sensor. The miniature patch consists of a sensitive wideband MEMS accelerometer and low-noise CMOS interface electronics on a small board, which was then placed on nine conventional lung auscultation sites on the patient’s chest walls to capture the pulmonary-induced vibrations (PIVs). A deep learning model was developed and compared with a deterministic time–frequency method to objectively detect wheezing in the PIV signals using data captured from 52 diverse patients with respiratory diseases. The wearable accelerometer patch, paired with the deep learning model, demonstrated high fidelity in capturing and detecting respiratory wheezes and patterns across diverse and pertinent settings. It achieved accuracy, sensitivity, and specificity of 95%, 96%, and 93%, respectively, with an AUC of 0.99 on the test set—outperforming the deterministic time–frequency approach. Furthermore, the accelerometer patch outperforms the digital stethoscopes in sound analysis while offering immunity to ambient sounds, which not only enhances data quality and performance for computational wheeze detection by a significant margin but also provides a robust sensor solution that can quantify respiration patterns simultaneously.