Microsystems & Nanoengineering最新文献

In this study, a controllable mass‒frequency tuning method is presented using the etching of rib structures on a single-crystal PZT membrane. The rib structures were optimized to reduce the membrane mass while maintaining the stiffness; therefore, the center frequency could be increased to improve the low-frequency bandwidth of microphones. Additionally, this methodology could reduce the modulus and improve the sensitivity for the same resonant frequency, which typically indicates the maximum acoustic overload point (AOP). The PZT film was chosen because of its greater density; the simulation results showed that PZT could provide a greater frequency tuning (24.9%) compared to that of the AlN film (5.8%), and its large dielectric constant enabled the optimal design to have small electrodes at the maximum stress location while mitigating the sacrificial capacitance effect on electrical gain. An analytical model of rib-structure microphones was established and greatly reduced the computing time. The experimental results of the impedance tests revealed that the center frequencies of the six microphones shifted from 74.6 kHz to 106.3 kHz with rib-structure inner radii ranging from 0 μm to 340 μm; this result was in good agreement with the those of the analytical analysis and finite element modeling. While the center frequency greatly varied, the measured sensitivities at 1 kHz only varied within a small range from 22.3 mV/Pa to 25.7 mV/Pa; thus, the membrane stiffness minimally changed. Moreover, a single-crystal PZT film with a (100) crystal orientation and 0.24-degree full width at half maximum (FWHM) was used to enable differential sensing and a low possibility of undesirable polarization. Paired with a two-stage differential charge amplifier, a differential sensing microphone was experimentally demonstrated to improve the sensitivity from 25.7 mV/Pa to 36.1 mV/Pa and reduce the noise from -68.2 dBV to -82.8 dBV.

Airflow sensing plays a pivotal role in numerous fields, including medicine, industry, and environmental monitoring. However, detecting bidirectional airflow using a single sensing unit poses significant challenges. In this work, a miniature airflow sensing device is introduced, utilizing a GaN optical chip integrated with a biomimetic hair structure. The sensing device comprises a monolithic GaN chip that handles both light emission and detection. The biomimetic hairs, constructed from nylon fibers and PDMS film, undergo structural bending in converting airflow signals into optical changes, modulating the light captured by the on-chip detector. The intensity of the airflow directly correlates with the bending extent of the biomimetic hair, facilitating the precise detection of airflow rates through changes in the photocurrent. The integrated device can measure a wide range of airflow rates from -23.87 ms^-1 to 21.29 ms^-1, and exhibit a rapid response time of 13 ms and a detection limit of 0.1 ms^-1. Characterized by its compact size, fast response time, and bidirectional detection ability, the developed device holds immense potential for applications in breath detection, speech recognition, encoding information, and the realization of logic operations.

Tactile sensors play a critical role in robotic intelligence and human-machine interaction. In this manuscript, we propose a hybrid tactile sensor by integrating a triboelectric sensing unit and a capacitive sensing unit based on porous PDMS. The triboelectric sensing unit is sensitive to the surface material and texture of the grasped objects, while the capacitive sensing unit responds to the object's hardness. By combining signals from the two sensing units, tactile object recognition can be achieved among not only different objects but also the same object in different states. In addition, both the triboelectric layer and the capacitor dielectric layer were fabricated through the same manufacturing process. Furthermore, deep learning was employed to assist the tactile sensor in accurate object recognition. As a demonstration, the identification of 12 samples was implemented using this hybrid tactile sensor, and an recognition accuracy of 98.46% was achieved. Overall, the proposed hybrid tactile sensor has shown great potential in robotic perception and tactile intelligence.

MEMS gyroscopes are well known for their outstanding advantages in Cost Size Weight and Power (CSWaP), which have inspired great research attention in recent years. A higher signal-to-noise ratio (SNR) for MEMS gyroscopes operating at larger vibrating amplitudes provides improved measuring resolution and ARW performance. However, the increment of amplitude causes strong nonlinear effects of MEMS gyroscopes due to their micron size, which has negative influences on the performance. This paper carries out detailed research on a general nonlinear mechanism on the sensors using parallel-plate capacitive transducers, which is called the gain nonlinearity in electrostatic actuation. The theoretical model established in this paper demonstrates the actuation gain nonlinearity causes the control-force coupling and brings extra angle-dependent bias with the 4^th component for the whole-angle gyroscopes, which are verified by the experiments carried out on a micro-shell resonator gyroscope (MSRG). Furthermore, a real-time correction method is proposed to restore a linear response of the electrostatic actuation, which is realized by the gain modification with an online parameter estimation based on the harmonic-component relationship of capacitive detection. This real-time correction method could reduce the 4^th component of the angle-dependent bias by over 95% from 0.003°/s to less than 0.0001°/s even under different temperatures. After the correction of actuation gain nonlinearity, the bias instability (BI) of whole-angle MSRG is improved by about 3.5 times from 0.101°/h to 0.029°/h and the scale factor nonlinearity (SFN) is reduced by almost one order of magnitude from 2.02 ppm to 0.21 ppm.

Electrohydrodynamic (EHD) printing has critical merits in micro/nanoscale additive manufacturing because of its ultrahigh resolution and wide ink compatibility, making it an advantageous choice for electronics manufacturing, high-resolution prototyping, and biological component fabrication. However, EHD printing is currently limited by its rather low throughput due to the lack of high-frequency and high-density multi-nozzle printheads. This paper presents a novel EHD printhead with a protruding polymer-based nozzle design. An insulated, hydrophobic, and protruding polymer nozzle array with an appropriate geometric structure can effectively address key problems in multi-nozzle jetting, such as electrical crosstalk, electrical discharge, liquid flooding, and nonuniform jetting. By investigating the influence of the electrical and geometric characteristics of the nozzle arrays on the electrical crosstalk behavior and fabricating the optimized nozzle array via MEMS technology, we achieve an EHD printhead with a large scale (256), high density (127 dpi), and high jetting frequency (23 kHz), and addressable jetting can be realized by adding independently controllable extractors underneath the nozzle array. Many functional materials, such as quantum dots, perovskite, and nanosilver inks, can be ejected into high-resolution patterns through the optimized nozzle array, demonstrating the great prospects of our designed printhead in electronics manufacturing. This MEMS-compatible printhead design lays the foundation for high-throughput fabrication of micro/nanostructures and promotes practical applications of EHD printing in functional electronics and biomedical/energy devices.

Despite the importance of positive and negative pressure sensing in numerous domains, the availability of a single sensing unit adept at handling this dual task remains highly limited. This study introduces a compact optical device capable of swiftly and precisely detecting positive and negative pressures ranging from -35 kPa to 35 kPa. The GaN chip, which serves as a core component of the device, is monolithically integrated with light-emitting and light-detecting elements. By combining a deformable PDMS film coated with a hydrophobic layer, the chip can respond to changes in optical reflectance induced by pressure fluctuations. The integrated sensing device has low detection limits of 4.3 Pa and -7.8 Pa and fast response times of 0.14 s and 0.22 s for positive and negative pressure variations, respectively. The device also demonstrates adaptability in capturing distinct human breathing patterns. The proposed device, characterized by its compactness, responsiveness, and ease of operation, holds promise for a variety of pressure-sensing applications.

With an interest in monitoring the patency of stents that are used to treat strictures in the bile duct, this paper reports the investigation of a wireless sensing system to interrogate a microsensor integrated into the stent. The microsensor is comprised of a 28-μm-thick magnetoelastic foil with 8.25-mm length and 1-mm width. Magnetic biasing is provided by permanent magnets attached to the foil. These elements are incorporated into a customized 3D polymeric package. The system electromagnetically excites the magnetoelastic resonant sensor and measures the resulting signal. Through shifts in resonant frequency and quality factor, the sensor is intended to provide an early indication of sludge accumulation in the stent. This work focuses on challenges associated with sensor miniaturization and placement, wireless range, drive signal feedthrough, and clinical use. A swine specimen in vivo experiment is described. Following endoscopic implantation of the sensor enabled plastic stent into the bile duct, at a range of approximately 17 cm, the signal-to-noise ratio of ~10⁶ was observed with an interrogation time of 336 s. These are the first reported signals from a passive wireless magnetoelastic sensor implanted in a live animal.

The design of the microelectromechanical system (MEMS) disc resonator gyroscope (DRG) structural topology is crucial for its physical properties and performance. However, creating novel high-performance MEMS DRGs has long been viewed as a formidable challenge owing to their enormous design space, the complexity of microscale physical effects, and time-consuming finite element analysis (FEA). Here, we introduce a new machine learning-driven approach to discover high-performance DRG topologies. We represent the DRG topology as pixelated binary matrices and formulate the design task as a path-planning problem. This path-planning problem is solved via deep reinforcement learning (DRL). In addition, we develop a convolutional neural network-based surrogate model to replace the expensive FEA to provide reward signals for DRL training. Benefiting from the computational efficiency of neural networks, our approach achieves a significant acceleration ratio of 4.03 × 10⁵ compared with FEA, reducing each DRL training run to only 426.5 s. Through 8000 training runs, we discovered 7120 novel structural topologies that achieve navigation-grade precision. Many of these surpass traditional designs in performance by several orders of magnitude, revealing innovative solutions previously unconceived by humans.

This paper proposes a novel piezo-MEMS pitch/roll gyroscope that co-integrates piezoelectric and electrostatic effects, for the first time achieves electrostatic mode-matching operation for piezoelectric gyroscopes. Movement of operated out-of-plane (OOP) mode (n = 3) and in-plane (IP) mode (n = 2) are orthogonal, ensuring that the OOP amplitude is not significantly limited by parallel plates set at nodes of IP mode. Therefore, a large OOP driving amplitude actuated by piezoelectric and frequency tuning in the IP sense mode trimmed by electrostatic can be achieved together with a low risk of pull-in, hence releases the trade-off between the tuning range and the linear actuation range. At a tuning voltage of 66 V, the frequency split decreased from 171 Hz to 0.1 Hz, resulting in a 167x times improvement in sensitivity. The mode-matched gyroscope exhibits an angle random walk (ARW) of 0.41°/√h and a bias instability (BI) of 8.85°/h on a test board within a customized vacuum chamber, marking enhancements of 68x and 301x, respectively, compared to its performance under mode-mismatch conditions. The BI performance of the presented pitch/roll gyroscope is comparable to that of the highest-performing mechanically trimmed piezo-MEMS yaw gyroscopes known to date, while offering the unique advantage of lower cost, better mode-matching resolution, and the flexibility of real-time frequency control.

The exploration of multi-dimensional brain activity with high temporal and spatial resolution is of great significance in the diagnosis of neurological disease and the study of brain science. Although the integration of electroencephalogram (EEG) with magnetic resonance imaging (MRI) and computed tomography (CT) provides a potential solution to achieve a brain-functional image with high spatiotemporal resolution, the critical issues of interface stability and magnetic compatibility remain challenging. Therefore, in this research, we proposed a conductive hydrogel EEG electrode with an asymmetrical bilayer structure, which shows the potential to overcome the challenges. Benefiting from the bilayer structure with different moduli, the hydrogel electrode exhibits high biological and mechanical compatibility with the heterogeneous brain-electrode interface. As a result, the impedance can be reduced compared with conventional metal electrodes. In addition, the hydrogel-based ionic conductive electrodes, which are free from metal conductors, are compatible with MRI and CT. Therefore, they can obtain high spatiotemporal resolution multi-dimensional brain information in clinical settings. The research outcome provides a new approach for establishing a platform for early diagnosis of brain diseases and the study of brain science.