This work presents a novel machine learning assisted microelectromechanical systems multiparameter (temperature and pressure) sensor using a single thermal piezoresistive membrane resonator in air. It uses differential thermal actuation and piezoresistive sensing to achieve dual outputs, i.e., modulated output (resonant frequency modulated temperature/pressure signal) and non-modulated output (unmodulated temperature/pressure signal). Optimized location of the resistors boosts actuation efficiency and reduce crosstalk for sensing. Actuation via three resistors results in a Q factor of 457 (6th mode, 1388 kHz). Different machine learning algorithms were studied to decouple temperature and pressure signals from the dual output signals. Experiments show the proposed dual-output decoupling multi-task learning framework reduces root-mean-square errors by up to 65.7% for pressure sensing and 96.7% for temperature sensing compared with 3rd order polynomial fitting, multi-task learning, multi-task learning with efficient channel attention. The dual-output, multiphysics sensing principle can be applied to measure many other parameters under atmospheric pressure, using a single MEMS structure, e.g., mass, humidity, gas concentration, and acoustic pressure.

This study introduces a novel closed-loop near-zero stiffness micro-electro-mechanical system (MEMS) accelerometer. It achieves high, adjustable sensitivity by tuning the buckling behavior of electrothermal microbeams. A closed-loop force feedback control system is implemented for the accelerometer, effectively enhancing its linearity, dynamic range, bandwidth, and operational stability. The control parameters are optimized through system-level modeling. The experiment demonstrates that the closed-loop system enhances linearity and bandwidth by 41.5% and 106%, respectively, compared to the open-loop system. Furthermore, across a temperature range of 20 degrees C-60 degrees C, the closed-loop system decreases output drift by 36%, compared to the open-loop system. This closed-loop control method can be widely applied to various near-zero stiffness MEMS accelerometers (e.g. those with mechanical anti-spring configurations). This research lays the groundwork for future advancements in high-performance sensing technologies.

This work describes a hybrid micro-electro-mechanical-systems (MEMS) microphone integrating capacitive and piezoelectric transduction mechanisms for signal-to-noise ratio (SNR) improvement. A theoretical system-level model was established to characterize the hybrid device, which was fabricated using a silicon-on-insulator (SOI) wafer-based process. The piezoelectric transduction component employs a Si/SiO2/Au/AlN/Pt material stack, while the capacitive transduction part consists of a variable capacitor formed by a silicon handle layer and a silicon device layer. Experimental results at 1 kHz show that the hybrid MEMS microphone achieves sensitivities of -64.3 dB (re: 1 V/Pa) in piezoelectric mode, -54.9 dB (re: 1 V/Pa) in capacitive mode, and -52.4 dB (re: 1 V/Pa) in hybrid mode, with corresponding SNR values of 65.7 dB, 59.8 dB, and 62.2 dB, respectively. To enhance the overall SNR of the hybrid MEMS microphone, a signal fusion technique is applied to the dual synchronized signals, resulting in an enhanced SNR of 66.7 dB, exhibiting a 14.1 dB improvement compared to the 52.6 dB reported in previous work.

This study presents a mechanical self-assembly strategy to fabricate high-performance, CMOS-compatible microscale thermoelectric devices (mu TEDs). Planar mu TEDs are transformed into 3D elevated architectures by exploiting intrinsic stress gradients in stacked thin films. These elevated structures generate substantial internal temperature differences (LTG) without an external cooling system or complex processing. To demonstrate this concept, chromium-nickel thermocouples, with respectively optimized thin-film power factors of approximately 1600 and 2900 mu W center dot m-1 center dot K-2, are used. Finite element method (FEM) simulations considering the fabrication constraints serve to guide geometry design. A surface topography control method enables precise tuning of thermocouple elevation height to maximize LTG, and output power as a result. The directly microfabricated on-chip devices deliver up to 2.5 mV across sub-mm2 areas at a substrate temperature of 70 degrees C and thermally floating cold junctions, with power densities exceeding 1 mu W center dot cm-2 in passive cooling mode and 3.5 mu W center dot cm-2 under mild forced convection. Simulations match experimental performance within 17 % error, proving the robustness of the design. Fully compatible with standard CMOS processes and materials, this approach offers a scalable platform for integrating high-performance thermoelectric materials into microelectronic systems for low-power energy harvesting and thermal management.

We present a device-agnostic hybrid (digital-physical) synchronization platform. Starting from a single-DoF AlN BAW resonator measured in ambient air with no compensation, we progressively improve stability by colocking a digitally synthesized resonator in a Huygens-clock-inspired anti-phase mode. A supervisory controller (i) tracks the physical resonator's drift and (ii) regulates the amplitude ratio to $\approx 1$, sustaining synchronization for more than 12 h under uncontrolled ambient conditions, without pressure or temperature compensation or stabilization. This reduces both short-term bias instability and long-term Allan deviation of the physical resonator's frequency (e.g., bias stability improves from $2.04 \times 10^{-8}$ to $1.20 \times 10^{-9}$ at $\tau \approx 0.16 \mathrm{s}; \sigma \mathrm{y}(\tau)$ remains between 1 and 2 decades lower up to 103 s). While MEMS synchronization and lock-range engineering are established, our advance is a digital twin that follows drift and preserves gain and frequency symmetry, expanding the usable synchronization range without analog tuning for any resonant MEMS device.

Capacitive-actuation and capacitive-detection (CACD) mechanisms have been adopted in MEMS electric current sensors (ECSs) for their favorable dynamic range (DR). However, parasitic capacitances inherent in capacitive transduction can degrade resolution and power efficiency. To address this limitation, this letter presents a high-performance ECS using capacitive-actuation and piezoresistive-detection (CAPD) architectures with optimized transduction efficiency. The ECS features a dual clamped-clamped beam with two symmetrically arranged piezoresistive gauges. The input current induces thermal strain in the first gauge, which is then transduced into a frequency shift detected by the second gauge. By optimizing the thermal bias applied to the sensing gauge, the transduction gain is maximized, enhancing resolution while minimizing power consumption. Experimental results demonstrate a 2.1-fold improvement in resolution to 9.1 nA/ $\surd $ Hz and a DR of 106.8dB, establishing a new benchmark for MEMS ECSs.[2025-0180]

This work reports a piezoelectric MEMS resonator featuring a curved beam structure designed to enable favorable frequency stability through two temperature coefficient of frequency (TCf) regulation methods, i.e., TCf manipulation using beat frequencies among different vibration modes and TCf amelioration exploiting the newly discovered temperature-insensitive region. Five distinct modes of the device are selected for testing over dynamic temperature changes from 25°C to 75°C. In brief, by utilizing the output frequency of Mode 1 beating with Mode 2, a stability of 127 parts per billion (ppb) was achieved despite continuous temperature fluctuations, significantly outperforming the operation with solely Mode 1. As for Mode 4, temperature control at its temperature abnormal region extremum point (@ 55°C) yielded optimal stability of 2.0 ppb at 2.510 s. These results confirm that the beat frequency technique and targeted thermal regulation effectively enhance frequency stability in MEMS resonators, particularly for those designed with multiple vibration modes.

Low-carbon thin strip steels used in umbrella manufacturing exhibit limitations in strength and corrosion resistance. Traditional processes involve trade-offs between cost, performance, and environmental pollution. The INO strategy enables cost-controlled, high-performance green manufacturing. This study focuses on the microstructure, mechanical behavior, and corrosion resistance of the surface strengthening layer in HR2 steel, based on nitriding parameter regulation within the INO strategy. Results indicated that synergistic enhancement of strength (max ~276%) and corrosion resistance (max ~5414%) can be achieved. The reduction in grain size within the nitriding layer is attributed to stress deformation and grain boundaries pinning by nitrided phases. Strength is negatively correlated with the fraction of porous layer in the nitriding layer, concerning the evolution of dislocation and recrystallization. The nitriding layer exhibited high-density dislocation tangles and segments in the conventional sample. Deep-layer treatment promoted dislocation transformation into interactive walls. In addition, conventional treatment promoted greater grain orientation variations between the nitriding and diffusion layers, while deep-layer treatment generated similar orientations across both layers. The interaction between recrystallization and nitrided phases is key to strength optimization. The combination of favorable {100} textures with a compact layer is crucial for enhancing corrosion resistance. This work can provide new perspectives for optimizing the properties of thin strip steel.

Silicon-based Micro-electromechanical Systems (MEMS) resonators face stability challenges due to their temperature susceptibility, which impedes the advancement towards high-precision applications. This work reports a multi-modal curved-beam piezoelectric resonator that enhances frequency stability through engineered irregular geometry and mechanical nonlinearity. Utilizing a standard Silicon-On-Insulator (SOI) - Aluminum Nitride (AlN) process, the proposed device engenders 17 vibration modes within 5 MHz, addressing the detection constraints and information extraction of non-inplane modes for capacitive counterparts and circumventing the needs of vacuum encapsulation. In addition, owing to the inimitable temperature coefficient of frequency (TCf) insensitive plateaus discovered in high-frequency modes (Mode 16 and Mode 18), a novel stability enhancement strategy has emerged. Through open-loop sweeps and phase-locked loop (PLL) tracking, it is suggested that these plateaus likely stem from modal coupling triggered by mechanical nonlinearities. This behavior, reminiscent of frequency veering, potentially enables energy redistribution between modes, leading to the resonance frequency deviating from the intrinsic thermal drift trajectory of silicon. Experimental results show that Mode 16 achieves a stability of 17.4 ppb at 46.390 s at a 62 °C plateau under ±1 °C fluctuations and reaches 2.0 ppb under stringent temperature regulation. Mode 18 reaches a peak stability of 37.9 ppb at 43 °C. This innovative approach presents a promising avenue for developing high-precision frequency references without the need for intricate TCf compensation, providing considerable potential for the evolution of next-generation silicon micro-resonators and enhancing their capabilities as stable timing sources in various applications.

This paper presents a novel two-dimensional (2D) model based on partial differential equations (PDEs) to characterize the input-output response of the dual-axis micro thermal convective tilt ( mu TCT) sensors. The proposed model enables highly efficient performance analysis of mu TCT sensors with a computational time of 3 minutes. Based on the theoretical framework, the key parameters of the mu TCT sensor, including the heater-detector distance, sensor length, film thickness, and cavity depth, are optimized to achieve high sensitivity and low power consumption. Furthermore, the model provides a reliable method for quantifying cross-axis crosstalk relative to the sensitivity of the sensitive axis. Accordingly, a mu TCT sensor has been designed and fabricated, demonstrating bidirectional inclination detection over +/- 180 degrees range with a power consumption of 3.29mW. Measured sensitivities along x-axis and y-axis were measured as 37.53 mV/degrees and 43.03 mV/degrees, respectively. Good agreement between experimental results and theoretical predictions validates the model's accuracy and feasibility. With a normalized sensitivity of 13.07 mV/degrees/mW, the mu TCT sensor surpasses the previous micro tilt sensors by >3 times, while maintaining the cross-axis crosstalk error ( delta ) below 5%. This study establishes the developed 2D model as an indispensable tool for the design and optimization of high-performance dual-axis mu TCT sensors. The significant performance improvements highlight the model's critical role in advancing micro tilt sensor technology for demanding applications such as high-precision attitude detection in industrial IoT systems. [2025-0218]

In this work, the effects of Si and Co additions on the mechanical properties, electrical conductivity, corrosion resistance and microstructure of Cu-Cr-Zr alloy were studied. The peak-aged Cu-Cr-Zr-Si-Co alloy exhibits an ultimate tensile strength of 686.73 MPa, a hardness of 233.14 HV, and an electrical conductivity of 71.72%IACS. Compared with the peak-aged Cu-Cr-Zr alloy, the ultimate tensile strength and hardness increase by 20.1% and 13.2% respectively, while the electrical conductivity only decreases by 5.3%. The corrosion resistance of Cu-Cr-Zr alloy can be effectively enhanced by the combined addition of Si and Co, as evidenced by a 37.9% decrease in corrosion current and a 30.7% increase in polarization resistance. In 3.5 wt.% NaCl solution, both alloys develop corrosion films with a double-layer structure. The charge transfer resistance of the inner layer is much higher than that of the outer layer, which is the key factor dominating the corrosion resistance. Compared with the Cu-Cr-Zr alloy, the Cu-Cr-Zr-Si-Co alloy contains more numerous and finer Cr-rich precipitates, along with the formation of Cu4Zr precipitates. Moreover, the Cu-Cr-Zr-Si-Co alloy exhibits a larger grain boundary length per unit area and a higher proportion of Σ3 grain boundary. The enhanced mechanical properties of the Cu-Cr-Zr-Si-Co alloy are attributed to the synergistic effects of grain boundary strengthening, Orowan strengthening, and modulus strengthening.

This study introduces a bio-inspired AlN-piezoelectric MEMS microphone that showcases a cantilever structure offering adjustable performance, fully emulating the dynamics and tunability observed in the basilar membrane of the mammalian cochlea. Through the incorporation of piezoelectric and converse piezoelectric effects alongside dual parametric modulation mechanisms, the device successfully replicates three crucial aspects of cochlear mechanics: i) sensory transduction characteristic of inner hair cell (IHC); ii) local stiffness modulation enabled by outer hair cell (OHC) somatic motility; and iii) energy redistribution in coupled-system recapitulating the energy transfer of cochlear traveling wave dynamics. The device performance was systematically characterized through electrical characterizations, optical analysis, and acoustic measurements. Experimental results demonstrate a baseline sensitivity of -25.38 dB/Pa and signal-to-noise ratios up to 79.28 dB within an operation bandwidth from 1.755 to 2.261 kHz (3 dB cut-on and cut-off bandwidth), while the quality factor (Q) can be tuned to a value ranging from -55.38% to 180.10% of initial values, representing a 124.72% tuning span. In essence, the critical innovations encompass: i) a MEMS microphone that pioneers the first fully mimicking simultaneous sensing/tuning functionality of the mammalian cochlea, through piezoelectric and converse piezoelectric effects; ii) a combination of two novel tuning mechanisms, i.e., AC (through parametric modulation) and mechanical coupling, are applied without the necessity for mechanical structure modification. It can be envisioned that such a technology enables next-generation hearing aids with bio-inspired auditory adaptation, bridging a critical gap in prosthetic sound processing, while also catering to the ever-increasing demands of intelligent acoustic sensors.

This work proposes a piezoelectric -capacitive dual-mode micro-electromechanical system (MEMS) microphone with peripheral electrostatic transduction. Finite element analysis is used to investigate the contribution of the peripheral electrode configuration to the response characteristics of the proposed piezoelectric-capacitive MEMS microphone (PCMM). Piezoelectric transduction is achieved using a conventional piezoelectric stack with multiple layers. The capacitive transduction part is implemented through a peripheral electrode formed by the overlapping circumferential region between the silicon substrate and the device layer. The proposed PCMM shows a measured sensitivity of -51.1 dB (1 V/Pa) and a signal-to-noise ratio (SNR) of 49.6 dB at 1kHz (1 Pa) for the piezoelectric part, and -51.3 and 68.9 dB at 1kHz, respectively, for the capacitive part. Through the integration of dual outputs from the above two modes, the hybrid mode achieves measured sensitivities and SNR of -45.3 dB (1 V/Pa) and 55.3 dB (1kHz). The A-weighted SNR in the piezoelectric, capacitive, and hybrid modes is 10.53, 30.58, and 16.27 dB(A), respectively. At 145.6-dB SPL, the hybrid mode shows lower total harmonic distortion (THD) (1.7%) than the piezoelectric (2.6%) and capacitive (2.3%) modes.

In this study, the Mg-2.5Nd-1.5Gd-0.2Zn-0.6Zr alloy was casted, homogenized and extruded into bars. Evolution of microstructure and texture, and tension-compression properties of the extrudate were examined. The as-cast experimental alloy was composed of equiaxed alpha-Mg grains enclosed by discontinuous alpha-Mg + Mg-12(Nd, Gd) eutectics, needle-like Mg12Nd phases and quadrate-like Mg5Gd phases within the alpha-Mg matrix. After homogenized at 515 degrees C for 18 h, a small amount of residual Mg-12(Nd, Gd) phases could be found along grain boundaries, and Zn2Zr3 phases were newly detected. Broken Zn2Zr3 phases, several Mg12Nd particles and many shear bands were observed in the initial extrusion stage. Strong basal texture with < 10_10 > parallelling to the extrusion direction was obtained. Several off-basal oriented dynamic recrystallized (DRXed) grains within shear bands were also detected, which were found to be related to the activation of pyramidal dislocations. With the processing of extrusion, basal texture was still the main texture component, while rare earth (RE) texture with < 2_1_11 > parallelling to the extrusion direction was found, which was related with the increasing DRX fraction. It was revealed that CDRX dominated the microstructural development at this position, and segregation of solute atoms and large amounts of non-basal dislocations were detected, leading to the formation of RE texture in DRXed grains. Almost fully DRXed grains was obtained in the final stage, RE texture at this position exhibited < 2_1_11 > and < 2_1_14 > parallelling to the extrusion direction. Apart from broken Zn2Zr3 phases, higher number of Mg12Nd and Mg5Gd were observed along grain boundaries or within the matrix, resulting in the limited growth of grain size. The extruded alloy exhibited low tension-compression yield asymmetry at room temperature. Besides, obvious yield drop and yield plateau presented in the tensile curve, which were caused by solute atoms, fine grain size and RE texture.

Recently, modifying texture characteristics has been regarded as a key strategy for achieving enhanced mechanical isotropy and excellent formability of Mg alloy sheets. In this work, the Mg-2Zn-3Li-1Gd alloy sheet with weak and diffused texture is successfully prepared via warm rolling (WR) and subsequent annealing, achieving a superior synergy of isotropy and formability (Erichsen value of 7.8 mm) in mechanical properties. Quasi-in-situ electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM) analyses demonstrate that diverse types of dislocations can be activated during the WR process along the transverse direction (TD). During annealing, recrystallized grains exhibit a diverse orientation distribution under the synergistic influence of various dislocations, which facilitates the development of weak and diffused texture. In addition, first-principles calculations have demonstrated that the co-segregation of Zn and Gd at grain boundaries (GB) reduces GB energy and strengthens atomic bonding, which suppresses crack initiation and further improves the formability. The outcomes of this work can provide worthwhile insights for designing formable and ductile Mg alloy sheets, which also offer new perspectives for mitigating planar anisotropy in mechanical behavior.

The effect of Zn/Ca ratio on the microstructure, mechanical properties, and deformation behavior of as-cast Mg-2Zn-0.2Zr-0.1Mn-xCa (x = 0, 0.2, 0.5, and 1 wt%) alloys is systematically investigated. The results show that Ca addition significantly refines the grain size and alters the secondary phase constitution, promoting the formation of Ca2Mg6Zn3 phases along grain boundaries. An optimal strength-ductility synergy is achieved at 0.2 wt% Ca, where the alloy exhibits a yield strength of 102.6 +/- 1.4 MPa, an ultimate tensile strength of 247.5 +/- 3.1 MPa, and an elongation of 30.3 +/- 2.2%. Further increasing Ca content leads to the formation of coarse, continuous second-phase networks, resulting in deteriorated ductility and premature fracture. Detailed analyses combining EBSDassisted slip trace analysis, TEM characterization, and XRD-based dislocation density measurements reveal that the enhanced mechanical performance is closely associated with dislocation evolution. The experimental alloy with 0.2 wt% Ca addition exhibits the highest dislocation storage capacity, which is attributed to the increased activation of non-basal slip systems. In contrast, higher Ca contents show a lower frequency of non-basal slip activity and promote strain localization, leading to reduced work-hardening capability. It is further demonstrated that the deformation behavior is not governed by the nominal Zn/Ca ratio, but by the effective solute content retained in the matrix. Moderate Ca addition results in a higher matrix Zn/Ca ratio due to limited solute consumption by secondary phases, thereby facilitating non-basal slip activation and dislocation interactions. This study provides new insights into the role of solute distribution in regulating dislocation behavior and offers a potential strategy for achieving high strain hardening and strength-ductility synergy in as-cast Mg-Zn-Ca alloys.

In this work, Al-30at.%Sc target and 6061Al backplate were diffusion bonded by spark plasma sintering. The bonding ratio, mechanical properties, electrical conductivity, thermal conduction properties, and microstructure of the bonded target assembly were investigated. Under a bonding pressure of 30 MPa and a holding time of 10 min, as the bonding temperature increased from 460 °C to 580 °C, the interfacial pores gradually closed, the bonding ratio increased from 65.15% to 100%, and the shear strength rose from 21.2 MPa to 94.3 MPa. The electrical and thermal conductivities of the target assembly first improved and then degraded with increasing bonding temperature. At 540 °C, the target assembly exhibited the lowest room-temperature electrical resistivity of 5.65 μΩ·cm, and the optimal thermal conductivity of 86.5–87.8 W/(m·K) within the ambient temperature range of 25 °C to 200 °C. Interdiffusion of Al and Sc atoms during bonding gradually formed a continuous Al3Sc layer at the interface. The wavy morphology of this newly formed Al3Sc layer at the interface with the 6061Al side induced mechanical interlocking, contributing to the enhancement of shear strength. Meanwhile, Mg in 6061Al diffused to the interface and reacted with the detrimental Al2O3 film, forming nanoscale discontinuous layers or particles of MgAl2O4.

Signal fusion between various sensors has been explored to enhance the robustness and resolution, leveraging their complementary characteristics. In general, a higher correlation between sensors leads to more efficient fusion. This work presents a silicon resonant accelerometer (SRA) that enables tunable noise correlation between capacitive and piezoresistive dual transductions. The accelerometer comprises a double clamped beam resonator with piezoresistive gauges and capacitive electrodes, allowing simultaneous transduction outputs of both signals. Through tuning the thermal bias applied to the piezoresistive gauges, the transduction gain of the piezoresistive signal can be tuned, enabling real-time control of the correlation between the two signals. The real-time frequencies demodulated from the signals with variable correlation are fused by using a general 2nd-order Kalman filter algorithm. Experimental results demonstrate that the fused output achieves a resolution of 0.49 mu gl/root Hz. This represents an improvement of approximately 10.45 dB compared with capacitive detection alone. Meanwhile, the fused signal preserves the broad bandwidth of similar to1150 Hz provided by piezoresistive detection. This highlights the effectiveness of noise correlation manipulation for enhancing sensor performance by output signal fusion.