This paper studies analytically and numerically the spring softening and hardening phenomena that occur in electrostatically actuated microelectromechanical systems comb drive resonators utilizing folded suspension beams. An analytical expression for the electrostatic force generated between the combs of the rotor and the stator is derived and takes into account both the transverse and longitudinal capacitances present. After formulating the problem, the resulting stiff differential equations are solved analytically using the method of multiple scales, and a closed-form solution is obtained. Furthermore, the nonlinear boundary value problem that describes the dynamics of inextensional spring beams is solved using straightforward perturbation to obtain the linear and nonlinear spring constants of the beam. The analytical solution is verified numerically using a Matlab/Simulink environment, and the results from both analyses exhibit excellent agreement. Stability analysis based on phase plane trajectory is also presented and fully explains previously reported empirical results that lacked sufficient theoretical description. Finally, the proposed solutions are, once again, verified with previously published measurement results. The closed-form solutions provided are easy to apply and enable predicting the actual behavior of resonators and gyroscopes with similar structures.

Ultrasonic diagnostics is the earliest way to predict industrial faults. Usually, a contact microphone is employed for detection, but the recording will be contaminated with noise. In this paper, a dataset that contains 10 main faults of pipelines and motors is analyzed from which 30 different features in the time and frequency domains are extracted. Afterward, for dimensionality reduction, principal component analysis (PCA), linear discriminant analysis (LDA), and t-distributed stochastic neighbor embedding (t-SNE) are performed. In the subsequent phase, recursive feature elimination (RFE) is employed as a strategic method to analyze and select the most relevant features for the classifiers. Next, predictive models consisting of k-Nearest Neighbor (KNN), Logistic Regression (LR), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Support Vector Machine (SVM) are employed. Then, in order to solve the classification problem, a stacking classifier based on a meta-classifier which combines multiple classification models is introduced. Furthermore, the k-fold cross-validation technique is employed to assess the effectiveness of the model in handling new data for the evaluation of experimental results in ultrasonic fault detection. With the proposed method, the accuracy is around 5% higher over five cross folds with the least amount of variation. The timing evaluation of the meta model on the 64 MHz Cortex M4 microcontroller unit (MCU) revealed an execution time of 11 ms, indicating it could be a promising solution for real-time monitoring.

Silicon nanowires (SiNWs) have garnered considerable attention in the last few decades owing to their versatile applications. One extremely desirable aspect of fabricating SiNWs is controlling their dimensions and alignment. In addition, strict control of surface roughness or diameter modulation is another key parameter for enhanced performance in applications such as photovoltaics, thermoelectric devices, etc. This study investigates a method of fabricating silicon nanowires using electron beam lithography (EBL) and the deep reactive ion etching (DRIE) Bosch process to achieve precisely controlled fabrication. The fabricated nanowires had a pitch error within 2% of the pitch of the direct writing mask. The maximum error in the average diameter was close to 25%. The simplified two-step method with tight control of the dimensions and surface tunability presents a reliable technique to fabricate vertically aligned SiNWs for some targeted applications.

This letter proposes a method for utilizing a positive photoresist, Shipley 1805, as a sacrificial layer for sub-180 °C fabrication process flows. In the proposed process, the sacrificial layer is etched at the end to release the structures using a relatively fast wet-etching technique employing resist remover and a critical point dryer (CPD). This technique allows high etching selectivity over a large number of materials, including silicon-based structural materials such as silicon-carbide, metals such as titanium and aluminum, and cured polymers. This selectivity, as well as the low processing thermal budget, introduces more flexibility in material selection for monolithic integration above complementary metal oxide semiconductor (CMOS) as well as flexible substrates.

This paper proposes a novel integrated micro-viscometer for engine-oil monitoring. The final solution consists of a capacitive micromachined ultrasonic transducer (CMUT) and an application-specific integrated circuit (ASIC). The CMUT is used to generate and capture acoustic waves while immersed in engine oil. The low power transceiver ASIC is interfaced with the CMUT structure for actuation and reception. An integrated charge pump boosts the supply voltage from 3.3 to 22 V to generate the DC polarization voltage of the CMUT. The receiver has a power consumption of 72 µW with an input-referred noise current of 3.2$\frac{pA}{\sqrt{Hz}}$ and a bandwidth of 7 MHz. The CMUT array occupies an area of 3.5 × 1 mm, whereas the ASIC has a chip area of 1 × 1 mm. The system was tested using engine oils of different types and ages at different temperatures. Measurement results show a significant frequency shift due to the dynamic viscosity change that occurs as oil ages. A shift of −1.9 kHz/cP was measured, which corresponds to a shift of 33 Hz/mile. This work paves the way for high accuracy-integrated solutions for oil condition monitoring and is expected to play a significant role in a more economic and environmentally friendly usage of oil.

This paper presents a new MEMS varactor that uses repulsive actuation to achieve an ultra-linear capacitance-to-voltage response. The approach proposed involves actuating the moveable electrode away from the fixed electrode, instead of the conventional closing-the-gap direction. This increasing-gap movement reduces the capacitance as the actuation voltage increases. The MEMS variable capacitor is fabricated using PolyMUMPs technology and exhibits an excellent linearity factor of 99.7% in capacitance-to-voltage response, and a capacitance tuning ratio of 11× was achieved. The proposed strategy will enable the development of high-performance MEMS-based tunable devices for various applications.