Theoretical and Experimental Study on Nonlinear Failure of an MEMS Accelerometer under Dual Frequency Acoustic Interference.

In order to quantitatively study the interfered output of the accelerometer under an acoustic injection attack, a mathematical model for fitting and predicting the accelerometer output was proposed. With ADXL103 as an example, an acoustic injection attack experiment with amplitude sweeping and frequency sweeping was performed. In the mathematical model, the R-squared coefficient was R2 = 0.9990 in the acoustic injection attack experiment with amplitude sweeping, and R2 = 0.9888 with frequency sweeping. Based on the mathematical model, the dual frequency acoustic injection attack mode was proposed. The difference frequency signal caused by the nonlinear effect was not filtered by the low-pass filter. At a 115 dB sound pressure level, the maximum acceleration bias of the output was 4.4 m/s2 and the maximum amplitude of fluctuation was 4.97 m/s2. Two kinds of methods of prevention against acoustic injection attack were proposed, including changing the damping ratio of the accelerometer and adding a preposition low-pass filter.

A Filtering Algorithm of MEMS Gyroscope to Resist Acoustic Interference.

To reduce the impact of acoustic interference in a microelectromechanical system (MEMS) gyroscope and to improve the reliability of output data, a filtering algorithm based on orthogonal demodulation is proposed. According to the working principle and failure mechanism of a MEMS gyroscope, the sound and angular velocity frequencies are not identical, which lead to a different frequency signal output of the original single-channel demodulation scheme. Therefore, a Q channel demodulation filtering process was added to the origin single-channel demodulation scheme. For the Q channel demodulated signal, a Hilbert transform was used to compensate for the 90 degree phase shift. The IQ dual-channel difference can remove the acoustic interference signal. The simulation results indicate that the scheme can effectively suppress the acoustic interference signal and it can eliminate more than 95% of the impact of sound waves. We assembled the acoustic interference experimental platform, collected the driving and sensing data, and verified the denoising performance with our algorithm, which eliminated more than 70% of the noise signal. The simulation and experimental results demonstrate that the scheme can eliminate acoustic interference signal without destroying angular velocity signal.

Influence of lateral misalignment on the optical rotational Doppler effect.

The discovery of the optical rotational Doppler effect associated with orbital angular momentum of light paves a new way to detect the rotational speed of spinning objects. In this paper, we investigate the influence of lateral misalignment, i.e., the distance between the beam axis of a probe light and the rotation axis of a spinning object, on the rotational Doppler effect. First, we analyze the mechanism of the rotational Doppler effect of optical vortices based on the linear Doppler effect. Specifically, we consider the general case where the center of the optical vortex does not coincide with the rotation axis, and deduce the generalized formula of rotational Doppler shift based on a local scattering model. It is found that the bandwidth of the rotational Doppler signal depends proportionally on the amount of lateral misalignment, whereas the value of rotational Doppler shift remains constant. A proof-of-concept experiment is performed, and the measured results agree well with theoretical predictions. These findings may be useful for practical application of the optical rotational Doppler effect in remote sensing and metrology.

Application and Prospect of Artificial Intelligence Methods in Signal Integrity Prediction and Optimization of Microsystems.

Microsystems are widely used in 5G, the Internet of Things, smart electronic devices and other fields, and signal integrity (SI) determines their performance. Establishing accurate and fast predictive models and intelligent optimization models for SI in microsystems is extremely essential. Recently, neural networks (NNs) and heuristic optimization algorithms have been widely used to predict the SI performance of microsystems. This paper systematically summarizes the neural network methods applied in the prediction of microsystem SI performance, including artificial neural network (ANN), deep neural network (DNN), recurrent neural network (RNN), convolutional neural network (CNN), etc., as well as intelligent algorithms applied in the optimization of microsystem SI, including genetic algorithm (GA), differential evolution (DE), deep partition tree Bayesian optimization (DPTBO), two stage Bayesian optimization (TSBO), etc., and compares and discusses the characteristics and application fields of the current applied methods. The future development prospects are also predicted. Finally, the article is summarized.

Thermodynamic Multi-Field Coupling Optimization of Microsystem Based on Artificial Intelligence.

An efficient multi-objective optimization method of temperature and stress for a microsystem based on particle swarm optimization (PSO) was established, which is used to map the relationship between through-silicon via (TSV) structural design parameters and performance objectives in the microsystem, and complete optimization temperature, stress and thermal expansion deformation efficiently. The relationship between the design and performance parameters is obtained by a finite element method (FEM) simulation model. The neural network is built and trained in order to understand the mapping relationship. Then, the design parameters are iteratively optimized using the PSO algorithm, and the FEM results are used to verify the efficiency and reliability of the optimization methods. When the optimization target of peak temperature, bump temperature, TSV temperature, maximum stress and maximum thermal deformation are set as 100 °C, 55 °C, 35 °C, 180 Mpa and 12 µm, the optimization results are as follows: the peak temperature is 97.90 °C, the bump temperature is 56.01 °C, the TSV temperature is 31.52 °C, the maximum stress is 247.4 Mpa and the maximum expansion deformation is 11.14 µm. The corresponding TSV structure design parameters are as follows: the radius of TSV is 10.28 µm, the pitch is 65 µm and the thickness of SiO2 is 0.83 µm. The error between the optimization result and the target temperature is 2.1%, 1.8%, 9.9%, 37.4% and 7.2% respectively. The PSO method has been verified by regression analysis, and the difference between the temperature and deformation optimization results of the FEM method is not more than 3%. The stress error has been analyzed, and the reliability of the developed method has been verified. While ensuring the accuracy of the results, the proposed optimization method reduces the time consumption of a single simulation from 2 h to 70 s, saves a lot of time and human resources, greatly improves the efficiency of the optimization design of microsystems, and has great significance for the development of microsystems.

Simulations of the Rotor-Stator-Cavity Flow in Liquid-Floating Rotor Micro Gyroscope.

When rotating at a high speed in a microscale flow field in confined spaces, rotors are subject to a complex flow due to the joint effect of the centrifugal force, hindering of the stationary cavity and the scale effect. In this paper, a rotor-stator-cavity (RSC) microscale flow field simulation model of liquid-floating rotor micro gyroscopes is built, which can be used to study the flow characteristics of fluids in confined spaces with different Reynolds numbers (Re) and gap-to-diameter ratios. The Reynolds stress model (RSM) is applied to solve the Reynolds averaged Navier-Stokes equation for the distribution laws of the mean flow, turbulence statistics and frictional resistance under different working conditions. The results show that as the Re increases, the rotational boundary layer gradually separates from the stationary boundary layer, and the local Re mainly affects the distribution of velocity at the stationary boundary, while the gap-to-diameter ratio mainly affects the distribution of velocity at the rotational boundary. The Reynolds stress is mainly distributed in boundary layers, and the Reynolds normal stress is slightly greater than the Reynolds shear stress. The turbulence is in the state of plane-strain limit. As the Re increases, the frictional resistance coefficient increases. When Re is within 104, the frictional resistance coefficient increases as the gap-to-diameter ratio decreases, while the frictional resistance coefficient drops to the minimum when the Re exceeds 105 and the gap-to-diameter ratio is 0.027. This study can enable a better understanding of the flow characteristics of microscale RSCs under different working conditions.

Macroscopic negative differential thermal resistance in the overlapping graphene homojunction structure.

As one of the most potential ways to manipulate heat, thermal functional devices have achieved several breakthroughs in recent years, but are still limited to theoretical simulations. One of its theoretical bases is the existence of the negative differential thermal resistance (NDTR). However, most of the existing systems where the phenomenon of NDTR is found are atomic-level systems. In order to realize the macroscopic NDTR and provide effective theoretical guidance and support for the practical realization of thermal functional devices, we construct the overlapping graphene homojunction model, using the negative thermal expansion property of graphene to modify the overlapping area, and thus regulating the heat flow. The COMSOL-MATLAB co-simulation is used to perform calculations through negative feedback loops. It is found that the NDTR phenomenon exists under certain parameter conditions, which can provide new ideas and bring more opportunities for the experimental realization of nonlinear thermal functional devices.

Architecture of Computing System based on Chiplet.

Computing systems are widely used in medical diagnosis, climate prediction, autonomous vehicles, etc. As the key part of electronics, the performance of computing systems is crucial in the intellectualization of the equipment. The conflict between performance, efficiency, and cost can be solved by choosing an appropriate computing system architecture. In order to provide useful advice and instructions for the designers to fabricate high-performance computing systems, this paper reviews the Chiplet-based computing system architectures, including computing architecture and memory architecture. Firstly, the computing architecture used for high-performance computing, mobile, and PC is presented and summarized. Secondly, the memory architecture based on mainstream memory and emerging non-volatile memory used for data storing and processing are introduced, and the key parameters of memory are compared and discussed. Finally, this paper is concluded, and the future perspectives of computing system architecture based on Chiplet are presented.

Extracorporeal membrane oxygenation for thyroid surgery in patients with severe tracheal stenosis.

Venovenous extracorporeal membrane oxygenation is effective for maintaining gas exchange in patients with respiratory failure or severe tracheal stenosis. Perioperative anesthetic management of severe airway obstruction can be associated with ventilation or intubation difficulties. Consequently, venovenous extracorporeal membrane oxygenation could be an option for treating such patients to avoid potential risks. However, only a limited number of similar cases have been reported. Therefore, we have summarized two cases to provide theoretical and practical references for treating patients with respiratory failure or severe tracheal stenosis using extracorporeal membrane oxygenation.