毫米波三维异质异构集成技术的进展与应用

三维异质异构集成技术是实现电子信息系统向着微型化、高效能、高整合、低功耗及低成本方向发展的最重要方法,也是决定信息化平台中微电子和微纳系统领域未来发展的一项核心高技术。文章详细介绍了毫米波频段三维异质异构集成技术的优势、近年来的发展趋势以及面临的挑战。利用硅基MEMS 光敏复合薄膜多层布线工艺可实现异质芯片的低损耗互连,同时三维集成高性能封装滤波器、高辐射效率封装天线等无源元件,还能很好地处理布线间的电磁兼容和芯片间的屏蔽问题。最后介绍了一款新型毫米波三维异质异构集成雷达及其在远距离生命体征探测方面的应用。     

Microstructure,mechanical, tribological,and oxidizing properties of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings with different modulated thicknesses

Multilayer structure design is one of the most promising methods for improving the comprehensive performance of AlCrN-based hard coatings applied to cutting tools. In this study, four types of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings, with different modulated thicknesses, were deposited to investigate their microstructure, mechanical, tribological, and oxidizing properties. All multilayer coatings exhibited grain growth along the crystallographic plane of (200) with a NaCl-type face-centered cubic (FCC) structure. The results show that, as the modulation thickness decreases from ～35 nm to ～10 nm, (1) the grain refinement effect is increasingly evident; (2) all multilayer coatings show a hardness of >30 GPa and an elastic modulus of >300 GPa. Both the ability to resist elastic strain to failure and the plastic deformation of multilayer coatings increase. In addition, their resistance to cracking reduces; (3) the wear rates of these multilayer coatings reduce successively from 1.78 × 10^?16 m³ N^?1 m^?1 to 7.7 × 10^?17 m³ N^?1 m^?1. This is attributed to an increase in self-lubricating VO_x and a decrease in adhesives from the counterparts; (4) the best high-temperature oxidation resistance was obtained for the multilayer coating with a modulated thickness of ～15 nm.     

High ultraviolet transparent conducting electrodes formed using tantalum oxide/Ag multilayer

We investigated the optical and electrical properties of Ta₂O₅/Ag/Ta₂O₅ films as functions of the thicknesses of the Ta₂O₅ and Ag layers. It was found that with an increase in the thicknesses of the Ta₂O₅ and Ag layers from 10 to 40 nm and from 12 to 24 nm, respectively, the sheet resistance, carrier concentration, electron mobility, and resistivity of the Ta₂O₅/Ag/Ta₂O₅ film varied from 2.02 to 8.95 Ω/sq, 5.74 × 10²¹ to 2.92 × 10²² cm^–3, from 13.21 to 24.07 cm²/V·s, and from 8.89 × 10^-6 to 8.24 × 10^-5 Ω cm, respectively. The average transmittance (T_av) of the multilayer samples ranged from 57.18% to 93.99%, and it depended on the Ta₂O₅ and Ag layer thicknesses. The highest T_av of 93.99% was observed for the film with 35 nm thick Ta₂O₅ and 18 nm thick Ag layers, and the peak Haacke's figure of merit (157.04 × 10^–3 Ω^–1) was obtained for 20 nm thick Ta₂O₅ and 21 nm thick Ag layers. Ta₂O₅ (100 nm) and Ta₂O₅/Ag/Ta₂O₅ (20 nm/21 nm/20 nm) samples had optical bandgaps of 4.70 and 4.45 eV, respectively. Film Wizard simulations were conducted to understand the dependence of the transmittance of the multilayer on the thicknesses of the Ta₂O₅ and Ag layers, and phasor analyses were performed to determine how the transmittance of the Ta₂O₅/Ag/Ta₂O₅ (20 nm/21 nm/20 nm) film depended on the Ta₂O₅ layer's thickness.     

Alternating Multilayer Structural Epoxy Composite Coating for Corrosion Protection of Steel

Epoxy composite coatings filled with fillers have been used extensively as anticorrosion materials. In this study, an alternating multilayer structure is designed to obtain multifunctional epoxy resin composite coating based on stepwise coating method via adding graphene and α‐alumina. Their mechanical properties, thermal conductivity, dielectric and anticorrosion properties are characterized. The toughness and the thermal conductivity clearly increase, while the dielectric properties decrease approximately to zero when the filler mass fraction increases from 0.00% to 0.15%. The whole corrosion process is controlled by electrochemical reaction, and the fillers effectively block the corrosive medium, thus improving the anticorrosion performance of the composite coating.     

基于多层感知器的气液两相流流型识别方法

通过对电阻层析成像数据采集原理和深度学习网络的研究,提出了一种基于阵列电阻值和多层感知器深度学习网络相结合的流型识别方法。利用电阻层析成像系统中的16个电极传感器来获取流型样本数据,并构建出流型识别数据库,然后对多层感知器深度学习网络进行训练,获得可以识别不同流型的网络。实验结果表明,采用阵列电阻值结合多层感知器网络对流型进行学习和识别的方法,流型识别准确率可以达到95%,解决了流型图像生成过程与数据特征预选过程中流型特征损失的问题,流型识别性能得到了提高。     

Advanced visible-light photocatalytic property of biologically structured carbon/ceria hybrid multilayer membranes prepared by bamboo leaves

Biologically structured carbon/cerium dioxide materials are synthesized by biological templates. The microscopic morphology, structure and the effects of different oxidation temperatures on materials are characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) ultraviolet-visible light spectrum (UV–Vis) and X-ray Photoelectron Spectroscopy (XPS). Moreover, by splitting water under visible light irradiation, the hydrogen production is measured to test the photocatalytic property of these materials. The results show that materials made with bamboo biological templates which are immersed in 0.1 mol L^?1 of cerium nitrate solution, then carbonizated in nitrogen (700 °C) and oxidized in air (500–600 °C), can obtain the biological structure of bamboo leaves. The product is in the composition of hybrid multilayer membrane, which one is carbon membrane form plant cell carbonation and another is ceria membrane by nanoparticle self assembly. The best oxidation temperature is 550 °C and the band gap of carbon/cerium dioxide materials synthesized at this optimum oxidation temperature could be reduced to 2.75 eV. After exposure to visible light for 6 h, the optimal hydrogen production is about 302 μmol g^?1, which is much higher than that of pure CeO₂.     

Multilayer thermal object identification in frequency domain using IR thermography and vector fitting

This paper deals with the identification of the thermal parameters of multilayer objects using the concept of thermal impedance. In order to perform such identification, temperature evolution in time is obtained by an infrared camera after power excitation is applied in the investigated structure. Infrared thermography offers the advantage of being a noncontact temperature detection and measurement method. In many practical cases, it is impossible to use contact temperature measurements. Typically, the power in the form of a step function is applied. In order to calculate the thermal impedance of an object, temperature and power are converted into the frequency domain using the Laplace transform for s = jω. Then, the poles of the thermal impedance are identified using vector fitting, which allows calculating the thermal impedance as a sum of partial fractions. This corresponds directly to the Foster network of a thermal object. In addition, the vector fitting method offers much better convergence in comparison with other methods using the polynomial rational approximation of thermal impedance. A considerable improvement of the numerical Laplace transform in high frequency range is proposed. In this approach, the variable s = jω is replaced by , and then, the integration result is corrected by the Taylor series. It leads to a kind of filtering of the temperature signal.     

Indirect adaptive control of nonlinear system via dynamic multilayer neural networks with multi‐time scales

This paper deals with adaptive nonlinear identification and trajectory tracking problem via dynamic multilayer neural network with different time scales. By means of a Lyapunov‐like analysis, we determine stability conditions for the on‐line identification. Then, a sliding mode controller is designed for trajectory tracking with consideration of the modeling error and disturbance. The main contributions of the paper lie in the following aspects. First, we extend our prior identification results of single‐layer dynamic neural networks with multi‐time scales to those of multilayer case. Second, the e‐modification in standard use in adaptive control is introduced in the on‐line update laws to guarantee bounded weights and bounded identification errors. Third, the potential singularity problem in controller design is solved by using new update laws for the NN weights so that the control signal is guaranteed bounded. The stability of proposed controller is proved by using Lyapunov function. Simulation results demonstrate the effectiveness of the proposed algorithm. Copyright © 2014 John Wiley & Sons, Ltd.     

Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed model has been analyzed by the root mean squared error (RMSE) function, and correlation coefficient (R). Furthermore, we tested the proposed model using other existing data recorded in Saudi Arabia (testing data). It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia. The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789. The number of recoveries will be 2000 to 4000 per day.     

Effect of MnO2 on the dielectric properties of Nb-doped BaTiO3-(Bi0.5Na0.5)TiO3 ceramics for X9R MLCC applications

MnO₂ and Nb₂O₅ co-doped 0.9BaTiO₃-0.1(Bi_0.5Na_0.5)TiO₃ powders with excellent dielectric properties were fabricated using a conventional solid-state reaction method and sand milling. The doping effects of various amounts of MnO₂ on the dielectric properties were investigated. The results revealed that the dielectric properties greatly depended on the concentration of MnO₂. All the ceramics met the X9R specification. The dielectric loss decreased with an increasing concentration of MnO₂. The specimen with an appropriate amount of 0.2 mol% MnO₂ exhibited the most enhanced properties: high insulation resistance (2.49 × 10¹³ Ω/cm) and improved degradation properties. Multilayer ceramic capacitor (MLCC) chips were prepared by tape casting using a 0.2 mol% Mn-doped 9010BTBNT-based ceramic powder. The capacitance of the MLCC chip was approximately 100 nF, and the dielectric loss was approximately 1.75% at room temperature. The high-temperature accelerated lifetime was over 1000 hours under 250 V (five times the working voltage) and at 230°C, indicating that the MLCC chips possess superior reliability.