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电磁脉冲冲击下工业芯片LDMOS器件可靠性仿真方法研究
朱亚星, 赵东艳, 陈燕宁, 刘芳, 吴波, 王凯, 梁英宗, 郁文, 池泊明, 连亚军
集成电路与嵌入式系统 ›› 2024, Vol. 24 ›› Issue (10) : 25-30.
PDF(3885 KB)
PDF(3885 KB)
电磁脉冲冲击下工业芯片LDMOS器件可靠性仿真方法研究
Research on reliability simulation method for industrial-chip-featured LDMOS devices under elctromagntic pulse impact
电磁脉冲冲击环境下工业芯片LDMOS(Laterally Diffused Metal Oxide Semiconductor)器件的可靠性仿真通常基于周期性单TLP(Transmission Line Pulse)脉冲信号的参数作为瞬态输入条件,利用商业TCAD(Technology Computer-Aided Design)软件基础退化模块进行仿真。由于仿真条件简单,难以覆盖工业芯片常见的复杂电磁脉冲环境,器件的可靠性寿命预期值与实际经验值之间相差巨大,导致芯片的稳定性很难得到精准评估。本研究结合期望最大算法和可靠性应力转化理论,在进行可靠性仿真前对复杂电磁脉冲信号进行预处理,降低整体电磁信号的复杂度,提高仿真效率,增强建模的可靠性。系列过程可作为电磁场仿真模块补充嵌入到主流的TCAD仿真软件,提高工业芯片器件可靠性仿真精准度。
The reliability simulation of industrial-chip-featured LDMOS (Laterally Diffused Metal Oxide Semiconductor) devices under electromagnetic pulse (EMP) impact can be accomplished using the commercial TCAD (Technology Computer-Aided Design) software, which employs periodic TLP (Transmission Line Pulse) signals as transient input conditions for the degradation module. Due to the simplicity of this simulation, it is challenging to cover the common and complex EMP environments encountered by industrial chips. The expected device lifetime differs significantly from the empirical value, making it difficult to accurately assess the stability of chips. In this research, we combine the expectation-maximization algorithm and the reliability theory to optimize this process.Before conducting reliability simulations, the complex electromagnetic pulse signal is preprocessed to reduce the overall complexity. The preprocess significantly improves simulation efficiency and enhances the reliability of the modeling. The method can be integrated as a complementary module for mainstream TCAD simulation software when conducting electromagnetic field simulation, thereby improving the accuracy of reliability simulations for industrial chip devices.
电磁脉冲冲击 / LDMOS器件 / 期望最大算法 / 可靠性理论
electromagnetic pulse impact / LDMOS devices / expectation-maximization algorithm / reliability theory
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Complex Morlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal precision and spectral precision. It is typically defined as the "number of cycles," but this parameter is opaque, and often leads to uncertainty and suboptimal analysis choices, as well as being difficult to interpret and evaluate. The purpose of this paper is to present alternative formulations of Morlet wavelets in time and in frequency that allow parameterizing the wavelets directly in terms of the desired temporal and spectral smoothing (expressed as full-width at half-maximum). This formulation provides clarity on an important data analysis parameter, and can facilitate proper analyses, reporting, and interpretation of results. MATLAB code and sample data are provided.Copyright © 2019 Elsevier Inc. All rights reserved.
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