The application of constant electrical stress to a metal–insulator-semiconductor (MOS) or metal–insulator-metal (MIM) structure can generate multiple breakdown events in the dielectric film. Very often, these events are detected as small jumps in the current–time characteristic of the device under test and can be treated from the stochastic viewpoint as a counting process. In this letter, a wide variety of standard reliability growth models for this process are assessed in order to determine which option provides the best simulation results compatible with the experimental observations. For the generation of the breakdown event arrivals, two alternative stochastic methods for the power-law Poisson process are investigated: first, the inversion algorithm for the cumulative distribution function and second, an on-the-fly method based on the so-called rejection algorithm. Though both methods are equivalent, the first one is more appropriate for data analysis using spreadsheet calculations while the second one is highly suitable for circuit simulation environments like LTSpice. The connection of the selected nonhomogeneous Poisson process with the Weibull model for dielectric breakdown is also discussed.

对金属-绝缘体-半导体 (MOS) 或金属-绝缘体-金属 (MIM) 结构施加恒定的电应力可以在介电薄膜中产生多次击穿事件。通常，这些事件被检测为被测设备的当前时间特性的小跳跃，并且可以从随机的角度将其视为计数过程。在这封信中，评估了该过程的各种标准可靠性增长模型，以确定哪个选项提供与实验观察结果兼容的最佳模拟结果。为了生成故障事件到达，研究了幂律泊松过程的两种替代随机方法：首先是累积分布函数的反演算法，其次是基于所谓拒绝的即时方法算法。尽管这两种方法是等效的，但第一种方法更适合使用电子表格计算进行数据分析，而第二种方法非常适合 LTSpice 等电路仿真环境。还讨论了所选非齐次泊松过程与介电击穿威布尔模型的联系。