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首页> 外文会议>2013 Proceedings - Annual Reliability and Maintainability Symposium >Monte Carlo evidence for need of improved percolation model for non-weibullian degradation in high-#x03BA; dielectrics
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Monte Carlo evidence for need of improved percolation model for non-weibullian degradation in high-#x03BA; dielectrics

机译：蒙特卡洛证据表明需要改进的渗流模型以解决高κ电介质中的非韦氏降解

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Dielectric breakdown is one of the critical failure mechanisms and showstopper for ultra-large scale integrated (ULSI) circuits as it impacts the performance and functioning of the transistor, which is the fundamental unit governing the operation of all the advanced microprocessors that we have today. As a reliability engineer, it is essential that the failure mode and mechanism be best described using statistical distributions that correlate with the physical mechanism and driving forces causing failure. In many cases, the distributions used to represent the time to failure data are empirically assumed, without carefully considering its implications on the extrapolated predictions of field lifetime. Application of a wrong distribution can give lifetime estimates that vary by many orders of magnitude, which nullify the very purpose of the reliability study in itself. The Weibull distribution is commonly used to describe random defect generation induced percolation failure of the oxide (dielectric) by means of the “weakest link” phenomenology [1, 2]. While the assumption of a Weibull distribution is well justified for silicon oxide (SiO2) and silicon oxynitride (SiON) materials [3, 4], the application of the same stochastics for high permittivity (high-κ) dielectrics is questionable [5] – [7]. This is fundamentally attributable to the different microstructure of the grown / deposited dielectrics, which we will discuss in detail, along with strong physical analysis evidence. We will present further evidence using Kinetic Monte Carlo (KMC) simulations to explain the origin of the non-Weibullian trends observed. The key motivation of this study is to caution microelectronics reliability scientists against the use of standard statistical distributions for all scenarios. We may have to resort to the need for non-standard distributions or selectively use the standard distributions only over confined percentile ranges, as material- and device failure mechanisms become increasingly complex and interdependent in nanoscale integrated circuits.
机译：介电击穿是关键的故障机制之一，对于超大规模集成电路（ULSI）来说，它是最重要的，因为它会影响晶体管的性能和功能，而晶体管是控制当今所有高级微处理器运行的基本单位。作为可靠性工程师，必须使用与物理机制和引起故障的驱动力相关的统计分布来最好地描述故障模式和机制。在许多情况下，凭经验假设用来表示失效时间数据的分布，而没有仔细考虑其对现场寿命外推预测的影响。错误分配的应用可能会导致寿命估算值变化多个数量级，从而使可靠性研究本身的目的无效。 Weibull分布通常用于通过“最弱链接”现象描述随机缺陷生成引起的氧化物（介电质）渗滤破坏[1，2]。尽管对于氧化硅（SiO 2 ）和氧氮化硅（SiON）材料来说，威布尔分布的假设是合理的[3，4]，但对于高介电常数（高κ ）电介质是有问题的[5] – [7]。从根本上讲，这可归因于生长/沉积的电介质的不同微观结构，我们将对此进行详细讨论，并提供有力的物理分析证据。我们将使用动力学蒙特卡洛（KMC）模拟来提供进一步的证据，以解释观察到的非威布尔趋势的起源。这项研究的主要动机是提醒微电子可靠性科学家不要在所有情况下都使用标准统计分布。随着材料和设备故障机制在纳米级集成电路中变得越来越复杂和相互依赖，我们可能不得不诉诸于非标准分布的需求或仅在有限的百分位数范围内选择性地使用标准分布。

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