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Hot carrier aging and its variation under use-bias: Kinetics, prediction, impact on Vdd and SRAM

机译:热载体老化及其在使用下的变化 - 偏差:动力学,预测,对VDD和SRAM的影响

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As CMOS scales down, hot carrier aging (HCA) scales up and can be a limiting aging process again. This has motivated re-visiting HCA, but recent works have focused on accelerated HCA by raising stress biases and there is little information on HCA under use-biases. Early works proposed that HCA mechanism under high and low biases are different, questioning if the high-bias data can be used for predicting HCA under use-bias. A key advance of this work is proposing a new methodology for evaluating the HCA-induced variation under use-bias. For the first time, the capability of predicting HCA under use-bias is experimentally verified. The importance of separating RTN from HCA is demonstrated. We point out the HCA measured by the commercial Source-Measure-Unit (SMU) gives erroneous power exponent. The proposed methodology minimizes the number of tests and the model requires only 3 fitting parameters, making it readily implementable.
机译:随着CMOS缩小的,热载体老化(HCA)缩放,并且可以再次进行限制的老化过程。这具有激励重新访问的HCA,但最近的作用通过提高压力偏差而重点关注加速的HCA,并且在使用偏差下几乎没有关于HCA的信息。早期作品提出,如果高偏置数据可用于预测使用偏差,则在高偏差下的HCA机制有所不同,质疑。这项工作的关键进展是提出一种评估使用偏差下的HCA诱导的变化的新方法。首次,通过实验验证在使用偏差下预测HCA的能力。证明了分离HCA的RTN的重要性。我们指出商业源 - 措施 - 单位(SMU)测量的HCA提供错误的动力指数。所提出的方法可以最大限度地减少测试的数量,并且该模型只需要3个拟合参数,使其变得易于实现。

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