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 SourceMeasure-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.

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Variability of nanometer-size devices is a major challenge for circuit design. Apart from the as-fabricated variability, the postfabrication degradation introduces a timedependent variability, originating from statistical distribution of charge location and number. The existing characterization techniques do not always capture the maximum degradation. Some of them does not separate the device-to-device variation from the charging fluctuation within the same device, either. The objective of this paper is to develop a new analysis method for characterizing time-dependent device-to-device variation, accounting for within-device fluctuation (TVF). The TVF captures the maximum degradation, separate device-to-device variation from withindevice fluctuation, and reduce the data points by three orders of magnitude. It is shown that the popular data acquisition at discrete time points does not capture the fluctuation well and drain current must be measured continuously. The TVF shows that degradation has two components-a fluctuation with time and one whose discharge is not observed under a given bias. Although both of them increase with stress time, the correlation between them is weak, indicating two different origins.

Abstract-The Z 2 -FET operation as capacitor-less DRAM is analyzed using advanced 2D TCAD simulations for IoT applications. The simulated architecture is built based on actual 28 nm FD-SOI devices. It is found that the triggering mechanism is dominated by the front-gate bias and the carrier's diffusion length. As in other FB-DRAMs, the memory window is defined by the ON voltage shift with the stored body charge. However, the Z 2 -FET's memory state is not exclusively defined by the inner charge but also by the reading conditions.