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Advanced CMOS technology is highly susceptible to ageing effects such as negative bias temperature instability (NBTI) and process variability. This article focuses on investigating the 'combined impact' of NBTI degradation along with the process, voltage and temperature (PVT) variations on SRAM metrics. These issues impact the performance of SRAM (Static Random Access Memory) cell in many ways but the two main dynamic metrics are critical read-stability and write-ability. The dynamic metrics can, in turn, be characterised by their static metrics, that determine the static noise margins (SNM) of SRAM. The dynamic metrics were analysed for symmetric and asymmetric NBTI degradation of two inverters of SRAM. NBTI degradations were incorporated on the pull-up transistors of SRAM cell. Furthermore, results of the correlated performance metrics are presented for varied data storage patterns in SRAM cell over its lifetime. This analysis aims to provide an insight into the effects of integrated PVT and NBTI degradation on SRAM cell performance, enabling robust designs and help designers at the early stage of design to mitigate system failure. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the negative bias temperature instability (NBTI) on conventional P-type metal-oxide-semiconductor field effect transistors (PMOSFET) using on-fly bulk trap technique (OTFBT). The extracted NBTI induced interface (ΔNit) and oxide traps (ΔNot), using OTFBT, are modelled and used to simulate the NBTI effect on N-type suspended gate metal-oxide-semiconductor devices (N-type SG-MOS), which could be manufactured by the same fabrication process as conventional PMOSFET. The used approach to simulate the NBTI effect is performed by combining, in the same simulation program, the N-type SG-MOS devices model with the NBTI induced ΔNit and ΔNot models. This approach allowed us to simulate and predict rapidly the lifetime of the N-type SG-MOS devices subjected to the NBTI degradation. The simulation shows that the degradation of N-type SG-MOS devices due to the NBTI is the same as that of conventional PMOSFET. However, the extracted lifetime of N-type SG-MOS devices (stiction of the suspended gate) is longer than that of conventional PMOSFET. [ABSTRACT FROM AUTHOR]

In this paper, we report an experimental evidence of the impact of applied a low magnetic field ( B<10~mT ) during negative bias temperature instability (NBTI) stress and recovery, on commercial power double diffused MOS transistor. We show that both interface (\Delta Nit) and oxide trap (\Delta Not) induced by NBTI stress are reduced by applying the magnetic field. This reducing is more pronounced as the magnetic field is high. However, the dynamic of interface trap during stress and recovery phase is not affected by the applied magnetic field. While, the dynamic of oxide trap is affected in both stress and recovery phases. [ABSTRACT FROM PUBLISHER]

NBTI degradation in STI-based LDMOSFETs has been investigated by multi-region DCIV spectroscopy (MR-DCIV), a non-destructive and sensitive method to probe the interface states on channel, accumulation and STI region. A unified MR-DCIV current model was proposed based on its independency to the forward bias and temperature. Under the same negative gate stress condition, MR-DCIV current degradation was compared for nLDMOSFET and pLDMOSFET. Much larger MR-DCIV current shift was observed at channel and accumulation region with thin gate oxide thickness, indicating interface states generation at related regions. Our results show that more significant degradation for multi-finger device was consistent with NBTI degradation mechanism. High voltage device design with thermal management consideration is of crucial importance to guaranteeing the device performance and reliability. [ABSTRACT FROM AUTHOR]

Three fast measuring methods, namely, "on-the-fly," fast direct threshold-voltage (VT) determination, and fast drain-current measurement near VT, are compared. Problems of the different methods are thoroughly discussed, and an analysis of systematic and statistical errors has been done. An example comparing the VT data extracted from the three methods is given. The results help us to understand the root causes for the observed differences in drift curves. [ABSTRACT FROM PUBLISHER]