Thin dielectric reliability assessment for DRAM technology with deep trench storage node

Vollertsen, R.‐P.

doi:10.1016/s0026-2714(03)00073-8

Cited by 12 publications

(3 citation statements)

References 90 publications

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“…A major limitation of dielectric stress for BD study is that the experimental time window usually spans from 1 to ∼10 4 s in wafer-level testing. To expand beyond this conventional time window, several different institutions 13,[24][25][26][27][28][29][30] have carried out long-term stress of up to three years at relatively lower stress-voltages. Nevertheless, though long-term stress over many years are certainly beneficial, its throughput is rather limited because of the long turn-around time.…”

Section: Identification and Demonstration Of Correct Voltage/field Ac...mentioning

confidence: 99%

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Fundamental roles of extreme-value distributions in dielectric breakdown and memory applications (minimum-value versus maximum-value statistics)

Ando

et al. 2020

Jpn. J. Appl. Phys.

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In this paper, a thorough review of minimum- and maximum-value statistical distributions is provided. Using the Weibull model (statistics of minima) and the Gumbel model (statistics of maxima) along with the respective scaling properties of their scale-factor and distribution-percentile with device area (size), the application of these two types of extreme-value distributions to dielectric breakdown (BD) and memory operations is discussed. In the case of dielectric breakdown, the minimum-value distribution (the Weibull model) provides an indispensable tool to establish a valid voltage/field acceleration model from experimental perspectives. On the other hand, recent advances in the introduction of maximum-value distribution (the Gumbel model) overcomes the shortcomings of the conventional practice of adopting the normal distribution to characterize memory functional operations and provides much needed mathematical rigor and physical insight particularly for the rapid growing field of resistive random-access memory devices.

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Section: Identification and Demonstration Of Correct Voltage/field Ac...mentioning

confidence: 99%

“…(15). The data of the long-term stress of 2.2 nm and 6.2 nm are from 13) and 24) with the device areas of 2.475 × 10 5 μm 2 and 10 5 μm 2 , respectively.…”

Section: Identification and Demonstration Of Correct Voltage/field Ac...mentioning

confidence: 99%

Fundamental roles of extreme-value distributions in dielectric breakdown and memory applications (minimum-value versus maximum-value statistics)

Ando

et al. 2020

Jpn. J. Appl. Phys.

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“…Cumulative failure distribution F (t) has been calculated and plotted versus time in Figure 14, which shows a logarithmic dependence (R 2 = 1) [54][55][56] . The t 50% value, calculated for 50% of failures from F (t), is equal to 2 × 10 5 h and the failure rate corresponds to 550 FITs for 15 years, in accordance with results reported by numerous papers on GaAs unpackaged LED technology 1,2,7 .…”

Section: Reliability Investigations Using Technological Dispersionmentioning

confidence: 99%

Long‐term Reliability Prediction of 935 nm LEDs Using Failure Laws and Low Acceleration Factor Ageing Tests

Deshayes

Béchou

Verdier

et al. 2005

Quality & Reliability Eng

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Numerous papers have already reported various results on electrical and optical performances of GaAs-based materials for optoelectronic applications. Other papers have proposed some methodologies for a classical estimation of reliability of GaAs compounds using life testing methods on a few thousand samples over 10 000 hours of testing. In contrast, fewer papers have studied the complete relation between degradation laws in relation to failure mechanisms and the estimation of lifetime distribution using accelerated ageing tests considering a short test duration, low acceleration factor and analytical extrapolation. In this paper, we report the results for commercial InGaAs/GaAs 935 nm packaged light emitting diodes (LEDs) using electrical and optical measurements versus ageing time. Cumulative failure distributions are calculated using degradation laws and process distribution data of optical power. A complete methodology is described proposing an accurate reliability model from experimental determination of the failure mechanisms (defect diffusion) for this technology. Electrical and optical characterizations are used with temperature dependence, short-duration accelerated tests (less than 1500 h) with an increase in bias current (up to 50%), a small number of samples (less than 20) and weak acceleration factors (up to 240).

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Dielectric Characterization and Reliability Methodology

Strong¹,

Wu²,

Vollertsen³

et al. 2009

Reliability Wearout Mechanisms in Advanced CMOS Technologies

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Thin dielectric reliability assessment for DRAM technology with deep trench storage node

Cited by 12 publications

References 90 publications

Fundamental roles of extreme-value distributions in dielectric breakdown and memory applications (minimum-value versus maximum-value statistics)

Fundamental roles of extreme-value distributions in dielectric breakdown and memory applications (minimum-value versus maximum-value statistics)

Long‐term Reliability Prediction of 935 nm LEDs Using Failure Laws and Low Acceleration Factor Ageing Tests

Dielectric Characterization and Reliability Methodology

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