Improvement of Aging Simulation of Electronic Circuits Using Behavioral Modeling

Fabert, Marc; Mongellaz, Benoit; Bestory, Corinne; Lévi, H.; Danto, Yves

doi:10.1109/tdmr.2006.879117

Cited by 18 publications

(3 citation statements)

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“…While it will fail to capture the full physics of the stress environment that TCAD can offer, the aging model should be physics-based and can be informed by calibrated TCAD stress simulations. Similar approaches have been made in the past with some success, such as for hot carrier breakdown of CMOS devices [7], [8]; however, most models fail to present the full picture for circuit aging, either through the use of simple physical models or incomplete representation of aging effects in the device [9]- [11]. Effective empirical aging models, such as in [12] and [13], have been developed, but they represent a nonideal solution, as they fail to provide an intuitive look at the causes of the aging and may not be as adaptable across different technologies.…”

Section: Introductionmentioning

confidence: 80%

A Physics-Based Circuit Aging Model for Mixed-Mode Degradation in SiGe HBTs

Wier¹,

Green

Kim

et al. 2016

IEEE Trans. Electron Devices

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A physics-based silicon-germanium (SiGe) heterojunction bipolar transistor (HBT) aging model for mixed-mode stress based on the lucky-electron model and reaction-diffusion theory is developed for integration with compact models. An effective aging parameter extraction method is described, and the aging model parameters are fit for a modern SiGe HBT platform. The aging model is implemented as a wrapper in the Cadence Spectre circuit simulator. Device-level aging simulations are shown to be well-matched to measured degradation data. The aging model is further used to explore the effects of aging on a simple current mirror circuit, showing a decrease in mirror ratio with degradation.

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Section: Introductionmentioning

confidence: 80%

A Physics-Based Circuit Aging Model for Mixed-Mode Degradation in SiGe HBTs

Wier¹,

Green

Kim

et al. 2016

IEEE Trans. Electron Devices

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“…This methodology can be applied without a specific tool for aging and easily integrated in any design flow. It takes into account reliability by computing degradation laws directly in compact models used in all Berkeley-SPICE derivative simulators and includes a "virtual degradation acceleration mechanism" to simulate years of aging and picoseconds of electric behavior [3]. This methodology has been developed and applied to an InP/InGaAs DHBT process of III-V lab featuring an f T and f MAX of approximately 300 GHz.…”

Section: Introductionmentioning

confidence: 99%

Advancements on reliability-aware analog circuit design

Ardouin¹,

Dupuy

Godin

et al. 2012

2012 Proceedings of the European Solid-State Device Research Conference (ESSDERC)

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This paper presents a new physics-based method for reliability prediction and modeling of Integrated Circuits (ICs). By implementing transistor degradation mechanisms via differential equations in the transistor compact model, the aging of the circuit can be simulated over (accelerated) time under real conditions. Actually, each transistor in the circuit integrates the voltage, current and temperature stress it suffers which results in (slowly) varying model parameters over time. Due to its straightforward implementation in commercial Computer Aided Design (CAD) flows, this method allows designers creating reliability-aware circuit architectures at an early stage of the design procedure, well before real circuits are actually fabricated. Application examples and results are presented for an InP/InGaAs DHBT process, but the universality of the method makes it suitable also for silicon based technologies such as CMOS and (SiGe) BiCMOS.I.

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“…The authors in [7] show that interactions between voltage, frequency, and temperature significantly impact the energy-delay-product of a target system. The work in [8] presents an analog circuit aging simulation technique based on a behavioral model which includes the effects of degradations on circuit parameters.…”

Section: Introductionmentioning

confidence: 99%