Random Dopant, Line-Edge Roughness, and Gate Workfunction Variability in a Nano InGaAs FinFET

Seoane, Natalia; Indalecio, Guillermo; Comesaña, Enrique; Aldegunde, Manuel; García‐Loureiro, Antonio J.; Kálna, K.

doi:10.1109/ted.2013.2294213

Cited by 44 publications

(31 citation statements)

References 20 publications

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“…In the presence of FER, the observed variations for the three figures of merit related to the off-region of the device (I OFF , SS and DIBL) are smaller in the In 0.53 Ga 0.47 As FinFET than in the Si FinFET. Note here that the standard deviations for all the figures of merit are strongly affected by the drain bias and the correlation length values in the Si FinFET whereas their impact on the In 0.53 Ga 0.47 As FinFET is smaller as previously seen in [6].…”

Section: A Fer and Mgw Variability Modelssupporting

confidence: 56%

“…First, we use a 3-D parallel finite-element (FE) drift-diffusion (DD) device simulator [11], [12] with integrated FE density gradient (DG) quantum corrections [13] and Fermi-Dirac statistics [14]. We have calibrated quantum corrections through the effective masses that characterise the DG solution, which mimic the source-todrain tunnelling and quantum confinement effects [6]. After that, this simulator has been validated at both low and high drain biases against 3-D Non-Equilibrium Green's Functions (NEGF) simulations [15], [16] with an excellent agreement as seen in Figs 2 and 3.…”

Section: Finfet Modellingmentioning

confidence: 99%

“…The FER is implemented as previously described in [6], [24]. DD simulations that include DG quantum confinement corrections have been widely used for the analysis of line-edge-roughness variability [8], [25], [26].…”

Section: A Fer and Mgw Variability Modelsmentioning

confidence: 99%

“…A full description of the followed methodology can be found in [6], [24]. In this work, we analyse four different grain sizes (GSs) (10, 7, 5 and 3 nm) and assume that TiN has two possible grain orientations with MGWs of 4.6 and 4.4 eV and probabilities 60% and 40%, respectively [29].…”

Section: A Fer and Mgw Variability Modelsmentioning

confidence: 99%

“…MA, DN, MAE and KK are with the ESDC, Swansea University, United Kingdom. MAE is also with Dept of Mathematics & Engineering Physics, Mansoura University, Egypt metal gate work-function variations, have become dominant in both Si and III-V channel-based nano-MOSFETs [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Fin-Edge Roughness and Metal Grain Work Function Variability in InGaAs and Si FinFETs

Seoane

Indalecio

Aldegunde

et al. 2016

IEEE Trans. Electron Devices

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Copies of full items can be used for personal research or study, educational, or not-for profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.Publisher's statement: "© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP url' above for details on accessing the published version and note that access may require a subscription. Abstract-The fin edge roughness (FER) and the TiN metal grain work-function (MGW) induced variability affecting off and on device characteristics is studied and compared between a 10.4 nm gate length In 0.53 Ga 0.47 As FinFET and a 10.7 nm gate length Si FinFET. We have analysed the impact of variability by assessing five figures of merit (V T , SS, I OFF , DIBL and I ON ) using two state-of-the-art in-house-build 3-D simulation tools based on the finite element method. Quantum-corrected 3-D drift-diffusion simulations are employed for variability studies in the sub-threshold region while, in the on-region, we use quantum-corrected 3-D ensemble Monte Carlo simulations. The In 0.53 Ga 0.47 As FinFET is more resilient to the FER and MGW variability in the sub-threshold compared to the Si FinFET due to a stronger quantum carrier confinement present in the In 0.53 Ga 0.47 As channel. However, the on-current variability is between 1.1-2.2 times larger for the In 0.53 Ga 0.47 As FinFET than for the Si counterpart, respectively.

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Section: A Fer and Mgw Variability Modelssupporting

confidence: 56%