Predictive effective mobility model for FDSOI transistors using technology parameters

Pragya Kushwaha; Harshit Agarwal; Yogesh S. Chauhan; Mandar Bhoir; Nihar R. Mohapatra; Sourabh Khandelwal; Juan P. Duarte; Yen Kai Lin; Huan Lin Chang; Chenming Hu

doi:10.1109/EDSSC.2016.7785304

Predictive effective mobility model for FDSOI transistors using technology parameters

Pragya Kushwaha, Harshit Agarwal, Yogesh S. Chauhan, Mandar Bhoir, Nihar R. Mohapatra, Sourabh Khandelwal, Juan P. Duarte, Yen Kai Lin, Huan Lin Chang, Chenming Hu

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

7 Citations (Scopus)

Abstract

The formulation of effective mobility for fully depleted silicon-on-insulator (FDSOI) transistors is a very challenging task. As vertical electric field (E_eff) changes it's sign from positive to negative according to the front and back channel dominance which results in non-unique relationship between E_eff and carrier distribution. This is the first time, when a predictive mobility model for wide range of back gate biases, solely dependent on technology parameters (front and back gate oxide thickness T_ox/_box, threshold voltage V_th, front/back gate bias V_fg/b_g and flat-band voltage V_fb) is proposed. This predictive mobility model allows the user to predict the deviation in device characteristics due to the variations in the device structure.

Original language	English
Title of host publication	EDSSC 2016
Subtitle of host publication	IEEE International Conference on Electron Devices and Solid-State Circuits : proceedings
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	448-451
Number of pages	4
ISBN (Electronic)	9781509018307
DOIs	https://doi.org/10.1109/EDSSC.2016.7785304
Publication status	Published - 15 Dec 2016
Externally published	Yes
Event	2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016 - Hong Kong, Hong Kong Duration: 3 Aug 2016 → 5 Aug 2016

Other

Other	2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016
Country/Territory	Hong Kong
City	Hong Kong
Period	3/08/16 → 5/08/16

Keywords

FDSOI
Mobility
Model
Split-CV

Access to Document

10.1109/EDSSC.2016.7785304

Cite this

Kushwaha, P., Agarwal, H., Chauhan, Y. S., Bhoir, M., Mohapatra, N. R., Khandelwal, S., Duarte, J. P., Lin, Y. K., Chang, H. L., & Hu, C. (2016). Predictive effective mobility model for FDSOI transistors using technology parameters. In EDSSC 2016: IEEE International Conference on Electron Devices and Solid-State Circuits : proceedings (pp. 448-451). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EDSSC.2016.7785304

@inproceedings{cceec449f075411cbfce71ab09461c52,

title = "Predictive effective mobility model for FDSOI transistors using technology parameters",

abstract = "The formulation of effective mobility for fully depleted silicon-on-insulator (FDSOI) transistors is a very challenging task. As vertical electric field (Eeff) changes it's sign from positive to negative according to the front and back channel dominance which results in non-unique relationship between Eeff and carrier distribution. This is the first time, when a predictive mobility model for wide range of back gate biases, solely dependent on technology parameters (front and back gate oxide thickness Tox/box, threshold voltage Vth, front/back gate bias Vfg/bg and flat-band voltage Vfb) is proposed. This predictive mobility model allows the user to predict the deviation in device characteristics due to the variations in the device structure.",

keywords = "FDSOI, Mobility, Model, Split-CV",

author = "Pragya Kushwaha and Harshit Agarwal and Chauhan, \{Yogesh S.\} and Mandar Bhoir and Mohapatra, \{Nihar R.\} and Sourabh Khandelwal and Duarte, \{Juan P.\} and Lin, \{Yen Kai\} and Chang, \{Huan Lin\} and Chenming Hu",

year = "2016",

month = dec,

day = "15",

doi = "10.1109/EDSSC.2016.7785304",

language = "English",

pages = "448--451",

booktitle = "EDSSC 2016",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016 ; Conference date: 03-08-2016 Through 05-08-2016",

}

Kushwaha, P, Agarwal, H, Chauhan, YS, Bhoir, M, Mohapatra, NR, Khandelwal, S, Duarte, JP, Lin, YK, Chang, HL & Hu, C 2016, Predictive effective mobility model for FDSOI transistors using technology parameters. in EDSSC 2016: IEEE International Conference on Electron Devices and Solid-State Circuits : proceedings. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 448-451, 2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016, Hong Kong, Hong Kong, 3/08/16. https://doi.org/10.1109/EDSSC.2016.7785304

Predictive effective mobility model for FDSOI transistors using technology parameters. / Kushwaha, Pragya; Agarwal, Harshit; Chauhan, Yogesh S. et al.
EDSSC 2016: IEEE International Conference on Electron Devices and Solid-State Circuits : proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 448-451.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

TY - GEN

T1 - Predictive effective mobility model for FDSOI transistors using technology parameters

AU - Kushwaha, Pragya

AU - Agarwal, Harshit

AU - Chauhan, Yogesh S.

AU - Bhoir, Mandar

AU - Mohapatra, Nihar R.

AU - Khandelwal, Sourabh

AU - Duarte, Juan P.

AU - Lin, Yen Kai

AU - Chang, Huan Lin

AU - Hu, Chenming

PY - 2016/12/15

Y1 - 2016/12/15

N2 - The formulation of effective mobility for fully depleted silicon-on-insulator (FDSOI) transistors is a very challenging task. As vertical electric field (Eeff) changes it's sign from positive to negative according to the front and back channel dominance which results in non-unique relationship between Eeff and carrier distribution. This is the first time, when a predictive mobility model for wide range of back gate biases, solely dependent on technology parameters (front and back gate oxide thickness Tox/box, threshold voltage Vth, front/back gate bias Vfg/bg and flat-band voltage Vfb) is proposed. This predictive mobility model allows the user to predict the deviation in device characteristics due to the variations in the device structure.

AB - The formulation of effective mobility for fully depleted silicon-on-insulator (FDSOI) transistors is a very challenging task. As vertical electric field (Eeff) changes it's sign from positive to negative according to the front and back channel dominance which results in non-unique relationship between Eeff and carrier distribution. This is the first time, when a predictive mobility model for wide range of back gate biases, solely dependent on technology parameters (front and back gate oxide thickness Tox/box, threshold voltage Vth, front/back gate bias Vfg/bg and flat-band voltage Vfb) is proposed. This predictive mobility model allows the user to predict the deviation in device characteristics due to the variations in the device structure.

KW - FDSOI

KW - Mobility

KW - Model

KW - Split-CV

UR - https://www.scopus.com/pages/publications/85010399692

U2 - 10.1109/EDSSC.2016.7785304

DO - 10.1109/EDSSC.2016.7785304

M3 - Conference proceeding contribution

AN - SCOPUS:85010399692

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BT - EDSSC 2016

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016

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ER -

Kushwaha P, Agarwal H, Chauhan YS, Bhoir M, Mohapatra NR, Khandelwal S et al. Predictive effective mobility model for FDSOI transistors using technology parameters. In EDSSC 2016: IEEE International Conference on Electron Devices and Solid-State Circuits : proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 448-451 doi: 10.1109/EDSSC.2016.7785304

Predictive effective mobility model for FDSOI transistors using technology parameters

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