Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique

Diego R. Benalcazar; Esteban Garzon; Lionel Trojman

doi:10.1109/ETCM.2018.8580289

Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique

Diego R. Benalcazar
, Esteban Garzon
, Lionel Trojman

Universidad San Francisco de Quito USFQ

Universidad San Francisco de Quito

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

Abstract

This paper presents the description and the results obtained with a new RFCV system written on python v2.7. which is used to acquire different parameters from MOSFET devices. RFCV is a technique that permits the measurement of capacitances from devices with an oxide thickness up into the nanometric range. Employing this technique, the developed system controls two tools in a synchronized way: A Vector Network Analyzer (VNA) and a Source Measure Unit (SMU) located in a Parameter Analyzer (PA). The obtained results are satisfactory and allow getting an adequate parameter extraction and the corresponding parasitic assessment of devices with channels as short as 34 nm.

Original language	English
Title of host publication	2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538666579
DOIs	https://doi.org/10.1109/ETCM.2018.8580289
State	Published - 17 Dec 2018
Event	3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018 - Cuenca, Ecuador Duration: 15 Oct 2018 → 19 Oct 2018

Publication series

Name	2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018

Conference

Conference	3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018
Country/Territory	Ecuador
City	Cuenca
Period	15/10/18 → 19/10/18

Keywords

Parameter Analyzer
Python
RFCV
Source Measure Unit
Vector Network Analyzer

Access to Document

10.1109/ETCM.2018.8580289

Cite this

Benalcazar, D. R., Garzon, E., & Trojman, L. (2018). Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique. In 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018 Article 8580289 (2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETCM.2018.8580289

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title = "Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique",

abstract = "This paper presents the description and the results obtained with a new RFCV system written on python v2.7. which is used to acquire different parameters from MOSFET devices. RFCV is a technique that permits the measurement of capacitances from devices with an oxide thickness up into the nanometric range. Employing this technique, the developed system controls two tools in a synchronized way: A Vector Network Analyzer (VNA) and a Source Measure Unit (SMU) located in a Parameter Analyzer (PA). The obtained results are satisfactory and allow getting an adequate parameter extraction and the corresponding parasitic assessment of devices with channels as short as 34 nm.",

keywords = "Parameter Analyzer, Python, RFCV, Source Measure Unit, Vector Network Analyzer",

author = "Benalcazar, \{Diego R.\} and Esteban Garzon and Lionel Trojman",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018 ; Conference date: 15-10-2018 Through 19-10-2018",

year = "2018",

month = dec,

day = "17",

doi = "10.1109/ETCM.2018.8580289",

language = "Ingl{\'e}s",

series = "2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018",

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Benalcazar, DR, Garzon, E & Trojman, L 2018, Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique. in 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018., 8580289, 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018, Institute of Electrical and Electronics Engineers Inc., 3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018, Cuenca, Ecuador, 15/10/18. https://doi.org/10.1109/ETCM.2018.8580289

Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique. / Benalcazar, Diego R.; Garzon, Esteban; Trojman, Lionel.
2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8580289 (2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018).

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

TY - GEN

T1 - Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique

AU - Benalcazar, Diego R.

AU - Garzon, Esteban

AU - Trojman, Lionel

PY - 2018/12/17

Y1 - 2018/12/17

N2 - This paper presents the description and the results obtained with a new RFCV system written on python v2.7. which is used to acquire different parameters from MOSFET devices. RFCV is a technique that permits the measurement of capacitances from devices with an oxide thickness up into the nanometric range. Employing this technique, the developed system controls two tools in a synchronized way: A Vector Network Analyzer (VNA) and a Source Measure Unit (SMU) located in a Parameter Analyzer (PA). The obtained results are satisfactory and allow getting an adequate parameter extraction and the corresponding parasitic assessment of devices with channels as short as 34 nm.

AB - This paper presents the description and the results obtained with a new RFCV system written on python v2.7. which is used to acquire different parameters from MOSFET devices. RFCV is a technique that permits the measurement of capacitances from devices with an oxide thickness up into the nanometric range. Employing this technique, the developed system controls two tools in a synchronized way: A Vector Network Analyzer (VNA) and a Source Measure Unit (SMU) located in a Parameter Analyzer (PA). The obtained results are satisfactory and allow getting an adequate parameter extraction and the corresponding parasitic assessment of devices with channels as short as 34 nm.

KW - Parameter Analyzer

KW - Python

KW - RFCV

KW - Source Measure Unit

KW - Vector Network Analyzer

UR - https://www.scopus.com/pages/publications/85060738872

U2 - 10.1109/ETCM.2018.8580289

DO - 10.1109/ETCM.2018.8580289

M3 - Contribución a la conferencia

AN - SCOPUS:85060738872

T3 - 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018

BT - 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018

Y2 - 15 October 2018 through 19 October 2018

ER -

Benalcazar DR, Garzon E, Trojman L. Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique. In 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8580289. (2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018). doi: 10.1109/ETCM.2018.8580289

Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique

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