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

Diego R. Benalcazar, Esteban Garzon, Lionel Trojman

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

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.

Idioma originalInglés
Título de la publicación alojada2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538666579
DOI
EstadoPublicada - 17 dic. 2018
Evento3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018 - Cuenca, Ecuador
Duración: 15 oct. 201819 oct. 2018

Serie de la publicación

Nombre2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018

Conferencia

Conferencia3rd IEEE Ecuador Technical Chapters Meeting, ETCM 2018
País/TerritorioEcuador
CiudadCuenca
Período15/10/1819/10/18

Huella

Profundice en los temas de investigación de 'Capacitance Extraction of 34-nm Metallurgical Channel Length MOSFET for Parasitic Assessment Using the RFCV Technique'. En conjunto forman una huella única.

Citar esto