A neural computation to study the scaling capability of the undoped DG MOSFET

• Опубліковано в: : Semiconductor Physics Quantum Electronics & Optoelectronics
• Дата: 2008
• Автори: Djeffal, F., Guessasma, S., Benhaya, A., Bendib, T.
• Формат: Стаття
• Мова: Англійська
• Опубліковано: Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України 2008
• Онлайн доступ: https://nasplib.isofts.kiev.ua/handle/123456789/118884
• Назва журналу: Digital Library of Periodicals of National Academy of Sciences of Ukraine
• Цитувати: A neural computation to study the scaling capability of the undoped DG MOSFET / F. Djeffal, S. Guessasma, A. Benhaya, T. Bendib // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2008. — Т. 11, № 2. — С. 196-202. — Бібліогр.: 11 назв. — англ.

The DG MOSFET is one of the most promising candidates for further CMOS
 scaling beyond the year of 2010. It will be scaled down to various degrees upon a wide
 range of system/circuit requirements (such as high-performance, low standby power and
 low operating power). The key electrical parameter of the DG MOSFET is the
 subthreshold swing (S). In this paper, we present the applicability of the artificial neural
 network for the study of the scaling capability of the undoped DG MOSFET. The latter is
 based on the development of a semi-analytical model of the subthreshold swing (S) using
 the Finite Elements Method (FEM). Our results are discussed in order to draw some
 useful information about the ULSI technology.