A neural computation to study the scaling capability of the undoped DG MOSFET
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...
Збережено в:
| Дата: | 2008 |
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| Автори: | , , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
2008
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| Назва видання: | Semiconductor Physics Quantum Electronics & Optoelectronics |
| Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/118884 |
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| 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. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Резюме: | 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. |
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