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...
Gespeichert in:
| Veröffentlicht in: | Semiconductor Physics Quantum Electronics & Optoelectronics |
|---|---|
| Datum: | 2008 |
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
2008
|
| Online Zugang: | https://nasplib.isofts.kiev.ua/handle/123456789/118884 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | 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. |
Institution
Digital Library of Periodicals of National Academy of Sciences of Ukraine| id |
nasplib_isofts_kiev_ua-123456789-118884 |
|---|---|
| record_format |
dspace |
| spelling |
Djeffal, F. Guessasma, S. Benhaya, A. Bendib, T. 2017-06-01T04:04:50Z 2017-06-01T04:04:50Z 2008 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. 1560-8034 PACS 85.30.-z, 07.05.Mh, 68.65.-k, 85.35.-p https://nasplib.isofts.kiev.ua/handle/123456789/118884 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. en Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України Semiconductor Physics Quantum Electronics & Optoelectronics A neural computation to study the scaling capability of the undoped DG MOSFET Article published earlier |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| title |
A neural computation to study the scaling capability of the undoped DG MOSFET |
| spellingShingle |
A neural computation to study the scaling capability of the undoped DG MOSFET Djeffal, F. Guessasma, S. Benhaya, A. Bendib, T. |
| title_short |
A neural computation to study the scaling capability of the undoped DG MOSFET |
| title_full |
A neural computation to study the scaling capability of the undoped DG MOSFET |
| title_fullStr |
A neural computation to study the scaling capability of the undoped DG MOSFET |
| title_full_unstemmed |
A neural computation to study the scaling capability of the undoped DG MOSFET |
| title_sort |
neural computation to study the scaling capability of the undoped dg mosfet |
| author |
Djeffal, F. Guessasma, S. Benhaya, A. Bendib, T. |
| author_facet |
Djeffal, F. Guessasma, S. Benhaya, A. Bendib, T. |
| publishDate |
2008 |
| language |
English |
| container_title |
Semiconductor Physics Quantum Electronics & Optoelectronics |
| publisher |
Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України |
| format |
Article |
| description |
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.
|
| issn |
1560-8034 |
| url |
https://nasplib.isofts.kiev.ua/handle/123456789/118884 |
| citation_txt |
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. |
| work_keys_str_mv |
AT djeffalf aneuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT guessasmas aneuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT benhayaa aneuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT bendibt aneuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT djeffalf neuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT guessasmas neuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT benhayaa neuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet AT bendibt neuralcomputationtostudythescalingcapabilityoftheundopeddgmosfet |
| first_indexed |
2025-12-07T16:16:52Z |
| last_indexed |
2025-12-07T16:16:52Z |
| _version_ |
1850866886543147008 |