Comparative analysis of junctionless and inversion-mode nanosheet FETs for self-heating effect mitigation
Artificial intelligence computing requires hardware like central processing units and graphic processing units for data processing. However, excessive heat generated during computations remains a challenge. The paper focuses on the heat issue in logic devices caused by transistor structures. To addr...
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Published in | Semiconductor science and technology Vol. 39; no. 1; pp. 15006 - 15012 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
IOP Publishing
01.01.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Artificial intelligence computing requires hardware like central processing units and graphic processing units for data processing. However, excessive heat generated during computations remains a challenge. The paper focuses on the heat issue in logic devices caused by transistor structures. To address the problem, the operational mechanism of the Junctionless Field-Effect Transistor (JLFET) is investigated. JLFET shows potential in mitigating heat-related issues and is compared to other nanosheet (ns) FETs. In the case of JL-nsFET, the change in mobility with increasing temperature is smaller compared to Con-nsFET, resulting in less susceptibility to lattice scattering and thermal resistance ( R th) in self-heating effect situation is 0.43 [K µ W −1 ] for Con-nsFET and 0.414 [K µ W −1 ] for JL-nsFET. The reason why the R th of JL-nsFET is smaller than that of Con-nsFET is that JL-nsFET uses a source heat injection conduction mechanism and a large heat transfer area by using a bulk channel. |
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Bibliography: | SST-109768.R2 |
ISSN: | 0268-1242 1361-6641 |
DOI: | 10.1088/1361-6641/ad10c4 |