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...

Full description

Saved in:
Bibliographic Details
Published inSemiconductor science and technology Vol. 39; no. 1; pp. 15006 - 15012
Main Authors An, Do Gyun, Kim, Garam, Kim, Hyunwoo, Kim, Sangwan, Kim, Jang Hyun
Format Journal Article
LanguageEnglish
Published IOP Publishing 01.01.2024
Subjects
Online AccessGet full text

Cover

Loading…
More Information
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.
Bibliography:SST-109768.R2
ISSN:0268-1242
1361-6641
DOI:10.1088/1361-6641/ad10c4