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Paper Abstract and Keywords
Presentation 2021-11-12 16:45
Simulation of Phonon Transport in Si Nanowires with Physics Informed Neural Networks
Yuma Fujita, Yuhei Suzuki, Yoshinari Kamakura (Osaka Inst. Technol.) SDM2021-66
Abstract (in Japanese) (See Japanese page) 
(in English) The temperature distribution was calculated for Si with a dogbone structure by solving the phonon-Boltzmann transport equation using Physics Informed Neural Networks (PINNs), which can get approximate solutions to partial differential equations. The temperature distribution calculated by PINNs shows a very similar trend to that calculated by Monte Carlo method, reflecting the device size dependence of the quasi-ballistic transport effect. As a result, PINNs is expected to provide efficient optimization of device designs because it can perform inference in a uniform calculation time independent of the size of the structure.
Keyword (in Japanese) (See Japanese page) 
(in English) physics Informed Neural Networks / Boltzmann transport equation / silicon / / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 235, SDM2021-66, pp. 72-76, Nov. 2021.
Paper # SDM2021-66 
Date of Issue 2021-11-04 (SDM) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SDM2021-66

Conference Information
Committee SDM  
Conference Date 2021-11-11 - 2021-11-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Process, Device, Circuit simulation, etc. 
Paper Information
Registration To SDM 
Conference Code 2021-11-SDM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Simulation of Phonon Transport in Si Nanowires with Physics Informed Neural Networks 
Sub Title (in English)  
Keyword(1) physics Informed Neural Networks  
Keyword(2) Boltzmann transport equation  
Keyword(3) silicon  
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1st Author's Name Yuma Fujita  
1st Author's Affiliation Osaka Institute of Technology (Osaka Inst. Technol.)
2nd Author's Name Yuhei Suzuki  
2nd Author's Affiliation Osaka Institute of Technology (Osaka Inst. Technol.)
3rd Author's Name Yoshinari Kamakura  
3rd Author's Affiliation Osaka Institute of Technology (Osaka Inst. Technol.)
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Speaker Author-1 
Date Time 2021-11-12 16:45:00 
Presentation Time 25 minutes 
Registration for SDM 
Paper # SDM2021-66 
Volume (vol) vol.121 
Number (no) no.235 
Page pp.72-76 
#Pages 5 
Date of Issue 2021-11-04 (SDM) 

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