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Paper Abstract and Keywords
Presentation 2018-02-28 16:40
Artificial Intelligence Approach for Control of Quantized Conductance of Au Atomic Junctions Using Feedback-Controlled Electromigration
Yuma Iwata, Shotaro Sakai, Noriaki Numakura, Jun-ichi Shirakashi (Tokyo Univ. of Agr. & Tech.) ED2017-114 SDM2017-114
Abstract (in Japanese) (See Japanese page) 
(in English) Feedback controlled electromigration (FCE) methods have been developed to control electromigration and avoid catastrophic instability. The FCE procedure can successfully control metal nanowires with quantized conductance and make atomic junctions. FCE scheme is tuned by many parameters such as threshold differential conductance GTH, feedback voltage VFB, and voltage step VSTEP and so on. Therefore, it is necessary to optimize the FCE procedure according to the situation for precise and stable control of the quantized conductance of metal nanowires. However, the conventional system selects optimum parameters based on human experiments. This process may not necessarily be optimum for the FCE procedure. Hence, in order to address these problems, we focus on artificial intelligence (AI) approach. In this study, in order to realize AI approach for fabrication of nanoscale device, we designed intelligent control system for FCE. The system is composed by three kinds of AI engines that play a role in learning, evaluation and inference. These engines can determine the optimum VFB parameter without human intervention. Therefore, it is considered that intelligent control system allows us to improve the controllability of quantized conductance of Au atomic junctions with appropriate VFB parameters.
Keyword (in Japanese) (See Japanese page) 
(in English) Electromigration / Atomic Junction / Artificial Intelligence / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 453, ED2017-114, pp. 45-50, Feb. 2018.
Paper # ED2017-114 
Date of Issue 2018-02-21 (ED, SDM) 
ISSN Print edition: ISSN 0913-5685    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 ED2017-114 SDM2017-114

Conference Information
Committee ED SDM  
Conference Date 2018-02-28 - 2018-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Centennial Hall, Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Functional nanodevices and related technologies 
Paper Information
Registration To ED 
Conference Code 2018-02-ED-SDM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Artificial Intelligence Approach for Control of Quantized Conductance of Au Atomic Junctions Using Feedback-Controlled Electromigration 
Sub Title (in English)  
Keyword(1) Electromigration  
Keyword(2) Atomic Junction  
Keyword(3) Artificial Intelligence  
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1st Author's Name Yuma Iwata  
1st Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agr. & Tech.)
2nd Author's Name Shotaro Sakai  
2nd Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agr. & Tech.)
3rd Author's Name Noriaki Numakura  
3rd Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agr. & Tech.)
4th Author's Name Jun-ichi Shirakashi  
4th Author's Affiliation Tokyo University of Agriculture and Technology (Tokyo Univ. of Agr. & Tech.)
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Speaker Author-1 
Date Time 2018-02-28 16:40:00 
Presentation Time 25 minutes 
Registration for ED 
Paper # ED2017-114, SDM2017-114 
Volume (vol) vol.117 
Number (no) no.453(ED), no.454(SDM) 
Page pp.45-50 
#Pages 6 
Date of Issue 2018-02-21 (ED, SDM) 

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