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2018 Fiscal Year Final Research Report

Study on ReRAM circuit operation using in-situ TEM for development of artificial neurons

Research Project

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Project/Area Number 16H04339
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field Electron device/Electronic equipment
Research InstitutionHokkaido University

Principal Investigator

Arita Masashi  北海道大学, 情報科学研究科, 准教授 (20222755)

Co-Investigator(Kenkyū-buntansha) 高橋 庸夫  北海道大学, 情報科学研究科, 教授 (90374610)
福地 厚  北海道大学, 情報科学研究科, 助教 (00748890)
Research Collaborator MUTO Satoshi  
ISHIKAWA Ryusuke  
Project Period (FY) 2016-04-01 – 2019-03-31
Keywords抵抗変化メモリ / 電子顕微鏡 / 電子・電気材料 / 電子デバイス・機器 / ナノ材料
Outline of Final Research Achievements

In this work, the resistance random access memories (ReRAMs) were investigated using in-situ transmission electron microscopy (in-situ TEM) where dynamical observations and analyses of the internal microstructure can be done during memory operations. The conductive bridge ReRAMs (CBRAMs) were the main subject to be investigated, where copper (Cu) nanofilaments contribute to the memory operation. In the study of the double-layer CBRAM, movement of Cu was suppressed at the interface between two insulators having different characteristics. This is the origin of stable device characters including device recovery. In the study of the planar CBRAM, formation of nanoparticles in the switching layer was detected during device initialization. These nanoparticles can localize the electric field and trigger the memory operation. These results using samples simulating devices in practical use must give important information contributing on-going development of ReRAM devices and circuits.

Free Research Field

電気電子工学

Academic Significance and Societal Importance of the Research Achievements

本研究においては、基本動作原理にとどまらず、実デバイスの理解を目的としている。その点で過去の研究例とは異なる。より実用に近い二層型構造におけるCuの移動やナノフィラメント形成様式を明らかにできたことは、ReRAMデバイスの動作保証を行う上で重要な事項である。一方、TEM観察可能なReRAM回路の作製を念頭においた平面型CBRAMにおいて(電気特性と比較しながら)ナノスケール観察の可能性を示したことは、近年の人工ニューラルネットワーク開発に関連して、ReRAM回路のTEM的理解を促進でき得るものであり、今後のReRAM開発へ寄与が期待できる結果であると言える。

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Published: 2020-03-30  

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