Effects of switching layer morphology on resistive switching behavior: A case study of electrochemically synthesized mixed-phase copper oxide memristive devices

Somnath S. Kundale, Akhilesh P. Patil, Snehal L. Patil, Prashant B. Patil, Rajanish K. Kamat, Deok kee Kim, Tae Geun Kim, Tukaram D. Dongale

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

Resistive switching (RS) behavior can serve as a building block in the development of non-volatile memory and neuromorphic computing applications. Thus far, various device parameters have been modulated appropriately to achieve the desired characteristics from RS devices. However, no clear guideline for device parameter modulation has been reported. Herein, we systematically investigate the effect of the switching layer morphology and thickness, as well as the choice of the bottom electrode, on RS properties by using electrochemically synthesized mixed-phase copper oxide (CuxO) as a model material for memristive devices. By controlling various electrochemical parameters, we have fabricated CuxO switching layers with various morphologies (microcrystal, microcubic, compact thin film, short dendritic nanowire, granular, and nanoparticle). Interestingly, the CuxO-based RS devices fabricated by means of electrodeposition (CuxO/FTO) exhibit the forming-free digital RS property, which is suitable for non-volatile memory, whereas those fabricated by utilizing anodization (CuxO/Cu) exhibit the analog RS property, which makes them suitable for use in synaptic learning applications. A convolutional neural network (CNN) was implemented using experimental synaptic weights of the anodized CuxO RS device for image edge detection application. In addition, conduction mechanisms and possible RS mechanisms are suggested for both types of devices. These results indicate that the electrochemically synthesized switching layers are promising for use in both non-volatile memory and neuromorphic computing applications.

Original languageEnglish
Article number101460
JournalApplied Materials Today
Volume27
DOIs
Publication statusPublished - 2022 Jun

Bibliographical note

Funding Information:
The authors would like to thank the Science and Engineering Research Board, Department of Science and Technology (DST-SERB), Government of India , for financial support through a grant ( No. EMR/2017/001810 ). This research was supported by the MOTIE (Ministry of Trade, Industry & Energy ( 10080581 ) and the KSRC (Korea Semiconductor Research Consortium) support program for the development of future semiconductor devices. This work was supported by a National Research Foundation of Korea grant funded by the Korean government ( No.2016R1A3B1908249 ). The authors thank Mr. Atul Khot, Ms. Kalyani Kadam, and Ms. Harshada Patil for their assistance during characterizations.

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Artificial synapse
  • Copper oxide
  • Electrochemical synthesis
  • Memristive device
  • Resistive switching

ASJC Scopus subject areas

  • General Materials Science

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