Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices

Author:

Kumari Renu1ORCID,Gellanki Jnaneswari2ORCID,Kundale Somnath S.3ORCID,Ustad Ruhan E.3ORCID,Dongale Tukaram D.3ORCID,Fu Ying4ORCID,Pettersson Håkan45ORCID,Kumar Sandeep1ORCID

Affiliation:

1. Department of Physics, Central University of Rajasthan 1 , Ajmer 305817, India

2. Department of Physics, Hansraj College, University of Delhi 2 , Delhi 110007, India

3. Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University 3 , Kolhapur 416 004, India

4. School of Information Technology, Halmstad University 4 , Box 823, 301 18 Halmstad, Sweden

5. Solid State Physics and NanoLund, Lund University 5 , Box 118, 221 00 Lund, Sweden

Abstract

Computational efficiency is significantly enhanced using artificial neural network-based computing. A two-terminal memristive device is a powerful electronic device that can mimic the behavior of a biological synapse in addition to storing information and performing logic operations. This work focuses on the fabrication of a memristive device that utilizes a resistive switching layer composed of polyvinyl alcohol infused with ZnO nanoparticles. By incorporating ZnO nanoparticles into the polymer film, the fabricated memristive devices exhibit functionalities that closely resemble those of biological synapses, including short-term and long-term plasticity, paired-pulse facilitation, and spike time-dependent plasticity. These findings establish the ZnO nanoparticle-polymer nanocomposite as a highly promising material for future neuromorphic systems.

Funder

Inter-University Accelerator Center

Publisher

AIP Publishing

Subject

General Engineering,General Materials Science

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