Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices
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 focus...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-10-01
|
| Series: | APL Materials |
| Online Access: | http://dx.doi.org/10.1063/5.0165205 |
| _version_ | 1797634182009061376 |
|---|---|
| author | Renu Kumari Jnaneswari Gellanki Somnath S. Kundale Ruhan E. Ustad Tukaram D. Dongale Ying Fu Håkan Pettersson Sandeep Kumar |
| author_facet | Renu Kumari Jnaneswari Gellanki Somnath S. Kundale Ruhan E. Ustad Tukaram D. Dongale Ying Fu Håkan Pettersson Sandeep Kumar |
| author_sort | Renu Kumari |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T12:04:59Z |
| format | Article |
| id | doaj.art-ab2731e2638f4c1ea20e7f7023417cee |
| institution | Directory Open Access Journal |
| issn | 2166-532X |
| language | English |
| last_indexed | 2024-03-11T12:04:59Z |
| publishDate | 2023-10-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | APL Materials |
| spelling | doaj.art-ab2731e2638f4c1ea20e7f7023417cee2023-11-07T17:27:29ZengAIP Publishing LLCAPL Materials2166-532X2023-10-011110101124101124-710.1063/5.0165205Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devicesRenu Kumari0Jnaneswari Gellanki1Somnath S. Kundale2Ruhan E. Ustad3Tukaram D. Dongale4Ying Fu5Håkan Pettersson6Sandeep Kumar7Department of Physics, Central University of Rajasthan, Ajmer 305817, IndiaDepartment of Physics, Hansraj College, University of Delhi, Delhi 110007, IndiaComputational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416 004, IndiaComputational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416 004, IndiaComputational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416 004, IndiaSchool of Information Technology, Halmstad University, Box 823, 301 18 Halmstad, SwedenSchool of Information Technology, Halmstad University, Box 823, 301 18 Halmstad, SwedenDepartment of Physics, Central University of Rajasthan, Ajmer 305817, IndiaComputational 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.http://dx.doi.org/10.1063/5.0165205 |
| spellingShingle | Renu Kumari Jnaneswari Gellanki Somnath S. Kundale Ruhan E. Ustad Tukaram D. Dongale Ying Fu Håkan Pettersson Sandeep Kumar Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices APL Materials |
| title | Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices |
| title_full | Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices |
| title_fullStr | Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices |
| title_full_unstemmed | Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices |
| title_short | Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices |
| title_sort | artificial synaptic characteristics of pva zno nanocomposite memristive devices |
| url | http://dx.doi.org/10.1063/5.0165205 |
| work_keys_str_mv | AT renukumari artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT jnaneswarigellanki artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT somnathskundale artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT ruhaneustad artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT tukaramddongale artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT yingfu artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT hakanpettersson artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices AT sandeepkumar artificialsynapticcharacteristicsofpvaznonanocompositememristivedevices |