A scalable solution recipe for a Ag-based neuromorphic device
Abstract Integration and scalability have posed significant problems in the advancement of brain-inspired intelligent systems. Here, we report a self-formed Ag device fabricated through a chemical dewetting process using an Ag organic precursor, which offers easy processing, scalability, and flexibi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer
2023-10-01
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| Series: | Discover Nano |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s11671-023-03906-5 |
| _version_ | 1797451787557404672 |
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| author | Tejaswini S. Rao Indrajit Mondal Bharath Bannur Giridhar U. Kulkarni |
| author_facet | Tejaswini S. Rao Indrajit Mondal Bharath Bannur Giridhar U. Kulkarni |
| author_sort | Tejaswini S. Rao |
| collection | DOAJ |
| description | Abstract Integration and scalability have posed significant problems in the advancement of brain-inspired intelligent systems. Here, we report a self-formed Ag device fabricated through a chemical dewetting process using an Ag organic precursor, which offers easy processing, scalability, and flexibility to address the above issues to a certain extent. The conditions of spin coating, precursor dilution, and use of solvents were varied to obtain different dewetted structures (broadly classified as bimodal and nearly unimodal). A microscopic study is performed to obtain insight into the dewetting mechanism. The electrical behavior of selected bimodal and nearly unimodal devices is related to the statistical analysis of their microscopic structures. A capacitance model is proposed to relate the threshold voltage (Vth) obtained electrically to the various microscopic parameters. Synaptic functionalities such as short-term potentiation (STP) and long-term potentiation (LTP) were emulated in a representative nearly unimodal and bimodal device, with the bimodal device showing a better performance. One of the cognitive behaviors, associative learning, was emulated in a bimodal device. Scalability is demonstrated by fabricating more than 1000 devices, with 96% exhibiting switching behavior. A flexible device is also fabricated, demonstrating synaptic functionalities (STP and LTP). |
| first_indexed | 2024-03-09T14:59:26Z |
| format | Article |
| id | doaj.art-ce7f62a43260432ab7928a95cbf50a03 |
| institution | Directory Open Access Journal |
| issn | 2731-9229 |
| language | English |
| last_indexed | 2024-03-09T14:59:26Z |
| publishDate | 2023-10-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Nano |
| spelling | doaj.art-ce7f62a43260432ab7928a95cbf50a032023-11-26T14:01:26ZengSpringerDiscover Nano2731-92292023-10-0118111410.1186/s11671-023-03906-5A scalable solution recipe for a Ag-based neuromorphic deviceTejaswini S. Rao0Indrajit Mondal1Bharath Bannur2Giridhar U. Kulkarni3Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific ResearchChemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific ResearchChemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific ResearchChemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific ResearchAbstract Integration and scalability have posed significant problems in the advancement of brain-inspired intelligent systems. Here, we report a self-formed Ag device fabricated through a chemical dewetting process using an Ag organic precursor, which offers easy processing, scalability, and flexibility to address the above issues to a certain extent. The conditions of spin coating, precursor dilution, and use of solvents were varied to obtain different dewetted structures (broadly classified as bimodal and nearly unimodal). A microscopic study is performed to obtain insight into the dewetting mechanism. The electrical behavior of selected bimodal and nearly unimodal devices is related to the statistical analysis of their microscopic structures. A capacitance model is proposed to relate the threshold voltage (Vth) obtained electrically to the various microscopic parameters. Synaptic functionalities such as short-term potentiation (STP) and long-term potentiation (LTP) were emulated in a representative nearly unimodal and bimodal device, with the bimodal device showing a better performance. One of the cognitive behaviors, associative learning, was emulated in a bimodal device. Scalability is demonstrated by fabricating more than 1000 devices, with 96% exhibiting switching behavior. A flexible device is also fabricated, demonstrating synaptic functionalities (STP and LTP).https://doi.org/10.1186/s11671-023-03906-5Self-formingDewettingChemical processHierarchical structuresNeuromorphic deviceAssociative learning |
| spellingShingle | Tejaswini S. Rao Indrajit Mondal Bharath Bannur Giridhar U. Kulkarni A scalable solution recipe for a Ag-based neuromorphic device Discover Nano Self-forming Dewetting Chemical process Hierarchical structures Neuromorphic device Associative learning |
| title | A scalable solution recipe for a Ag-based neuromorphic device |
| title_full | A scalable solution recipe for a Ag-based neuromorphic device |
| title_fullStr | A scalable solution recipe for a Ag-based neuromorphic device |
| title_full_unstemmed | A scalable solution recipe for a Ag-based neuromorphic device |
| title_short | A scalable solution recipe for a Ag-based neuromorphic device |
| title_sort | scalable solution recipe for a ag based neuromorphic device |
| topic | Self-forming Dewetting Chemical process Hierarchical structures Neuromorphic device Associative learning |
| url | https://doi.org/10.1186/s11671-023-03906-5 |
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