Cited 3 time in
Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Kim, Juri | - |
| dc.contributor.author | Lee, Subaek | - |
| dc.contributor.author | Seo, Yeongkyo | - |
| dc.contributor.author | Kim, Sungjun | - |
| dc.date.accessioned | 2024-08-08T11:31:50Z | - |
| dc.date.available | 2024-08-08T11:31:50Z | - |
| dc.date.issued | 2024-04 | - |
| dc.identifier.issn | 0021-9606 | - |
| dc.identifier.issn | 1089-7690 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/21814 | - |
| dc.description.abstract | Here, we demonstrate double-layer 3D vertical resistive random-access memory with a hole-type structure embedding Pt/HfOx/AlN/TiN memory cells, conduct analog resistive switching, and examine the potential of memristors for use in neuromorphic systems. The electrical characteristics, including resistive switching, retention, and endurance, of each layer are also obtained. Additionally, we investigate various synaptic characteristics, such as spike-timing dependent plasticity, spike-amplitude dependent plasticity, spike-rate dependent plasticity, spike-duration dependent plasticity, and spike-number dependent plasticity. This synapse emulation holds great potential for neuromorphic computing applications. Furthermore, potentiation and depression are manifested through identical pulses based on DC resistive switching. The pattern recognition rates within the neural network are evaluated, and based on the conductance changing linearly with incremental pulses, we achieve a pattern recognition accuracy of over 95%. Finally, the device's stability and synapse characteristics exhibit excellent potential for use in neuromorphic systems. | - |
| dc.format.extent | 10 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | AIP Publishing | - |
| dc.title | Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1063/5.0202610 | - |
| dc.identifier.scopusid | 2-s2.0-85189928957 | - |
| dc.identifier.wosid | 001198367000004 | - |
| dc.identifier.bibliographicCitation | The Journal of Chemical Physics, v.160, no.14, pp 1 - 10 | - |
| dc.citation.title | The Journal of Chemical Physics | - |
| dc.citation.volume | 160 | - |
| dc.citation.number | 14 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 10 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Chemistry | - |
| dc.relation.journalResearchArea | Physics | - |
| dc.relation.journalWebOfScienceCategory | Chemistry, Physical | - |
| dc.relation.journalWebOfScienceCategory | Physics, Atomic, Molecular & Chemical | - |
| dc.subject.keywordPlus | OXIDE-BASED RRAM | - |
| dc.subject.keywordPlus | SWITCHING MEMORY | - |
| dc.subject.keywordPlus | DEVICES | - |
| dc.subject.keywordPlus | MECHANISM | - |
| dc.subject.keywordPlus | LAYER | - |
| dc.subject.keywordAuthor | Neurons | - |
| dc.subject.keywordAuthor | Pattern Recognition | - |
| dc.subject.keywordAuthor | Double Layers | - |
| dc.subject.keywordAuthor | Electrical Characteristic | - |
| dc.subject.keywordAuthor | Embeddings | - |
| dc.subject.keywordAuthor | Memory Cell | - |
| dc.subject.keywordAuthor | Memristor | - |
| dc.subject.keywordAuthor | Neuromorphic Systems | - |
| dc.subject.keywordAuthor | Random Access Memory | - |
| dc.subject.keywordAuthor | Resistive Memory | - |
| dc.subject.keywordAuthor | Resistive Switching | - |
| dc.subject.keywordAuthor | Type Structures | - |
| dc.subject.keywordAuthor | Random Access Storage | - |
| dc.subject.keywordAuthor | Artificial Neural Network | - |
| dc.subject.keywordAuthor | Electricity | - |
| dc.subject.keywordAuthor | Electricity | - |
| dc.subject.keywordAuthor | Neural Networks, Computer | - |
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