The rise of memtransistors for neuromorphic hardware and In-memory computing
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jihong Bae | - |
dc.contributor.author | Jongbum Won | - |
dc.contributor.author | Wooyoung Shim | - |
dc.date.accessioned | 2024-08-09T02:30:05Z | - |
dc.date.available | 2024-08-09T02:30:05Z | - |
dc.date.created | 2024-05-13 | - |
dc.date.issued | 2024-07 | - |
dc.identifier.issn | 2211-2855 | - |
dc.identifier.uri | https://pr.ibs.re.kr/handle/8788114/15493 | - |
dc.description.abstract | In the impending era of data deluge, escalating costs related to time and energy owing to data movement underscore the need for a departure from traditional systems. The pursuit of in-memory computing that emulates the high-density memory and energy-efficient information processing of the human brain is of paramount significance. At the forefront of this initiative are memtransistors, with an emphasis on those capable of processing multibit digital and analog data and offering the distinctive features of electrostatically tuning memory and learning behaviors at the device level. Herein, a conceptual overview of the materials and device architectures of memtransistors is presented to underscore their pivotal role in in-memory computing. The discussion includes the strategies for achieving their 3D integration and addresses pertinent challenges and opportunities from materials to chip level for advanced memory storage and neuromorphic computing applications. © 2024 Elsevier Ltd | - |
dc.language | 영어 | - |
dc.publisher | Elsevier BV | - |
dc.title | The rise of memtransistors for neuromorphic hardware and In-memory computing | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.identifier.wosid | 001238912100001 | - |
dc.identifier.scopusid | 2-s2.0-85192072962 | - |
dc.identifier.rimsid | 83071 | - |
dc.contributor.affiliatedAuthor | Wooyoung Shim | - |
dc.identifier.doi | 10.1016/j.nanoen.2024.109646 | - |
dc.identifier.bibliographicCitation | Nano Energy, v.126 | - |
dc.relation.isPartOf | Nano Energy | - |
dc.citation.title | Nano Energy | - |
dc.citation.volume | 126 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Physical | - |
dc.relation.journalWebOfScienceCategory | Nanoscience & Nanotechnology | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.subject.keywordPlus | MOS2 MEMTRANSISTORS | - |
dc.subject.keywordPlus | CROSSBAR ARRAYS | - |
dc.subject.keywordPlus | DATA-STORAGE | - |
dc.subject.keywordPlus | MEMRISTOR | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | MECHANISM | - |
dc.subject.keywordPlus | BEHAVIOR | - |
dc.subject.keywordPlus | DENSITY | - |
dc.subject.keywordPlus | DEVICE | - |
dc.subject.keywordAuthor | High-density memory | - |
dc.subject.keywordAuthor | In-memory computing | - |
dc.subject.keywordAuthor | Memtransistor | - |
dc.subject.keywordAuthor | Neuromorphic computing | - |