Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing
Abstract Flexible memristors are promising candidates for multifunctional neuromorphic computing applications, overcoming the limitations of conventional computing devices. However, unpredictable switching behavior and poor mechanical stability in conventional memristors present significant challeng...
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| Format: | Article |
| Language: | English |
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Wiley
2025-03-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202412289 |
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| author | Jae‐Hyeok Cho Suk Yeop Chun Ga Hye Kim Panithan Sriboriboon Sanghee Han Seung Beom Shin Jeehoon Kim San Nam Yunseok Kim Yong‐Hoon Kim Jung Ho Yoon Myung‐Gil Kim |
| author_facet | Jae‐Hyeok Cho Suk Yeop Chun Ga Hye Kim Panithan Sriboriboon Sanghee Han Seung Beom Shin Jeehoon Kim San Nam Yunseok Kim Yong‐Hoon Kim Jung Ho Yoon Myung‐Gil Kim |
| author_sort | Jae‐Hyeok Cho |
| collection | DOAJ |
| description | Abstract Flexible memristors are promising candidates for multifunctional neuromorphic computing applications, overcoming the limitations of conventional computing devices. However, unpredictable switching behavior and poor mechanical stability in conventional memristors present significant challenges to achieving device reliability. Here, a reliable and flexible memristor using zirconium‐oxo cluster (Zr6O4OH4(OMc)12) as the resistive switching layer is demonstrated. The optimization of the structural rigidity of the hybrid oxo‐cluster network by thermal polymerization allows the precise formation of dispersed conductive cluster networks, enhancing the repeatability of the resistive switching with mechanical flexibility. The optimized memristor exhibits endurance of ∼104 cycles and stable memory retention performance up to 104 s, maintaining a high ION/IOFF ratio of 104 under a bending radius of 2.5 mm. Moreover, the device achieves a pattern recognition accuracy of 97.44%, enabled by highly symmetric analog switching with multilevel conductance states. These results highlight that hybrid metal‐oxo clusters can provide novel material design principles for flexible and reliable neuromorphic applications, contributing to the development of artificial neural networks. |
| format | Article |
| id | doaj-art-3eeecfa01fdd477ba72db7c26d61b63e |
| institution | OA Journals |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-3eeecfa01fdd477ba72db7c26d61b63e2025-08-20T02:24:47ZengWileyAdvanced Science2198-38442025-03-011211n/an/a10.1002/advs.202412289Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic ComputingJae‐Hyeok Cho0Suk Yeop Chun1Ga Hye Kim2Panithan Sriboriboon3Sanghee Han4Seung Beom Shin5Jeehoon Kim6San Nam7Yunseok Kim8Yong‐Hoon Kim9Jung Ho Yoon10Myung‐Gil Kim11School of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaKU‐KIST Graduate School of Converging Science and Technology Korea University Seoul 02841 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaSchool of Advanced Materials Science and Engineering Sungkyunkwan University Suwon 16419 Republic of KoreaAbstract Flexible memristors are promising candidates for multifunctional neuromorphic computing applications, overcoming the limitations of conventional computing devices. However, unpredictable switching behavior and poor mechanical stability in conventional memristors present significant challenges to achieving device reliability. Here, a reliable and flexible memristor using zirconium‐oxo cluster (Zr6O4OH4(OMc)12) as the resistive switching layer is demonstrated. The optimization of the structural rigidity of the hybrid oxo‐cluster network by thermal polymerization allows the precise formation of dispersed conductive cluster networks, enhancing the repeatability of the resistive switching with mechanical flexibility. The optimized memristor exhibits endurance of ∼104 cycles and stable memory retention performance up to 104 s, maintaining a high ION/IOFF ratio of 104 under a bending radius of 2.5 mm. Moreover, the device achieves a pattern recognition accuracy of 97.44%, enabled by highly symmetric analog switching with multilevel conductance states. These results highlight that hybrid metal‐oxo clusters can provide novel material design principles for flexible and reliable neuromorphic applications, contributing to the development of artificial neural networks.https://doi.org/10.1002/advs.202412289flexible memristorsmetal‐oxo clustersneuromorphic computingssynaptic devicesZr6O4OH4(OMc)12 |
| spellingShingle | Jae‐Hyeok Cho Suk Yeop Chun Ga Hye Kim Panithan Sriboriboon Sanghee Han Seung Beom Shin Jeehoon Kim San Nam Yunseok Kim Yong‐Hoon Kim Jung Ho Yoon Myung‐Gil Kim Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing Advanced Science flexible memristors metal‐oxo clusters neuromorphic computings synaptic devices Zr6O4OH4(OMc)12 |
| title | Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing |
| title_full | Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing |
| title_fullStr | Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing |
| title_full_unstemmed | Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing |
| title_short | Flexible Synaptic Memristors With Controlled Rigidity in Zirconium‐Oxo Clusters for High‐Precision Neuromorphic Computing |
| title_sort | flexible synaptic memristors with controlled rigidity in zirconium oxo clusters for high precision neuromorphic computing |
| topic | flexible memristors metal‐oxo clusters neuromorphic computings synaptic devices Zr6O4OH4(OMc)12 |
| url | https://doi.org/10.1002/advs.202412289 |
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