Jie Cheng, Pan Zhang, Xinyu Ouyang, Weijia Tang, Bing Song, Youwei Zhang, Yu Zheng, Anlian Pan
{"title":"通过电刺激诱导缺陷工程实现二维存储器,用于复杂神经形态计算","authors":"Jie Cheng, Pan Zhang, Xinyu Ouyang, Weijia Tang, Bing Song, Youwei Zhang, Yu Zheng, Anlian Pan","doi":"10.1002/adfm.202416333","DOIUrl":null,"url":null,"abstract":"Defect engineering is extensively utilized in 2D memory devices due to its effectiveness in enhancing charge-trapping ability. However, conventional defect modulation techniques usually introduce only single types of carrier traps and cannot reconfigure trap types and densities after device fabrication. Here, for the first time, electrical stimulation-driven long-range migration of Cu ions within CuInP<sub>2</sub>S<sub>6</sub> (CIPS) films is demonstrated to simultaneously introduce both electron and hole traps and enable reconfigurable modulation of interfacial defect trapping. This process is referred to as “electrical stimulation-induced defect engineering”. By integrating these defect traps and the dual-gate coupling effect, the memory window-to-scan range (MW/S.R) ratio, which reflects the device's charge trapping ability, doubled and peaked at 78.1% at <i>V</i><sub>bg</sub> = ± 80 V. Additionally, the dual-gate memory device based on the graphene/CIPS/h-BN/WSe<sub>2</sub> heterostructure exhibits a maximum on/off ratio reaching 10<sup>7</sup> for multi-level storage states, integrating neuromorphic computing and logic operations within a single platform. With 81 storage states and paired-pulse facilitation (<i>PPF</i>), it achieves ≈90% accuracy in reservoir computing (RC) simulations. These results highlight the potential of electrical stimulation-induced defect engineering for next-generation electronics.","PeriodicalId":112,"journal":{"name":"Advanced Functional Materials","volume":"18 1","pages":""},"PeriodicalIF":18.5000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"2D Memory Enabled by Electrical Stimulation-Induced Defect Engineering for Complicated Neuromorphic Computing\",\"authors\":\"Jie Cheng, Pan Zhang, Xinyu Ouyang, Weijia Tang, Bing Song, Youwei Zhang, Yu Zheng, Anlian Pan\",\"doi\":\"10.1002/adfm.202416333\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Defect engineering is extensively utilized in 2D memory devices due to its effectiveness in enhancing charge-trapping ability. However, conventional defect modulation techniques usually introduce only single types of carrier traps and cannot reconfigure trap types and densities after device fabrication. Here, for the first time, electrical stimulation-driven long-range migration of Cu ions within CuInP<sub>2</sub>S<sub>6</sub> (CIPS) films is demonstrated to simultaneously introduce both electron and hole traps and enable reconfigurable modulation of interfacial defect trapping. This process is referred to as “electrical stimulation-induced defect engineering”. By integrating these defect traps and the dual-gate coupling effect, the memory window-to-scan range (MW/S.R) ratio, which reflects the device's charge trapping ability, doubled and peaked at 78.1% at <i>V</i><sub>bg</sub> = ± 80 V. Additionally, the dual-gate memory device based on the graphene/CIPS/h-BN/WSe<sub>2</sub> heterostructure exhibits a maximum on/off ratio reaching 10<sup>7</sup> for multi-level storage states, integrating neuromorphic computing and logic operations within a single platform. With 81 storage states and paired-pulse facilitation (<i>PPF</i>), it achieves ≈90% accuracy in reservoir computing (RC) simulations. These results highlight the potential of electrical stimulation-induced defect engineering for next-generation electronics.\",\"PeriodicalId\":112,\"journal\":{\"name\":\"Advanced Functional Materials\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":18.5000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Functional Materials\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1002/adfm.202416333\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Functional Materials","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/adfm.202416333","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
2D Memory Enabled by Electrical Stimulation-Induced Defect Engineering for Complicated Neuromorphic Computing
Defect engineering is extensively utilized in 2D memory devices due to its effectiveness in enhancing charge-trapping ability. However, conventional defect modulation techniques usually introduce only single types of carrier traps and cannot reconfigure trap types and densities after device fabrication. Here, for the first time, electrical stimulation-driven long-range migration of Cu ions within CuInP2S6 (CIPS) films is demonstrated to simultaneously introduce both electron and hole traps and enable reconfigurable modulation of interfacial defect trapping. This process is referred to as “electrical stimulation-induced defect engineering”. By integrating these defect traps and the dual-gate coupling effect, the memory window-to-scan range (MW/S.R) ratio, which reflects the device's charge trapping ability, doubled and peaked at 78.1% at Vbg = ± 80 V. Additionally, the dual-gate memory device based on the graphene/CIPS/h-BN/WSe2 heterostructure exhibits a maximum on/off ratio reaching 107 for multi-level storage states, integrating neuromorphic computing and logic operations within a single platform. With 81 storage states and paired-pulse facilitation (PPF), it achieves ≈90% accuracy in reservoir computing (RC) simulations. These results highlight the potential of electrical stimulation-induced defect engineering for next-generation electronics.
期刊介绍:
Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week.
Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.