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Multi-Level Resistive Al/Ga 2 O 3 /ITO Switching Devices with Interlayers of Graphene Oxide for Neuromorphic Computing.

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Title: Multi-Level Resistive Al/Ga 2 O 3 /ITO Switching Devices with Interlayers of Graphene Oxide for Neuromorphic Computing.
Authors: Wang, Li-Wen1 (AUTHOR) jk220052@gmail.com, Huang, Chih-Wei2 (AUTHOR) william9450504@gmail.com, Lee, Ke-Jing2,3 (AUTHOR) luke.k.j.lee@gmail.com, Chu, Sheng-Yuan1 (AUTHOR) chusy@mail.ncku.edu.tw, Wang, Yeong-Her2,3 (AUTHOR) luke.k.j.lee@gmail.com
Source: Nanomaterials (2079-4991). Jun2023, Vol. 13 Issue 12, p1851. 12p.
Subjects: Nonvolatile random-access memory, Semiconductor materials, Nonvolatile memory
Abstract: Recently, resistive random access memory (RRAM) has been an outstanding candidate among various emerging nonvolatile memories for high-density storage and in-memory computing applications. However, traditional RRAM, which accommodates two states depending on applied voltage, cannot meet the high density requirement in the era of big data. Many research groups have demonstrated that RRAM possesses the potential for multi-level cells, which would overcome demands related to mass storage. Among numerous semiconductor materials, gallium oxide (a fourth-generation semiconductor material) is applied in the fields of optoelectronics, high-power resistive switching devices, and so on, due to its excellent transparent material properties and wide bandgap. In this study, we successfully demonstrate that Al/graphene oxide (GO)/Ga2O3/ITO RRAM has the potential to achieve two-bit storage. Compared to its single-layer counterpart, the bilayer structure has excellent electrical properties and stable reliability. The endurance characteristics could be enhanced above 100 switching cycles with an ON/OFF ratio of over 103. Moreover, the filament models are also described in this thesis to clarify the transport mechanisms. [ABSTRACT FROM AUTHOR]
Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Label: Title
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  Data: Multi-Level Resistive Al/Ga 2 O 3 /ITO Switching Devices with Interlayers of Graphene Oxide for Neuromorphic Computing.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Li-Wen%22">Wang, Li-Wen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jk220052@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Huang%2C+Chih-Wei%22">Huang, Chih-Wei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> william9450504@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Lee%2C+Ke-Jing%22">Lee, Ke-Jing</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> luke.k.j.lee@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Chu%2C+Sheng-Yuan%22">Chu, Sheng-Yuan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chusy@mail.ncku.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Yeong-Her%22">Wang, Yeong-Her</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<i> luke.k.j.lee@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Nanomaterials+%282079-4991%29%22">Nanomaterials (2079-4991)</searchLink>. Jun2023, Vol. 13 Issue 12, p1851. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Nonvolatile+random-access+memory%22">Nonvolatile random-access memory</searchLink><br /><searchLink fieldCode="DE" term="%22Semiconductor+materials%22">Semiconductor materials</searchLink><br /><searchLink fieldCode="DE" term="%22Nonvolatile+memory%22">Nonvolatile memory</searchLink>
– Name: Abstract
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  Data: Recently, resistive random access memory (RRAM) has been an outstanding candidate among various emerging nonvolatile memories for high-density storage and in-memory computing applications. However, traditional RRAM, which accommodates two states depending on applied voltage, cannot meet the high density requirement in the era of big data. Many research groups have demonstrated that RRAM possesses the potential for multi-level cells, which would overcome demands related to mass storage. Among numerous semiconductor materials, gallium oxide (a fourth-generation semiconductor material) is applied in the fields of optoelectronics, high-power resistive switching devices, and so on, due to its excellent transparent material properties and wide bandgap. In this study, we successfully demonstrate that Al/graphene oxide (GO)/Ga2O3/ITO RRAM has the potential to achieve two-bit storage. Compared to its single-layer counterpart, the bilayer structure has excellent electrical properties and stable reliability. The endurance characteristics could be enhanced above 100 switching cycles with an ON/OFF ratio of over 103. Moreover, the filament models are also described in this thesis to clarify the transport mechanisms. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/nano13121851
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              Text: Jun2023
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              Y: 2023
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