Flexible Parylene C-Based RRAM Array for Neuromorphic Applications
Resistive random-access memory (RRAM) has been explored to implement neuromorphic systems to accelerate neural networks. In this study, an RRAM crossbar array using parylene C (PPXC) as both a resistive switching layer and substrate was fabricated. PPXC is a flexible and transparent polymer with exc...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9910149/ |
| _version_ | 1811250097957109760 |
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| author | Jo-Eun Kim Boram Kim Hui Tae Kwon Jaesung Kim Kyungmin Kim Dong-Wook Park Yoon Kim |
| author_facet | Jo-Eun Kim Boram Kim Hui Tae Kwon Jaesung Kim Kyungmin Kim Dong-Wook Park Yoon Kim |
| author_sort | Jo-Eun Kim |
| collection | DOAJ |
| description | Resistive random-access memory (RRAM) has been explored to implement neuromorphic systems to accelerate neural networks. In this study, an RRAM crossbar array using parylene C (PPXC) as both a resistive switching layer and substrate was fabricated. PPXC is a flexible and transparent polymer with excellent chemical stability and biocompatibility. We studied PPXC-based RRAM devices with Ti/PPX-C/Cu and Cu/PPX-C/Ti structures. Devices with the Ti/PPX-C/Cu structure offer stable electrical and mechanical characteristics, such as a low set voltage of < 1 V, good retention time of <inline-formula> <tex-math notation="LaTeX">$> 10^{4}$ </tex-math></inline-formula> s, endurance cycles of >300, conductance ON/OFF ratio >10, and can withstand >350 mechanical bending cycles. Additionally, the switching and conduction mechanisms of the devices were carefully investigated by analyzing their electrical, structural, and chemical properties. Finally, we demonstrated the feasibility of the fabricated RRAM array for neuromorphic applications through system-level simulations using the Modified National Institute of Standards and Technology database. The simulation results reflecting the variations of realistic devices demonstrated that the artificial neural network developed using the PPXC-based RRAM array works satisfactorily in pattern recognition tasks. The findings of this study can aid in the development of future wearable neuromorphic systems. |
| first_indexed | 2024-04-12T15:59:04Z |
| format | Article |
| id | doaj.art-2301ee0632154f5c90d9b8f67fd511a5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T15:59:04Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2301ee0632154f5c90d9b8f67fd511a52022-12-22T03:26:16ZengIEEEIEEE Access2169-35362022-01-011010976010976710.1109/ACCESS.2022.32119569910149Flexible Parylene C-Based RRAM Array for Neuromorphic ApplicationsJo-Eun Kim0https://orcid.org/0000-0002-2682-0731Boram Kim1Hui Tae Kwon2Jaesung Kim3https://orcid.org/0000-0003-1510-5107Kyungmin Kim4Dong-Wook Park5Yoon Kim6https://orcid.org/0000-0002-4837-8411School of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaSchool of Electrical and Computer Engineering, University of Seoul, Seoul, South KoreaResistive random-access memory (RRAM) has been explored to implement neuromorphic systems to accelerate neural networks. In this study, an RRAM crossbar array using parylene C (PPXC) as both a resistive switching layer and substrate was fabricated. PPXC is a flexible and transparent polymer with excellent chemical stability and biocompatibility. We studied PPXC-based RRAM devices with Ti/PPX-C/Cu and Cu/PPX-C/Ti structures. Devices with the Ti/PPX-C/Cu structure offer stable electrical and mechanical characteristics, such as a low set voltage of < 1 V, good retention time of <inline-formula> <tex-math notation="LaTeX">$> 10^{4}$ </tex-math></inline-formula> s, endurance cycles of >300, conductance ON/OFF ratio >10, and can withstand >350 mechanical bending cycles. Additionally, the switching and conduction mechanisms of the devices were carefully investigated by analyzing their electrical, structural, and chemical properties. Finally, we demonstrated the feasibility of the fabricated RRAM array for neuromorphic applications through system-level simulations using the Modified National Institute of Standards and Technology database. The simulation results reflecting the variations of realistic devices demonstrated that the artificial neural network developed using the PPXC-based RRAM array works satisfactorily in pattern recognition tasks. The findings of this study can aid in the development of future wearable neuromorphic systems.https://ieeexplore.ieee.org/document/9910149/NeuromorphicRRAMparylene Cartificial neural networkmemristorflexible neuromorphic electronics |
| spellingShingle | Jo-Eun Kim Boram Kim Hui Tae Kwon Jaesung Kim Kyungmin Kim Dong-Wook Park Yoon Kim Flexible Parylene C-Based RRAM Array for Neuromorphic Applications IEEE Access Neuromorphic RRAM parylene C artificial neural network memristor flexible neuromorphic electronics |
| title | Flexible Parylene C-Based RRAM Array for Neuromorphic Applications |
| title_full | Flexible Parylene C-Based RRAM Array for Neuromorphic Applications |
| title_fullStr | Flexible Parylene C-Based RRAM Array for Neuromorphic Applications |
| title_full_unstemmed | Flexible Parylene C-Based RRAM Array for Neuromorphic Applications |
| title_short | Flexible Parylene C-Based RRAM Array for Neuromorphic Applications |
| title_sort | flexible parylene c based rram array for neuromorphic applications |
| topic | Neuromorphic RRAM parylene C artificial neural network memristor flexible neuromorphic electronics |
| url | https://ieeexplore.ieee.org/document/9910149/ |
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