Hybrid Tuning of Sub‐Filaments to Improve Analog Switching Performance in Memristive Devices Article Swipe
Pan Hu
,
Sushmit Hossain
,
Zerui Liu
,
Deming Meng
,
Yunxiang Wang
,
Tse‐Hsien Ou
,
Hao Yang
,
Buyun Chen
,
Zhi Cai
,
Yudi Shi
,
Mark Barnell
,
Qing Wu
,
Stephen B. Cronin
,
Wei Wu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1002/admt.202300109
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1002/admt.202300109
Memristive devices are promising candidates for analog computing applications such as neuromorphic computation. Larger dynamic ranges and more sufficient multilevel states can enable the significant development of memristor‐based utilizations. Herein, a method to improve the analog switching performance of memristors through a hybrid tuning (coarse and fine tuning) of two sub‐filaments is demonstrated. The creation of sub‐filaments inside the dielectric switching layer is realized by deploying Pt metal islands in the switching layer. Given the different material stack configurations of the two sub‐filaments, they exhibit different switching properties to play the roles of coarse and fine tuning respectively in the memristor. Based on the above mechanism, a Pt/Ta/Al 2 O 3 /Pt island/Al 2 O 3‐x /TiO y /Al 2 O 3‐x /Pt memristor is proposed and fabricated. Through the hybrid tuning of two sub‐filaments, a combined dynamic range of 600 Ω to 50 kΩ is achieved. Compared to the reference Pt/Ta/Al 2 O 3 /Pt memristors (dynamic range: 600 Ω to 8 kΩ), both dynamic range and multilevel resistance states are increased significantly. Meanwhile, the energy efficiency is improved because the resistance of tunable states can be set to larger values. Furthermore, this mechanism can be incorporated into various existing memristors to improve their dynamic range and multilevel states, which extensively enriches the applications of memristors.
Related Topics
Concepts
Memristor
Neuromorphic engineering
Materials science
Stack (abstract data type)
Optoelectronics
Layer (electronics)
Dielectric
Range (aeronautics)
Computer science
Electronic engineering
Nanotechnology
Artificial neural network
Topology (electrical circuits)
Electrical engineering
Engineering
Artificial intelligence
Composite material
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/admt.202300109
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/admt.202300109
- OA Status
- hybrid
- Cited By
- 4
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4376564218
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4376564218Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/admt.202300109Digital Object Identifier
- Title
-
Hybrid Tuning of Sub‐Filaments to Improve Analog Switching Performance in Memristive DevicesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-14Full publication date if available
- Authors
-
Pan Hu, Sushmit Hossain, Zerui Liu, Deming Meng, Yunxiang Wang, Tse‐Hsien Ou, Hao Yang, Buyun Chen, Zhi Cai, Yudi Shi, Mark Barnell, Qing Wu, Stephen B. Cronin, Wei WuList of authors in order
- Landing page
-
https://doi.org/10.1002/admt.202300109Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/admt.202300109Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/admt.202300109Direct OA link when available
- Concepts
-
Memristor, Neuromorphic engineering, Materials science, Stack (abstract data type), Optoelectronics, Layer (electronics), Dielectric, Range (aeronautics), Computer science, Electronic engineering, Nanotechnology, Artificial neural network, Topology (electrical circuits), Electrical engineering, Engineering, Artificial intelligence, Composite material, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 2Per-year citation counts (last 5 years)
- References (count)
-
47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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