Controlled Formation of Conduction Channels in Memristive Devices Observed by X‐ray Multimodal Imaging. Issue 35 (3rd August 2022)
- Record Type:
- Journal Article
- Title:
- Controlled Formation of Conduction Channels in Memristive Devices Observed by X‐ray Multimodal Imaging. Issue 35 (3rd August 2022)
- Main Title:
- Controlled Formation of Conduction Channels in Memristive Devices Observed by X‐ray Multimodal Imaging
- Authors:
- Liu, Huajun
Dong, Yongqi
Galib, Mirza
Cai, Zhonghou
Stan, Liliana
Zhang, Lei
Suwardi, Ady
Wu, Jing
Cao, Jing
Tan, Chee Kiang Ivan
Sankaranarayanan, Subramanian K. R. S.
Narayanan, Badri
Zhou, Hua
Fong, Dillon D. - Abstract:
- Abstract: Neuromorphic computing provides a means for achieving faster and more energy efficient computations than conventional digital computers for artificial intelligence (AI). However, its current accuracy is generally less than the dominant software‐based AI. The key to improving accuracy is to reduce the intrinsic randomness of memristive devices, emulating synapses in the brain for neuromorphic computing. Here using a planar device as a model system, the controlled formation of conduction channels is achieved with high oxygen vacancy concentrations through the design of sharp protrusions in the electrode gap, as observed by X‐ray multimodal imaging of both oxygen stoichiometry and crystallinity. Classical molecular dynamics simulations confirm that the controlled formation of conduction channels arises from confinement of the electric field, yielding a reproducible spatial distribution of oxygen vacancies across switching cycles. This work demonstrates an effective route to control the otherwise random electroforming process by electrode design, facilitating the development of more accurate memristive devices for neuromorphic computing. Abstract : While neuromorphic computing provides a means for achieving faster and more energy efficient computations, the accuracy needs improvement by reducing the randomness of memristive behavior. The controlled formation of conduction channels is shown here, as observed by X‐ray multimodal imaging of both oxygen stoichiometry andAbstract: Neuromorphic computing provides a means for achieving faster and more energy efficient computations than conventional digital computers for artificial intelligence (AI). However, its current accuracy is generally less than the dominant software‐based AI. The key to improving accuracy is to reduce the intrinsic randomness of memristive devices, emulating synapses in the brain for neuromorphic computing. Here using a planar device as a model system, the controlled formation of conduction channels is achieved with high oxygen vacancy concentrations through the design of sharp protrusions in the electrode gap, as observed by X‐ray multimodal imaging of both oxygen stoichiometry and crystallinity. Classical molecular dynamics simulations confirm that the controlled formation of conduction channels arises from confinement of the electric field, yielding a reproducible spatial distribution of oxygen vacancies across switching cycles. This work demonstrates an effective route to control the otherwise random electroforming process by electrode design, facilitating the development of more accurate memristive devices for neuromorphic computing. Abstract : While neuromorphic computing provides a means for achieving faster and more energy efficient computations, the accuracy needs improvement by reducing the randomness of memristive behavior. The controlled formation of conduction channels is shown here, as observed by X‐ray multimodal imaging of both oxygen stoichiometry and crystallinity. The results suggest an effective route for controlling the otherwise random electroforming process. … (more)
- Is Part Of:
- Advanced materials. Volume 34:Issue 35(2022)
- Journal:
- Advanced materials
- Issue:
- Volume 34:Issue 35(2022)
- Issue Display:
- Volume 34, Issue 35 (2022)
- Year:
- 2022
- Volume:
- 34
- Issue:
- 35
- Issue Sort Value:
- 2022-0034-0035-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-08-03
- Subjects:
- conduction channels -- deterministic electroforming -- memristive devices -- X‐ray imaging
Materials -- Periodicals
Chemical vapor deposition -- Periodicals
620.11 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1521-4095 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/adma.202203209 ↗
- Languages:
- English
- ISSNs:
- 0935-9648
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.897800
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23294.xml