Journal
ADVANCED MATERIALS
Volume 34, Issue 35, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adma.202203209
Keywords
conduction channels; deterministic electroforming; memristive devices; X-ray imaging
Categories
Funding
- U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division [DE-SC0021229]
- NERSC [DE-AC02-05CH11231]
- Office of Basic Energy Sciences [DE-AC02- 06CH11357]
- A*STAR, Singapore [C210812020]
- U.S. Department of Energy (DOE) [DE-SC0021229] Funding Source: U.S. Department of Energy (DOE)
Ask authors/readers for more resources
This research focuses on controlling the formation of conduction channels in memristive devices to improve their accuracy, by utilizing sharp protrusions in the electrode gap. Classical molecular dynamics simulations confirm that this controlled formation arises from confinement of the electric field, leading to a reproducible spatial distribution of oxygen vacancies across switching cycles.
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available