Exploring Heteroatomic Layer Structures to Enhance Switching Dynamics of Sub-2 nm Memristors
Source abstract
Abstract
In oxide memristors composed of a switching layer and an oxygen vacancy reservoir layer (V O layer), both layers are typically made up of homostructures of the same materials. A question arises: how microscopically are the memristor switching dynamics determined by the structure of these two layers? To answer this question, this work reports an exploratory study of the Vo layer in sub-2 nm memristors by stacking 5–7 constituent atomic heterostructured layers (or 0.6–0.8 nm in Vo layer thickness) of Al 2 O 3 (pristine oxide with negligible V O ), MgO and Ga 2 O 3 (both containing considerable Vo). The study revealed an intriguing correlation between the atomic layer structure and the memristor switching dynamics, including both switching speed and endurance. Specifically, heterostructured MgO/Ga 2 O 3 Vo layer outperformed its homostructured MgO or Ga 2 O 3 counterparts with higher switching speed up to 2 orders of magnitude, and higher endurance and device yield by a significant margin. An in situ scanning probe spectroscopy study revealed that the heterostructure of MgO and Ga 2 O 3 atomic layers contained comparable V O concentrations but different crystalline structures that can reduce the amount of unintended defects formed at the interface and within the above 2–3 atomic layers. This results in a distinct advantage to facilitate high-speed and high-efficiency V O drift from the V O layer to the switching layer, as illustrated in the high switching speed and endurance. This is however not readily available in homostructured V O layers as unintended defects extend through the entire V O layer, which negatively impacts the switching dynamics of the memristors. This result provides critical insights into the correlation between the atomic-scale device design and switching dynamics of ultrathin memristors for various applications of microelectronics and neuromorphic computing, in which switching dynamics play a vital role.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Transition Metal Oxide Nanomaterials · Ga2O3 and related materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
ZenoLeap LLC
Department of Physics & Astronomy
University of Kansas
Department of Physics, Astronomy and Materials Science
Missouri State University
Funding
Translational Impacts · Division of Electrical, Communications and Cyber Systems · Division of Materials Research
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