Exploring the Impact of Deposition Conditions on the Functionality of a -IGZO/AlO x -Based Sandwich Structures with Memory Effects
Source abstract
Abstract
Memristors, inspired by the synaptic functions of the human brain, are crucial components for implementing synaptic weights in neuromorphic computing. Among them, semiconductor-oxide-based memristors have attracted significant attention owing to their material versatility and electrical tunability. However, their switching and conduction behaviors remain highly sensitive to fabrication conditions, often resulting in variability and poor reliability. While earlier studies have focused on oxygen vacancy control in either the active or reservoir layers, the combined influence of the plasma deposition environment exposed to the oxide layer, reservoir layer, and their interface for subtle processing variations has not been systematically examined. Here, we investigate amorphous InGaZnO ( a- IGZO)-based memristors with an adjacent aluminum oxide (AlO x ) interfacial layer and demonstrate how minute changes in oxygen plasma conditions for the AlO x layer, along with the oxygen partial pressure during a -IGZO deposition, modulate interfacial oxygen distribution and vacancy stability. These interfacial modifications activate distinct conduction pathways─thermionic emission, thermionic field emission, and trap-assisted tunneling─that govern both steady-state conduction and current relaxation dynamics. Our results reveal that even slight variations in plasma and deposition conditions can induce pronounced shifts in the dominant conduction mechanisms, directly impacting device stability and performance. By establishing the interfacial origin of conduction mechanism transitions and current relaxation, this work advances the understanding of process–property relationships in oxide-based memristors and provides design guidelines for developing more stable and reproducible devices for neuromorphic applications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Thin-Film Transistor Technologies · Transition Metal Oxide Nanomaterials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Division of Nanotechnology
DGIST
Institute of Next-Generation Semiconductor Convergence Technology
Department of Physics and Chemistry
Funding
Ministry of Science and ICT, South Korea · National Research Foundation of Korea · Ministry of Science, ICT and Future Planning
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