journal article·2024-10Open access

Reliable Low‐Current and Multilevel Memristive Electrochemical Neuromorphic Devices with Semi‐Metal Sb Filament

Chenyu Zhuge, Yukun Zhang, Jiandong Jiang, Xiang Li, Yanfei Zhao, Yujun Fu, Qi Wang, Deyan He

Small· Volume 20· Issue 42

Abstract

Abstract Memristors are used in artificial neural networks owing to their exceptional integration capabilities and scalability. However, traditional memristors are hampered by limited resistance states and randomness, which curtails their application. The migration of metal ions critically influences the number of conductance states and the linearity of weight updates. Semi‐metal filaments can provide subquantum conductance changes to the memristors due to the smaller single‐atom conductance, such as Sb (≈0.01 G 0 = 7.69 × 10 −7 S). Here, a memristor featuring an active electrode composed of semi‐metal Sb is introduced for the first time. This memristor demonstrates precise conductance control, a large on/off ratio, consistent switching, and prolonged retention exceeding 10 5 s. Density functional theory (DFT) calculations and characterization methods reveal the formation of Sb filaments during a set process. The interaction between Sb and O within the dielectric layer facilitates the Sb filaments' ability to preserve their morphology in the absence of electric fields.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Transition Metal Oxide Nanomaterials · Neuroscience and Neural Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Materials and Energy Lanzhou University Lanzhou 730000 China

Funding

National Natural Science Foundation of China

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