Details

Autor(en) / Beteiligte

• Kang, Jaehyun
• Kim, Taeyoon
• Hu, Suman
• Kim, Jaewook
• Kwak, Joon Young
• Park, Jongkil
• Park, Jong Keuk
• Kim, Inho
• Lee, Suyoun
• Kim, Sangbum
• Jeong, YeonJoo

Titel

Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing

Ist Teil von

• Nature communications, 2022-07, Vol.13 (1), p.4040-4040, Article 4040

Ort / Verlag

London: Nature Publishing Group

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Abstract Memristors, or memristive devices, have attracted tremendous interest in neuromorphic hardware implementation. However, the high electric-field dependence in conventional filamentary memristors results in either digital-like conductance updates or gradual switching only in a limited dynamic range. Here, we address the switching parameter, the reduction probability of Ag cations in the switching medium, and ultimately demonstrate a cluster-type analogue memristor. Ti nanoclusters are embedded into densified amorphous Si for the following reasons: low standard reduction potential, thermodynamic miscibility with Si, and alloy formation with Ag. These Ti clusters effectively induce the electrochemical reduction activity of Ag cations and allow linear potentiation/depression in tandem with a large conductance range (~244) and long data retention (~99% at 1 hour). Moreover, according to the reduction potentials of incorporated metals (Pt, Ta, W, and Ti), the extent of linearity improvement is selectively tuneable. Image processing simulation proves that the Ti 4.8% :a-Si device can fully function with high accuracy as an ideal synaptic model.