Physics-based modeling of a bi-layer Al₂O₃/Nb₂O₅ analog memristive device.
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This paper proposes the derivation of a physics-based model of an analog memristive device realized as a bi-layer Al2O3/Nb2O5 stack. Memristive crossbar arrays implementing matrix-vector multiplications are a central building block of novel computing-in-memory architectures for artificial neural network and neuromorphic computing applications. The presented memristor shows analog, multi-level switching at high resistances without electroforming and is suitable for crossbar operations with low energy consumption. By including a graphical analysis method of the I-V curves obtained in a quasi-static approach, the dynamic behavior is analyzed with regard to ohmic and Poole-Frenkel behavior. Finally, a compact model, represented by an algebraic differential equation, is proposed and verified by fitting calculated solutions to experimental data.
|Title of host publication||IEEE International Symposium on Circuits and Systems, ISCAS 2022|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|Publication status||Published - May 2022|
|Series||Proceedings - IEEE International Symposium on Circuits and Systems|
|Title||2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022|
|Duration||27 May - 1 June 2022|
Sustainable Development Goals
ASJC Scopus subject areas
- analog memristive device, bi-layer Al2O3/Nb2O5 stack, crossbar array for neuromorphic computing, Physics-based compact model, Poole-Frenkel emission