DOAJ Open Access 2023

Device-circuit co-design of memristor-based on niobium oxide for large-scale crossbar memory

Avinash Kumar Gupta Mani Shankar Yadav Brajesh Rawat

Abstrak

Memristor-based crossbar architecture emerges as a promising candidate for 3-D memory and neuromorphic computing. However, the sneak current through the unselected cells becomes a fundamental roadblock to their development, resulting in misreading and high power consumption. In this regard, we theoretically investigate the Pt/Ti/NbO2/Nb2O5−x/Pt-based self-selective memristor, which combines the inherent nonlinearity of the NbO2 switching layer and the non-volatile operation of the Nb2O5−x memory layer in a single device. The results show that the Pt/Ti/NbO2/Nb2O5−x/Pt-based self-selective memristor offers the sneak current of 310 nA, selectivity of around 174, and on/off current ratio of 75, compared to the sneak current of approximately 70 μA, selectivity of about 4.02, and on/off current ratio of around 1.55 for the Pt/Ti/Nb2O5−x/Pt-based memristor device. Our self-selective memristor minimizes the sneak current, but a small on/off current ratio limits their readout margin and power efficiency for crossbar array size greater than 4KB. Further, we demonstrate that breaking down a large-scale crossbar array into smaller subarrays and separating them by transistor switches, called the split crossbar array, is a more efficient way of achieving a practical size crossbar array with improved readout margin and power efficiency. Our results shed light on the potential of the Pt/Ti/NbO2/Nb2O5−x/Pt-based self-selective memristor and explore the split crossbar array architecture as a practical solution to augment readout margins and power efficiency in a large-scale crossbar array.

Penulis (3)

A

Avinash Kumar Gupta

M

Mani Shankar Yadav

B

Brajesh Rawat

Format Sitasi

Gupta, A.K., Yadav, M.S., Rawat, B. (2023). Device-circuit co-design of memristor-based on niobium oxide for large-scale crossbar memory. https://doi.org/10.1016/j.memori.2023.100080

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Informasi Jurnal
Tahun Terbit
2023
Sumber Database
DOAJ
DOI
10.1016/j.memori.2023.100080
Akses
Open Access ✓