Resistive Switching in Nanodevices
Hannes Raebiger, Antonio Claudio M. Padilha, Alexandre R. Rocha,, Gustavo M. Dalpian

TL;DR
This paper explains resistive switching in nanoscale metal/insulator/metal devices as a result of different spontaneous charge states caused by band bending, revealing the physical mechanism behind resistive state changes.
Contribution
It introduces a physical model based on band bending solutions of Poisson's equation to explain resistive switching, and proposes a new magnetic memristor device with enhanced storage capacity.
Findings
Resistive states correspond to different charge distributions due to band bending.
Switching occurs only at nanoscale and specific bias voltages.
A new magnetic memristor device with increased storage capacity is proposed.
Abstract
Passing current at given threshold voltages through a metal/insulator/metal sandwich structure device may change its resistive state. Such resistive switching is unique to nanoscale devices, but its underlying physical mechanism remains unknown. We show that the different resistive states are due to different spontaneously charged states, characterized by different `band bending' solutions of Poisson's equation. For an insulator with mainly donor type defects, the low-resistivity state is characterized by a negatively charged insulator due to convex band bending, and the high-resistivity state by a positively charged insulator due to concave band bending; vice versa for insulators with mainly acceptor type defects. These multiple solutions coexist only for nanoscale devices and for bias voltages limited by the switching threshold values, where the system charge spontaneously changes and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering
