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Published on: May 13, 2020
Volatile and Nonvolatile Resistive Switching Coexistence in Conductive Point Hexagonal Boron Nitride Monolayer
Sung Jin Yang1, Liangbo Liang2, Yoonseok Lee3
1Microelectronics Research Center, The University of Texas at Austin, Austin, Texas 78758, United States.
Hexagonal boron nitride (h-BN) atomristors with silver electrodes exhibit both volatile and nonvolatile resistance switching. This behavior depends on conductive bridge strength, controlled by current compliance and device area, enabling dual-function neuromorphic computing.
Area of Science:
- Materials Science
- Nanotechnology
- Solid-State Electronics
Background:
- Metal-insulator-metal (MIM) atomristors based on 2D monolayers show nonvolatile resistive switching.
- Further exploration of 2D resistance switching devices is needed, considering material combinations and future applications.
Purpose of the Study:
- Investigate the coexistence of volatile and nonvolatile switching in monolayer hexagonal boron nitride (h-BN) atomristors.
- Understand the factors influencing the transition between volatile and nonvolatile switching behaviors.
Main Methods:
- Fabrication and characterization of h-BN monolayer atomristors with silver (Ag) electrodes.
- Analysis of switching behavior under varying current compliance and atomristor areas.
- Computational modeling to understand conductive bridge formation.
Main Results:
- Demonstrated coexistence of volatile and nonvolatile switching in h-BN/Ag atomristors.
- Transition attributed to the thickness and stiffness of conductive bridges between h-BN and Ag.
- Current compliance controls Ag atom dissociation; device area influences electric field localization and bridge stability.
Conclusions:
- Weak conductive bridges lead to volatile switching, while strong bridges result in nonvolatile switching.
- h-BN atomristors with Ag electrodes offer potential for integrating volatile neurons and nonvolatile synapses in neuromorphic arrays.
- Electrical and dimensional design choices are key for creating dual-function neuromorphic devices.
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