Spatially Distributed Ramp Reversal Memory in VO2

Author:

Basak Sayan12,Sun Yuxin12,Banguero Melissa Alzate3,Salev Pavel45,Schuller Ivan K.5,Aigouy Lionel3,Carlson Erica W.12,Zimmers Alexandre3ORCID

Affiliation:

1. Department of Physics and Astronomy Purdue University West Lafayette IN 47907 USA

2. Purdue Quantum Science and Engineering Institute West Lafayette IN 47907 USA

3. Laboratoire de Physique et d'Étude des Matériaux ESPCI Paris, PSL Université, CNRS Sorbonne Université Paris 75005 France

4. Department of Physics and Astronomy University of Denver Denver Colorado 80208 USA

5. Department of Physics and Center for Advanced Nanoscience University of California‐San Diego La Jolla California 92093 USA

Abstract

AbstractRamp‐reversal memory has recently been discovered in several insulator‐to‐metal transition materials where a non‐volatile resistance change can be set by repeatedly driving the material partway through the transition. This study uses optical microscopy to track the location and internal structure of accumulated memory as a thin film of VO2 is temperature cycled through multiple training subloops. These measurements reveal that the gain of insulator phase fraction between consecutive subloops occurs primarily through front propagation at the insulator‐metal boundaries. By analyzing transition temperature maps, it is found, surprisingly, that the memory is also stored deep inside both insulating and metallic clusters throughout the entire sample, making the metal‐insulator coexistence landscape more rugged. This non‐volatile memory is reset after heating the sample to higher temperatures, as expected. Diffusion of point defects is proposed to account for the observed memory writing and subsequent erasing over the entire sample surface. By spatially mapping the location and character of non‐volatile memory encoding in VO2, this study results enable the targeting of specific local regions in the film where the full insulator‐to‐metal resistivity change can be harnessed in order to maximize the working range of memory elements for conventional and neuromorphic computing applications.

Funder

Division of Materials Research

U.S. Air Force

H2020 European Institute of Innovation and Technology

U.S. Department of Energy

Publisher

Wiley

Subject

Electronic, Optical and Magnetic Materials

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