High-Resolution Full-Field Structural Microscopy of the Voltage-Induced Filament Formation in VO2-Based Neuromorphic Devices

Year: 2025

Type: article

Abstract: Neuromorphic functions in memristive devices, linked to electrically induced resistive switching to form conductive pathways, could be made more efficient by insights into filament formation at micro- and mesoscopic levels. Despite extensive research on VO2, a key material for its filament formation, local operando structural measurements are highly challenging and often involve destructive specimen preparation and long rastering time, which greatly limits the scope of experimental studies. Utilizing dark-field X-ray microscopy (DFXM), a novel full-field X-ray imaging technique, we explored structural signatures of the filament formation process operando in VO2 devices. Our DFXM experiments display that rutile filaments contain isolated monoclinic clusters, indicating structural non-uniformity of the filament. We also show that the formation of the rutile phase beneath device electrodes precedes filament development, with filament paths then guided by nucleation sites within the device. Finally, we observed a new medium-term memory mechanism in VO2 mediated by sites that tend to switch at significantly lower voltages after electrical cycling, a tendency that persists through brief cooling. High spatial resolution, large field-of-view, structure selectivity, and fast signal acquisition of DFXM enabled first-of-their-kind measurements providing unprecedented insight into subtle structural features of the filamentary channel and surrounding regions during voltage cycling.

Source: ACS Nano

DOI: 10.1021/acsnano.4c14696

Authors: Elliot Kisiel, Pavel Salev, Ishwor Poudyal, David J. Alspaugh, Fellipe Carneiro, Erbin Qiu, Fanny Rodolakis, Zhan Zhang, Oleg G. Shpyrko, Marcelo Rozenberg, Ivan K. Schuller, Zahir Islam, Alex Frano

Institutions: Argonne National Laboratory, University of California San Diego, University of Denver, Los Alamos National Laboratory, Centro Brasileiro de Pesquisas Físicas, Université Paris-Sud, Centre National de la Recherche Scientifique, Laboratoire de physique des Solides

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,500

Funders: National Science Foundation, U.S. Department of Energy, Office of Science, University of California, San Diego, Division of Electrical, Communications and Cyber Systems, Basic Energy Sciences, Argonne National Laboratory, Los Alamos National Laboratory, Energy Frontier Research Centers

OpenAlex ID: W4409433039