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High-Resolution Full-Field Structural Microscopy of the Voltage-Induced Filament Formation in VO<sub>2</sub>-Based Neuromorphic Devices

Elliot Kisiel, Pavel Salev, Ishwor Poudyal, David J. Alspaugh, F. B. Carneiro, Erbin Qiu, Fanny Rodolakis, Zhan Zhang, Oleg Shpyrko, M. J. Rozenberg, Iván K. Schuller, Z. Islam, Alex Frañó

2025ACS Nano13 citationsDOIOpen Access PDF

Abstract

High Resolution Image Download MS PowerPoint Slide In order to make neuromorphic functions in memristive devices more efficient, information about the structural properties of filament formation at the micro- and mesoscopic scales is necessary. Despite extensive research on VO 2, a key material due to its filament formation, local operando structural measurements remain challenging and often involve destructive specimen preparation and long rastering times, greatly limiting the scope of experimental studies. Utilizing dark-field X-ray microscopy (DFXM), a full-field imaging modality, structural signatures of the filament formation process operando are revealed in VO 2 devices. DFXM experiments illustrate that rutile filaments contain isolated monoclinic clusters, indicating structural nonuniformity interior to the filament. The formation of the rutile phase beneath device electrodes was shown to precede filament development, followed by the formation of filament paths guided by nucleation sites within the device. Finally, a medium-term (<30 min) memory mechanism is observed in VO 2, mediated by sites within the device gap that tend to switch at significantly lower voltages after electrical cycling, a tendency that persists through a brief thermal reset. High spatial resolution, large field-of-view, structure selectivity, and fast signal acquisition of DFXM provided insight into structural features of the filamentary channel and surrounding regions during voltage cycling.

Topics & Concepts

Neuromorphic engineeringProtein filamentMaterials scienceMicroscopyNanotechnologyOptoelectronicsField (mathematics)Resolution (logic)OpticsComputer sciencePhysicsArtificial neural networkArtificial intelligenceComposite materialMathematicsPure mathematicsAdvanced Memory and Neural ComputingTransition Metal Oxide NanomaterialsCCD and CMOS Imaging Sensors