Tin Oxide Nanorod Array-Based Photonic Memristors with Multilevel Resistance States Driven by Optoelectronic Stimuli
Source abstract
Abstract
One-dimensional (1D) metal oxide-based photonic memristors, combining information storage and optical response, have shown great potential for the design and development of high-density and high-efficient computing systems beyond the era of von-Neumann architecture and Moore’s law. Here, the functional memristive devices based on SnO x slanted nanorod arrays are demonstrated; wherein both the optical and electrical stimuli have been used to modulate the switching characteristics to achieve multilevel cell operations. The switching characteristics of Al/SnO x /FTO devices include low operating voltages (0.7 V/–0.6 V), moderate ON/OFF ratio (>10), and longer endurance (>10 2 cycles) and retention (>10 3 s) with a self-compliance effect in the dark. Under illumination, ranging from ultraviolet (254 and 365 nm) to visible light (405 and 533 nm), an unusual negative photo response with an enlarged ON/OFF ratio of >10 7 and a faster response time of <8 ms is observed. Additionally, multiple low and high resistance states have been achieved by modulating the programming current and the optical stimulus, respectively. The optoelectronic resistive memory behavior is attributed to the electric field-induced formation and light-stimulated dissolution of oxygen vacancies. Comprehensively, the results suggest that the optical illumination reduces the oxygen ion migration barrier, leading to the dissolution of conductive filaments and thereby locally increasing the OFF state resistance. The fabricated photonic memristors demonstrate the potential applications of metal oxide-based 1D nanostructures for artificial visual memory and optoelectronic applications.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Photoreceptor and optogenetics research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Centre for Nano and Soft Matter Sciences (CeNS), Shivanapura, Bangalore 562162, India
Manipal Academy of Higher Education (MAHE), Manipal 576104, India
Funding
Department of Science and Technology, Ministry of Science and Technology
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