Artificial synapse based on Co₃O₄ nanoflowers with picojoule energy consumption, microsecond time constant, and visual learning capability

Abstract Metal oxide nanomaterials are promising candidates for neuromorphic systems due to their remarkable physical properties, including atomic-scale thickness and high ionic activity. In this work, Co 3 O 4 nanoflowers were incorporated into artificial synaptic devices, exhibiting both short-term plasticity (e.g. paired-pulse facilitation) and long-term plasticity (e.g. spike-timing-dependent plasticity) with picojoule energy consumption and microsecond time constants. Utilizing the long-term potentiation and depression characteristics of the Co 3 O 4 nanoflower-based artificial synapses, the visual learning capability was demonstrated. X-ray photoelectron spectroscopy depth profiling analysis revealed that the synaptic behavior is primarily governed by the migration of oxygen vacancies. These findings underscore the potential of metal oxide nanoflower-based artificial synapses for use in energy-efficient neuromorphic circuits and complex cognitive systems.