Battery-Inspired Electrochemical Synapses for Neuromorphic Applications.

Artificial synapses capable of analog memory and adaptive learning are key components for neuromorphic computing systems. To emulate biological synaptic functions effectively, artificial devices must exhibit gradual conductance modulation, linear responses to pulse stimuli, diverse forms of synaptic plasticity, and low-power operation. Ion-mediated electrochemical devices have recently emerged as promising candidates for such functionalities because ionic redistribution can continuously modify the internal electrochemical state of materials and naturally produce history-dependent conductance changes. This review discusses recent advances in battery-ion-inspired synaptic devices that exploit electrochemical processes to implement artificial synaptic behavior. We first outline the fundamental electrochemical mechanisms underlying ion-mediated state modulation, including ion insertion/accumulation, intercalation, migration, and diffusion. We then survey the materials landscape for battery-inspired synaptic devices, covering electrolytes and active channel materials such as transition metal oxides, two-dimensional materials, and organic mixed ionic-electronic conductors. Emerging applications in neuromorphic computing and neuromorphic biosensing are revisited, where ionic dynamics enable the integration of sensing, memory, and computation. Key challenges related to device reliability, scalability, and environmental stability are discussed, together with future perspectives for advancing battery-ion-based neuromorphic technologies.