Neuromorphic computing, inspired by the structure and function of biological neural networks, offers a promising alternative to traditional von Neumann architectures by integrating memory and computation for enhanced energy efficiency and processing speed. Electrochemical ionic synapses (EIS) have emerged as a next-generation memory technology, leveraging the reversible insertion and extraction of mobile ions to modulate conductance. Among various implementations, lithium-ion and proton-based EIS devices have gained attention due to their high tunability, fast response, and energy efficiency. This review delves into recent advancements in EIS technology. Lithium-ion-based EIS devices, employing transition metal oxides such as LiCoO2 and LixTiO2, demonstrate stable and scalable synaptic behavior. Meanwhile, proton-based EIS, utilizing materials like WO3 and MoO3, offer rapid ion transport and complementary metal-oxide-semiconductor compatibility, paving the way for practical neuromorphic hardware. We discuss the critical challenges related to material selection, retention stability, and large-scale integration, while exploring future directions for advancing EIS-based computing. By providing insights into the underlying mechanisms and engineering strategies, this review aims to support the development of energy-efficient and high-performance neuromorphic systems, bringing artificial intelligence closer to the capabilities of the human brain.
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