Coplanar all-solid-state electrolyte-gated IGZO artificial synapses for neuromorphic computing applications

Abstract Brain-inspired neuromorphic computing has been considered as a promising novel paradigm and expected to replace traditional von Neumann architecture. Artificial synapses are recognized as the hardware foundation of neuromorphic computing, while the electrolyte-gated synapse has been proposed for its advantages in emulating biological synapses. Here, we propose a coplanar all-solid-state electrolyte-gated amorphous indium–gallium–zinc–oxide synapse that demonstrates multiple forms of both short- and long-term synaptic plasticity, including inhibitory and excitatory post-synaptic currents, paired-pulse facilitation, and relearning behavior. This artificial synapse not only efficiently executes Boolean operations but also switches between ‘AND’ and ‘OR’ logic types within a single device. Furthermore, it exhibits excellent performance in long-term potentiation and depression, with coefficients of nonlinearity of 0.046 and −0.073, achieving a notable accuracy of 93.2% in simulated handwritten digit recognition. This work emphasizes the significant potential of high-performance all-solid-state electrolyte-gated synapses in driving the development of next-generation neuromorphic computing systems.