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Rohit John1 4 Jieun Ko1 2 Wei Lin Leong1 2 3 Nripan Mathews1 4 5

1, Nanyang Technological University, Singapore, , Singapore
4, Nanyang Technological University, Singapore, , Singapore
2, Nanyang Technological University, Singapore, , Singapore
3, Nanyang Technological University, Singapore, , Singapore
5, Energy Research Institute @ NTU (ERI@N), Singapore, , Singapore

Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architectures. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors are demonstrated on rigid and flexible substrates. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm2 V−1 s−1 with good endurance and mechanical stability. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation printable transparent neural circuits.

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