Rohit John1 2 Natalia Yantara1 3 Nripan Mathews1 2 3

1, Nanyang Technological University, Singapore, , Singapore
2, Nanyang Technological University, Singapore, , Singapore
3, Nanyang Technological University, Singapore, , Singapore

Emulation of brain-like signal processing is the foundation for development of efficient learning circuitry, but few devices offer the dynamic range of tunable conductance necessary for mimicking synapses. A hybrid semiconductor which couples electronic and ionic conduction would enable low-power dynamic tuning of metastable resistance states and unlock novel device architectures. Here, we utilize hybrid organic-inorganic perovskite semiconductors to emulate intracellular ion/neurotransmitter flux dynamics responsible for temporal plasticity in chemical synapses. Our devices display a multimodal response with synaptic signatures observable in multiple outputs. This facilitates pattern recognition and image de-noising using a two-layer neural network with energy consumption four orders of magnitude lower than digital signal-processors. Injection barrier in the films define the degree of synaptic plasticity, more notable for larger organic cations.