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Dual-Mode Photonic Synapse Based on a Lead-Free 2D Ruddlesden-Popper Perovskite for Neuromorphic Vision
Cheng-Yueh Chen1, Hao-Cheng Lin1, Pei-En Jan1
1Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan.
Abstract:
Inspired by the human visual system, photonic synapses with photonic sensing and data memorization offer a promising alternative to traditional von Neumann architectures for neuromorphic computing. This study introduces a multifunctional artificial photonic synapse based on solution-processed PEA2SnI4 2D Ruddlesden-Popper perovskite. By modulation of the applied bias voltage, the PEA2SnI4 device can switch between two distinct optoelectronic modes. In the absence of bias, the device operates in the photodetector mode, demonstrating a responsivity of 42.4 mA W-1. The low dark current of the device allows for a high detectivity of 3.6 × 1014 Jones and a broad linear dynamic range of 140 dB. Under reverse bias, the device transitions into a synaptic mode, enabling the observation of several synaptic behaviors, including paired-pulse facilitation, long-term potentiation, spike-frequency-dependent plasticity, and spike-number-dependent plasticity. The synaptic behavior is attributed to band alignment and carrier accumulation in the interfacial layer. Moreover, the synaptic performance of the PEA2SnI4 device is further illustrated through simulations of image contrast enhancement and edge detection. This work reveals the potential of PEA2SnI4-based photonic synapses for next-generation neuromorphic vision systems, offering an energy-efficient and highly adaptable approach to optoelectronic computing applications.
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