Dual-Mode Photonic Synapse Based on a Lead-Free 2D Ruddlesden–Popper Perovskite for Neuromorphic Vision

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 PEA<sub>2</sub>SnI<sub>4</sub> 2D Ruddlesden-Popper perovskite. By modulation of the applied bias voltage, the PEA<sub>2</sub>SnI<sub>4</sub> 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<sup>-1</sup>. The low dark current of the device allows for a high detectivity of 3.6 × 10<sup>14</sup> 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 PEA<sub>2</sub>SnI<sub>4</sub> device is further illustrated through simulations of image contrast enhancement and edge detection. This work reveals the potential of PEA<sub>2</sub>SnI<sub>4</sub>-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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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-08-16
DOI
https://doi.org/10.1021/acsami.5c10557
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.19

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article

Dual-Mode Photonic Synapse Based on a Lead-Free 2D Ruddlesden–Popper Perovskite for Neuromorphic Vision

Hao‐Cheng Lin, Yung‐Tang Chuang, Hung-Ming Chen, Yu‐Ching Huang et al.
3 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
2.19
article

Dual-Mode Photonic Synapse Based on a Lead-Free 2D Ruddlesden–Popper Perovskite for Neuromorphic Vision

Hao‐Cheng Lin, Yung‐Tang Chuang, Hung-Ming Chen, Yu‐Ching Huang, Hao‐Wu Lin, Chia-Feng Li, Pei‐En Jan, Cheng‐Yueh Chen
article en
3 citations

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 PEA<sub>2</sub>SnI<sub>4</sub> 2D Ruddlesden-Popper perovskite. By modulation of the applied bias voltage, the PEA<sub>2</sub>SnI<sub>4</sub> 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<sup>-1</sup>. The low dark current of the device allows for a high detectivity of 3.6 × 10<sup>14</sup> 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 PEA<sub>2</sub>SnI<sub>4</sub> device is further illustrated through simulations of image contrast enhancement and edge detection. This work reveals the potential of PEA<sub>2</sub>SnI<sub>4</sub>-based photonic synapses for next-generation neuromorphic vision systems, offering an energy-efficient and highly adaptable approach to optoelectronic computing applications.

ACS Applied Materials & InterfacesVol. 17(34)
Ming Chi University of Technology (TW), National Tsing Hua University (TW), Research Center for Applied Science, Academia Sinica (TW), Issues Research (US), Academia Sinica (TW)
National Science and Technology Council
Openalex Percentile: Top 11%
Advanced Memory and Neural Computing
2.19
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