Visible‐Light Chiral Photonic Synapses Based on Hybrid Organic‐Inorganic 2D Perovskites

Visible‐Light Chiral Photonic Synapses Based on Hybrid Organic‐Inorganic 2D Perovskites

Abstract This study presents visible‐light chiral photonic synaptic devices based on 2D chiral hybrid organic‐inorganic perovskites (HOIPs), composed of Si/SiO₂/chiral HOIPs/poly(methyl methacrylate)/pentacene/Au, designed for circularly polarized light (CPL)‐active peripheral nervous system (PNS) a...

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Bibliographic Details
Main Authors: In‐Kook Hwang, Min Gu Lee, Jae Bum Jeon, Sang Hyun Nam, Daseul Lee, Changhyeon Lee, Junyoung Kwon, Sung‐Gap Im, Young‐Hoon Kim, Kyung Min Kim, Byong‐Guk Park
Format: Article
Language:English
Published: Wiley-VCH 2025-03-01
Series:Advanced Electronic Materials
Subjects:
chiral hybrid organic‐inorganic perovskites
chiral neuromorphic devices
chiral synaptic devices
circularly polarized light
visible light
Online Access:https://doi.org/10.1002/aelm.202400525
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Summary:Abstract This study presents visible‐light chiral photonic synaptic devices based on 2D chiral hybrid organic‐inorganic perovskites (HOIPs), composed of Si/SiO₂/chiral HOIPs/poly(methyl methacrylate)/pentacene/Au, designed for circularly polarized light (CPL)‐active peripheral nervous system (PNS) applications. In the heterostructure of 2D chiral HOIPs and pentacene, chiral HOIPs effectively distinguish the direction of CPL and the pentacene layer extracts photoinduced charge carriers to achieve synaptic properties, as confirmed by circular dichroism and photoluminescence analyses. The devices exhibit a photocurrent dissymmetry factor of up to 0.3 and a photoresponsivity of 130 mA W−1. Logic operations using a 3 × 4 pixel array of chiral HOIP‐based heterostructures are demonstrated, achieving pattern recognition based on the direction of CPL and pulse interval time. Notably, the efficiency to discriminate CPL direction increases with longer pulse intervals. This improvement enhances the learning capability by amplifying CPL direction discrimination ratios. Leveraging these properties, neural network simulations for neuromorphic applications are conducted, and artificial neural networks are trained for image recognition using the devices as CPL filters, achieving a 92% recognition accuracy. These results signify the beginning of chiral PNS devices communicating with visible CPL based on 2D chiral HOIPs.
ISSN:2199-160X

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