Ultra‐Sensitive Negative Photoconductivity Transistors via Long‐Afterglow Doping for All‐Optical Encryption

Negative photoconductivity (NPC)-based devices, characterised by the light-induced suppression of electrical conduction, have garnered significant interest for their multifunctional optoelectronic applications, fast light response and broadband spectral adaptability. However, conventional planar heterostructured NPC-based devices exhibit poor device performance owing to interfacial defects that disrupt carrier transport and recombination dynamics. In this study, an innovative bulk doping strategy is presented that incorporates organic long-afterglow materials into polymer semiconductors to achieve high-performance negative photoconductivity transistors (NPTs). The long-afterglow dopants generate long-lived charge separation states that effectively trap gate-modulated majority carriers of polymer semiconductors, enabling persistent NPC with photosensitivity (5.29 × 10⁶) and detectivity (3.40 × 10<sup>13</sup> Jones). In addition, this bulk doping strategy creates abundant trapping sites, which enable intralayer carrier recombination within the doped semiconductor film while maintaining an ultrahigh photosensitivity. Notably, this strategy can be generalised across diverse dopant-semiconductor systems. Furthermore, leveraging these exceptional NPTs, the negative synaptic functionalities are successfully emulated. To highlight its practical potential, system-level applicability is demonstrated by integrating NPTs into a recurrent neural network (RNN) for all-optical encryption/decryption, achieving up to 91% accuracy. This study establishes a general paradigm for high-performance NPC-based devices, unlocking their potential for next-generation optoelectronics and secure neuromorphic systems.

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Publication Details

Journal
Advanced Materials
Published
2025-10-25
DOI
https://doi.org/10.1002/adma.202514723
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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article

Ultra‐Sensitive Negative Photoconductivity Transistors via Long‐Afterglow Doping for All‐Optical Encryption

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2 citations
Advanced Materials
Advanced Memory and Neural Computing
1.46
article

Ultra‐Sensitive Negative Photoconductivity Transistors via Long‐Afterglow Doping for All‐Optical Encryption

Jiangli Han, Rui Huang, Yanhou Geng, Xin Zheng, Ding Ma, Yunfeng Deng, Guifang Dong, Lian Duan, Meiqiu Dong, Lixian Jiang, Yu Zhang, Cheng Xu
article en
2 citations

Abstract

Negative photoconductivity (NPC)-based devices, characterised by the light-induced suppression of electrical conduction, have garnered significant interest for their multifunctional optoelectronic applications, fast light response and broadband spectral adaptability. However, conventional planar heterostructured NPC-based devices exhibit poor device performance owing to interfacial defects that disrupt carrier transport and recombination dynamics. In this study, an innovative bulk doping strategy is presented that incorporates organic long-afterglow materials into polymer semiconductors to achieve high-performance negative photoconductivity transistors (NPTs). The long-afterglow dopants generate long-lived charge separation states that effectively trap gate-modulated majority carriers of polymer semiconductors, enabling persistent NPC with photosensitivity (5.29 × 10⁶) and detectivity (3.40 × 10<sup>13</sup> Jones). In addition, this bulk doping strategy creates abundant trapping sites, which enable intralayer carrier recombination within the doped semiconductor film while maintaining an ultrahigh photosensitivity. Notably, this strategy can be generalised across diverse dopant-semiconductor systems. Furthermore, leveraging these exceptional NPTs, the negative synaptic functionalities are successfully emulated. To highlight its practical potential, system-level applicability is demonstrated by integrating NPTs into a recurrent neural network (RNN) for all-optical encryption/decryption, achieving up to 91% accuracy. This study establishes a general paradigm for high-performance NPC-based devices, unlocking their potential for next-generation optoelectronics and secure neuromorphic systems.

Advanced MaterialsVol. 38(4)
Tianjin University (CN), Ji Hua Laboratory (CN), Henan Academy of Sciences (CN), Institute of Semiconductors (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 15%
Advanced Memory and Neural Computing
1.46
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