Programming Multi‐Timescale Carrier Dynamics in Circularly Polarized Light Photodetectors for Polarization Neuromorphic Vision
ABSTRACT Reliable recognition of complex scenes remains challenging because physically distinct objects can exhibit similar appearances in conventional intensity images, while dynamically changing environments require continuous temporal information processing. Although circularly polarized light (CPL) provides an additional optical dimension for distinguishing surface reflection properties, integrating efficient polarization perception with multi‐timescale synaptic plasticity in a single material platform remains difficult because these functionalities require fundamentally different carrier dynamics. Here, we demonstrate that donor–acceptor composition engineering in chiral bulk‐heterojunction diodes enables programmable carrier dynamics across multiple timescales. By regulating the balance between carrier transport and trapping, the devices evolve from volatile through quasi‐nonvolatile to nonvolatile synaptic plasticity while preserving efficient CPL photodetection. The optimized composition delivers a photocurrent dissymmetry factor of −0.026, whereas complementary volatile and nonvolatile devices enable cooperative temporal information processing. As a proof of concept, a polarization neuromorphic vision system combining RGB–CPL multidimensional perception and multi‐timescale memory improves static recognition accuracy by 15% and dynamic recognition accuracy by up to 12% compared with conventional systems. This work establishes donor–acceptor composition engineering as a strategy for coordinating optical perception and temporal computation, opening opportunities for polarization‐aware neuromorphic vision and intelligent optoelectronics.
Authors
- Huipeng Chen (ORCID: https://orcid.org/0000-0003-1706-3174)
- Lixuan Liu (ORCID: https://orcid.org/0000-0002-2781-9601)
- Xiaobo Shang (ORCID: https://orcid.org/0000-0002-8032-6486)
- Feihong Zhu
- Lei Ma
- Ruixin Liang
- Jinhang Liu
- Leqiu Wang
Institutions
- Fujian Normal University (CN)
- Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China (CN)
- Fuzhou University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2026-10-14
- DOI
- https://doi.org/10.1002/adfm.79045
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province