Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Jia Zhou; Wen Li; Ye Chen; Haowen Qian; Yen-Hung Lin; Ruipeng Li; Zhen Wang; Jin Wang; Wei Shi; Xianwang Tao; Youtian Tao; Haifeng Ling; Wei Huang; Mingdong Yi

doi:10.1038/s41377-025-01986-9

Your Location：

Home >

Browse articles >

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Original Articles

- Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing
- Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing
- Light: Science & Applications 2025年14卷第10期页码：3250-3260
- Affiliations：
  
  1.State Key Laboratory of Flexible Electronics, Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications (NUPT), Nanjing 210023, China
  2.Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
  3.State Key Laboratory of Advanced Displays and Optoelectronics Technologies, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
  4.National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
  5.Key Lab for Flexible Electronics and Institute of Advanced Materials, Nanjing Tech University, Nanjing 211816, China
- Author bio：
  
  Wen Li (iamwli@njupt.edu.cn)
  Youtian Tao (iamyttao@njtech.edu.cn)
  Wei Huang (vc@nwpu.edu.cn)
  Mingdong Yi (iammdyi@njupt.edu.cn)
- Funds：
- DOI：10.1038/s41377-025-01986-9
  中图分类号：
- 收稿：2025-02-18，
  
  修回：2025-07-09，
  
  录用：2025-07-24，
  
  网络出版：2025-09-08，
  
  纸质出版：2025-10-31
- Accepted：
Scan QR Code
Jia Zhou, Wen Li, Ye Chen, 等. Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing[J]. Light: Science & Applications, 2025,14(10):3250-3260.

Zhou, J. et al. Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing. Light: Science & Applications, 14, 3250-3260 (2025).
Jia Zhou, Wen Li, Ye Chen, 等. Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing[J]. Light: Science & Applications, 2025,14(10):3250-3260. DOI： 10.1038/s41377-025-01986-9.

Zhou, J. et al. Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing. Light: Science & Applications, 14, 3250-3260 (2025). DOI： 10.1038/s41377-025-01986-9.

摘要

Abstract

As the demand for edge platforms in artificial intelligence increases

including mobile devices and security applications

the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here

we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing

featuring

and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module

and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore

we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform

we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

关键词

Keywords

references

Xu, X. W. et al. Scaling for edge inference of deep neural networks. Nat. Electron. 1 , 216–222 (2018)..

Zhang, B. et al. 90% yield production of polymer nano-memristor for in-memory computing. Nat. Commun. 12 , 1984 (2021)..

Fu, T. Z. et al. Optical neural networks: progress and challenges. Light Sci. Appl. 13 , 263 (2024)..

Wang, S. J. et al. An organic electrochemical transistor for multi-modal sensing, memory and processing. Nat. Electron. 6 , 281–-291 (2023)..

Wang, C. et al. Parallel in-memory wireless computing. Nat. Electron. 6 , 381–389 (2023)..

Jang, Y. H. et al. Time-varying data processing with nonvolatile memristor-based temporal kernel. Nat. Commun. 12 , 5727 (2021)..

Liu, D. Y. et al. A wearable in-sensor computing platform based on stretchable organic electrochemical transistors. Nat. Electron. 7 , 1176–1185 (2024)..

Wang, M. et al. Tactile near-sensor analogue computing for ultrafast responsive artificial skin. Adv. Mater. 34 , 2201962 (2022)..

Nishioka, D. et al. Edge-of-chaos learning achieved by ion-electron-coupled dynamics in an ion-gating reservoir. Sci. Adv. 8 , eade1156 (2022)..

Zhang, G. H. et al. Functional materials for memristor-based reservoir computing: dynamics and applications. Adv. Funct. Mater. 33 , 2302929 (2023)..

Chai, Y. In-sensor computing for machine vision. Nature 579 , 32–33 (2020)..

Portilla, L. et al. Wirelessly powered large-area electronics for the Internet of Things. Nat. Electron. 6 , 10–17 (2023)..

Liu, K. Q. et al. An optoelectronic synapse based on α-In 2 Se3 with controllable temporal dynamics for multimode and multiscale reservoir computing. Nat. Electron. 5 , 761–773 (2022)..

Zhang, Z. F. et al. In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array. Nat. Commun. 13 , 6590 (2022)..

Zhang, H. T. et al. Reconfigurable perovskite nickelate electronics for artificial intelligence. Science 375 , 533–539 (2022)..

Lian, M. R. et al. Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output. Light Sci. Appl. 13 , 179 (2024)..

Zhong, Y. N. et al. A memristor-based analogue reservoir computing system for rea l-time and power-efficient signal processing. Nat. Electron. 5 , 672–681 (2022)..

Tan,H. W. & van Dijken, S. Dynamic machine vision with retinomorphic photomemristor-reservoir computing. Nat. Commun. 14 , 2169 (2023)..

Sun, L. F. et al. In-sensor reservoir computing for language learning via two-dimensional memristors. Sci. Adv. 7 , eabg1455 (2021)..

Dang, B. J. et al. Reconfigurable in-sensor processing based on a multi-phototransistor–one-memristor array. Nat. Electron. 7 , 991–1003 (2024)..

John, R. A. et al. Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing. Nat. Commun. 13 , 2074 (2022)..

Mennel, L. et al. Ultrafast machine vision with 2D material neural network image sensors. Nature 579 , 62–66 (2020)..

Yang, J. Q. et al. A perovskite memristor with large dynamic space for analog-encoded image recognition. ACS Nano 16 , 21324–21333 (2022)..

Zhou, F. C. & Chai, Y. Near-sensor and in-sensor computing. Nat. Electron. 3 , 664–671 (2020)..

Liang, X. C. et al. Multimode transistors and neural networks based on ion-dynamic capacitance. Nat. Electron. 5 , 859–869 (2022)..

Cui, D. S. et al. Versatile optoelectronic memristor based on wide-bandgap Ga 2 O 3 for artificial synapses and neuromorphic computing. Light Sci. Appl. 14 , 161 (2025)..

Tan, F. et al. Physisorption-assistant optoelectronic synaptic transistors based on Ta 2 NiSe 5 /SnS 2 heterojunction from ultraviolet to near-infrared. Light Sci. Appl. 14 , 122 (2025)..

Zhang, G. H. et al. Polyoxometalate accelerated cationic migration for reservoir computing. Adv. Funct. Mater. 32 , 2204721 (2022)..

Dobryden, I. et al. Dynamic self-stabilization in the electronic and nanomechanical properties of an organic polymer semiconductor. Nat. Commun. 13 , 3076 (2022)..

Jiang, T. et al. Retina-inspired organic neuromorphic v ision sensor with polarity modulation for decoding light information. Light Sci. Appl. 12 , 264 (2023)..

Wu, X. S. et al. Wearable in-sensor reservoir computing using optoelectronic polymers with through-space charge-transport characteristics for multi-task learning. Nat. Commun. 14 , 468 (2023)..

Huang, H. Y. et al. Fully integrated multi-mode optoelectronic memristor array for diversified in-sensor computing. Nat. Nanotechnol. 20 , 93–103 (2025)..

Zhong, Y. N. et al. Dynamic memristor-based reservoir computing for high-efficiency temporal signal processing. Nat. Commun. 12 , 408 (2021)..

Wang, W. C. et al. Neuromorphic sensorimotor loop embodied by monolithically integrated, low-voltage, soft e-skin. Science 380 , 735–742 (2023)..

Berdan, R. et al. Low-power linear computation using nonlinear ferroelectric tunnel junction memristors. Nat. Electron. 3 , 259–266 (2020)..

John, R. A. et al. Optogenetics inspired transition metal dichalcogenide neuristors for in-memory deep recurrent neural networks. Nat. Commun. 11 , 3211 (2020)..

Qing, M. et al. Three-dimensional donor-acceptor-type photoactive material/conducting polyaniline hydrogel complex for sensitive photocathodic enzymatic bioanalysis. Biosens. Bioelectron. 158 , 112179 (2020)..

Chen, L. J. et al. Donor-acceptor conjugated copolymer with high thermoelectric performance: a case study of the oxidation process within chemical doping. Chin. Phys. B 31 , 028507 (2022)..

Liu, J. Q. et al. A bioinspired flexible neuromuscular system based thermal-annealing-free perovskite with passivation. Nat. Commun. 13 , 7427 (2022)..

Hoefler, S. F. et al. The effect of polymer molecular weight on the performance of PTB7-Th:O-IDTBR non-fullerene organic solar cells. J. Mater. Chem. A 6 , 9506–9516 (2018)..

Kang, H. et al. High-performance all-polymer solar cells based on face-on stacked polymer blends with low interfacial tension. ACS Macro Lett. 3 , 1009–1014 (2014)..

Fu, Q. et al. Management of donor and acceptor building blocks in dopant-free polymer hole transport materials for hi gh-performance perovskite solar cells. Angew. Chem. Int. Ed. 61 , e202210356 (2022)..

Dong, Y. F. et al. Orientation dependent molecular electrostatics drives efficient charge generation in homojunction organic solar cells. Nat. Commun. 11 , 4617 (2020)..

Hoang, N. V. et al. Diffusion-enhanced exciton dissociation in single-material organic solar cells. Phys. Chem. Chem. Phys. 23 , 20848–20853 (2021)..

Seo, S. et al. An optogenetics-inspired flexible van der Waals optoelectronic synapse and its application to a convolutional neural network. Adv. Mater. 33 , 2102980 (2021)..

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

暂无数据