Flexible Organic Memristor for Robust Physical Reservoir Computing in Diversified Dynamic Tasks

ABSTRACT Flexible memristor‐based physical reservoir computing (PRC) holds substantial promise for efficient spatiotemporal information processing. However, the narrow environmental reliability of current PRC systems limits their adaptability and tunability, so the diversity of accessible reservoir states often remains constrained and requires task‐specific and finely tuned control. Here, we present a flexible memristor based on the chloro‐substituted organic small molecule dichloro copper phthalocyanine (Cl 2 CuPc) as an efficient thermally assisted physical reservoir. The device exhibits oxygen‐ion‐driven volatile short‐term synaptic behaviors, in which both electrical pulses and ambient temperature modulate the internal conductance states. By leveraging its strong thermal resilience up to 100°C on flexible substrates, the PRC system achieves 32 distinct reservoir states (5‐bit encoding) under combined control of temperature and pulse parameters. Two complementary encoding schemes, specifically time‐multiplexing and spike‐based preprocessing via pulse amplitude and frequency modulation, enable reliable performance across diversified dynamic tasks. High classification accuracies of 98.4% and 88.6% are obtained for human gait recognition and moving‐object monitoring, respectively. This work demonstrates a lightweight, robust, and multifunctional organic memristor‐based PRC platform, offering a scalable and adaptive solution for analog edge computing in dynamic and complex environments.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2025-12-27
DOI
https://doi.org/10.1002/adfm.202531718
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Flexible Organic Memristor for Robust Physical Reservoir Computing in Diversified Dynamic Tasks

W. Q. Li, Jianyu Ming, MingDong YI, Haifeng Ling et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

Flexible Organic Memristor for Robust Physical Reservoir Computing in Diversified Dynamic Tasks

W. Q. Li, Jianyu Ming, MingDong YI, Haifeng Ling, Zhongjie Ren, Haipeng Zhu, Jia Zhou, Wei Huang, Wei Shi, Ye Chen
article en

Abstract

ABSTRACT Flexible memristor‐based physical reservoir computing (PRC) holds substantial promise for efficient spatiotemporal information processing. However, the narrow environmental reliability of current PRC systems limits their adaptability and tunability, so the diversity of accessible reservoir states often remains constrained and requires task‐specific and finely tuned control. Here, we present a flexible memristor based on the chloro‐substituted organic small molecule dichloro copper phthalocyanine (Cl 2 CuPc) as an efficient thermally assisted physical reservoir. The device exhibits oxygen‐ion‐driven volatile short‐term synaptic behaviors, in which both electrical pulses and ambient temperature modulate the internal conductance states. By leveraging its strong thermal resilience up to 100°C on flexible substrates, the PRC system achieves 32 distinct reservoir states (5‐bit encoding) under combined control of temperature and pulse parameters. Two complementary encoding schemes, specifically time‐multiplexing and spike‐based preprocessing via pulse amplitude and frequency modulation, enable reliable performance across diversified dynamic tasks. High classification accuracies of 98.4% and 88.6% are obtained for human gait recognition and moving‐object monitoring, respectively. This work demonstrates a lightweight, robust, and multifunctional organic memristor‐based PRC platform, offering a scalable and adaptive solution for analog edge computing in dynamic and complex environments.

Advanced Functional Materials
Nanjing Tech University (CN), Nanjing University of Posts and Telecommunications (CN), Beijing University of Chemical Technology (CN)
National Natural Science Foundation of China, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province
Openalex Percentile: Top 42%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.