Memristive Fibers for Intelligent Textiles Information Storage and Processing in Multi‐Scenarios
Memristive fibers combine information storage and computing in textile-compatible crossbar arrays, enabling intelligent textiles to process signals from integrated electronics. A simple, cost-effective coating method for complex fiber surfaces with insufficient conductivity or difficult to withstand high pressure plays a key role in textile memristor tech. Here, a high-performance and reliable textile memristor fabricated from robust copper-tin oxide coated carbon fibers (CuSnO@C<sub>f</sub>) memristive fibers through a process involving two-stage selective electroless plating and subsequent thermal oxidation is reported. The surface coating of the memristive fiber includes a self-lopaded active electrode containing metal/intermetallic compounds (metal/IMCs), and a memristive functional layer (bimetallic amorphous oxide), which makes it exhibit a low set voltage (≈0.342 V), long retention time (>10<sup>4</sup> s) for multilevel storage (5 stages), high ON/OFF ratio (up to 6.58 × 10<sup>5</sup>), low energy consumption (34.5 pW), multi conductivity state (24), excellent synaptic plasticity, outstanding stability and durability. Besides, the textile memristor exhibits good repeatability and multi-level storage capability between devices, and can clearly recognize letters (H, V, O) through offline training and weight mapping. Highly compatible with intelligent textiles, the technology enables real-time diagnostics with accurate physiological data analysis. These advanced information processing capabilities will significantly advance intelligent textiles systems.
Authors
- Zizhao Ding
- Zixiang Zhao (ORCID: https://orcid.org/0000-0002-5461-6017)
- Shenglong Huang (ORCID: https://orcid.org/0009-0009-6374-5740)
- Yuh‐Jen Cheng (ORCID: https://orcid.org/0000-0002-0575-4296)
- Chao Jiang (ORCID: https://orcid.org/0000-0001-6367-9936)
- Dou Zhang (ORCID: https://orcid.org/0000-0001-8555-2784)
Institutions
- Central South University (CN)
Publication Details
- Journal
- Small
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1002/smll.202505191
- Citations
- 3
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.19