Flexible Memory: Progress, Challenges, and Opportunities
The evolution of information storage technology, from primitive knot‐tying to semiconductor‐based systems, has been pivotal to advancing human civilization. However, rigid storage devices face critical limitations in mechanical compliance, hindering their integration with emerging flexible electronics. Flexible memory technology, leveraging deformable substrates and novel functional materials, promises as a transformative solution to address these challenges. This review systematically interprets the historical trajectory of storage technologies, critically evaluates the strengths and weakness of conventional rigid systems, and proposes a unified framework for flexible memory technologies based on resistive, phase‐change, optical, and magnetic mechanisms. Emphasis is put on the pivotal role of material design—including stretchable organic polymers, liquid materials, and biocompatible hybrids—in achieving mechanical adaptability and functional stability. We further outline a macroscopic energy‐field coupling model to bridge electrical, magnetic, optical, and thermal interactions, providing a theoretical foundation for optimizing flexible memory device performance under dynamic deformation. Finally, we clarify critical challenges in balancing mechanical flexibility with electrical stability, scaling fabrication processes, and achieving neuromorphic integration. The article concludes that flexible memory holds significant potential for applications in wearable electronics, soft robotics, and biomimetic systems, contributing to the continuous innovation in information storage technologies.
Authors
- Minghui Guo
- Jing Liu (ORCID: https://orcid.org/0000-0002-0844-5296)
- Sen Chen (ORCID: https://orcid.org/0000-0003-3061-1497)
- Yujie Du
- Ziliang Cui (ORCID: https://orcid.org/0009-0004-9178-5313)
- Ruizhi Yuan (ORCID: https://orcid.org/0009-0003-6497-404X)
Institutions
- Chinese Academy of Sciences (CN)
- Technical Institute of Physics and Chemistry (CN)
- Beihang University (CN)
- Nanjing University of Aeronautics and Astronautics (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Advanced Intelligent Discovery
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1002/aidi.202500039
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Government of Jiangsu Province
- Natural Science Foundation of Jiangsu Province