Affiliation:
1. Department of Biomedical Engineering School of Medicine Tsinghua University Beijing 100084 China
2. School of Biological Science and Medical Engineering Beihang University Beijing 100083 China
3. Center of Double Helix Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen 518055 China
4. Institute for Frontier Science Nanjing University of Aeronautics and Astronautics Nanjing 210016 China
5. Technical Institute of Physics and Chemistry Chinese Academy of Sciences Beijing 100190 China
Abstract
AbstractStorage systems are vital components of electronic devices, while significant challenges persist in achieving flexible memory due to the limitations of existing storage methodologies. Inspired by the polarization and depolarization mechanisms in the human brain, here a novel class of storage principles is proposed and achieve a fully flexible memory through introducing the oxidation and deoxidation behaviors of liquid metals. Specifically, reversible electrochemical oxidation is utilized to modulate the overall conductivity of the target liquid metals, creating a substantial 11‐order resistance difference for binary data storage. To obtain the best storage performance, systematic optimizations of multiple parameters are conducted. Conceptual experiments demonstrate the memory's stability under extreme deformations (100% stretching, 180° bending, 360° twisting). Further tests reveal that the memory performs better when its unit size gets smaller, warranting superior integrability. Finally, a complete storage system achieves remarkable performance metrics, including rapid storage speed (>33 Hz), long data retention capacity (>43200 s), and stable repeatable operation (>3500 cycles). This groundbreaking method not only overcomes the inherent rigidity limitations of existing electronic storage units but also opens new possibilities for innovating neuromorphic devices, offering fundamental and practical avenues for future applications in soft robotics, wearable electronics, and bio‐inspired artificial intelligence systems.
Funder
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science