Adaptive memory of hydrogels with tunable hysteresis
Zichao Wang1, Xuan Zhang1, Xuehua Zhou1
1MOE Key Lab of Materials Physics and Chemistry in Extraordinary Conditions, Shaanxi Key Lab of Macromolecular Science and Technology, School of Chemistry and Chemical Engineering, Northwestern Polytechnical University, Xi'an, 710072, P. R. China. zhangxuan@nwpu.edu.cn.
Materials Horizons
|October 1, 2025
Summary
Researchers developed dual-responsive hydrogels that exhibit tunable hysteresis, enabling adaptive memory functions in soft materials. These smart hydrogels can autonomously adjust their memory windows, paving the way for intelligent systems.
Area of Science:
- Soft Matter Physics
- Materials Science
- Biomimetic Systems
Background:
- Adaptive memory in soft matter mimics brain function, offering advanced computational capabilities.
- Hysteresis is crucial for memory, enabling systems to retain and utilize past information.
- Stimuli-responsive hydrogels with tunable hysteresis are needed for controlled adaptive memory.
Purpose of the Study:
- To develop dual-responsive hydrogels for adaptive memory applications.
- To achieve tunable hysteresis in the hydrogel's volume phase transition.
- To demonstrate autonomous adaptation of memory windows to environmental stimuli.
Main Methods:
- One-pot synthesis of dual-responsive poly(N-isopropylacrylamide-co-acrylic acid)-g-methylcellulose hydrogels.
- Investigating temperature-dependent shape morphing and hysteresis.
- Utilizing pH as a stimulus to tune the hysteresis window.
Main Results:
- Tunable hysteresis window range from 0 °C to 17.6 °C by adjusting pH.
- Autonomous adaptation of thermal hysteresis windows to ambient temperature.
- Demonstrated ability to memorize multiple states using small hysteresis loops.
- Successful applications in microvalves, hydrogel patterns, and smart windows.
Conclusions:
- The developed hydrogels offer an innovative strategy for creating soft-matter-based adaptive memory.
- The autonomous memory window adaptation and multi-state memorization capabilities are key advancements.
- This research paves the way for more intelligent soft material systems with memory functions.
