Zichao Wang, Xuan Zhang, Xuehua Zhou, Mingze Liu, Xuefeng Zhu, Mingchao Zhang, Xuzi Yang, Yinglai Hou, Yuzhang Du, Jie Kong
{"title":"Adaptive memory of hydrogels with tunable hysteresis.","authors":"Zichao Wang, Xuan Zhang, Xuehua Zhou, Mingze Liu, Xuefeng Zhu, Mingchao Zhang, Xuzi Yang, Yinglai Hou, Yuzhang Du, Jie Kong","doi":"10.1039/d5mh01416f","DOIUrl":null,"url":null,"abstract":"<p><p>The creation of adaptive memory based on soft matter, similar to the brain, is an attractive and challenging research area. Hysteresis is closely related to adaptive memory because it involves a system's ability to retain and utilize information about its past states or inputs to influence its current and future behavior. To achieve adaptive memory control, it is highly desirable to develop stimuli-responsive hydrogels with a tunable hysteresis in the volume phase transition. Herein, we propose a one-pot synthesis method to develop environmentally adaptive memory by preparing dual-responsive hydrogels (<i>e.g.,</i> poly(<i>N</i>-isopropylacrylamide-<i>co</i>-acrylic acid)-<i>g</i>-methylcellulose). The range of the hysteresis window in temperature-dependent shape morphing can be adjusted from approximately 0 °C to 17.6 °C by changing the pH stimulus. Furthermore, the thermal hysteresis windows adapt to the surrounding temperature autonomously. The P(NIPAm-<i>co</i>-AAc)-<i>g</i>-MC hydrogel can maintain a series of small hysteresis loops, which are suitable for memorizing multiple states. Applications in microvalves, hydrogel patterns and smart windows are successfully demonstrated, leveraging the intrinsic hysteresis behavior of the hydrogels. The memory function can switch between memorizing and forgetting behavior, and the memory window adapts to environmental stimuli autonomously. This work contributes an innovative strategy to the development of adaptive memory based on soft materials, paving the way for more intelligent systems.</p>","PeriodicalId":87,"journal":{"name":"Materials Horizons","volume":" ","pages":""},"PeriodicalIF":10.7000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Horizons","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1039/d5mh01416f","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The creation of adaptive memory based on soft matter, similar to the brain, is an attractive and challenging research area. Hysteresis is closely related to adaptive memory because it involves a system's ability to retain and utilize information about its past states or inputs to influence its current and future behavior. To achieve adaptive memory control, it is highly desirable to develop stimuli-responsive hydrogels with a tunable hysteresis in the volume phase transition. Herein, we propose a one-pot synthesis method to develop environmentally adaptive memory by preparing dual-responsive hydrogels (e.g., poly(N-isopropylacrylamide-co-acrylic acid)-g-methylcellulose). The range of the hysteresis window in temperature-dependent shape morphing can be adjusted from approximately 0 °C to 17.6 °C by changing the pH stimulus. Furthermore, the thermal hysteresis windows adapt to the surrounding temperature autonomously. The P(NIPAm-co-AAc)-g-MC hydrogel can maintain a series of small hysteresis loops, which are suitable for memorizing multiple states. Applications in microvalves, hydrogel patterns and smart windows are successfully demonstrated, leveraging the intrinsic hysteresis behavior of the hydrogels. The memory function can switch between memorizing and forgetting behavior, and the memory window adapts to environmental stimuli autonomously. This work contributes an innovative strategy to the development of adaptive memory based on soft materials, paving the way for more intelligent systems.