Zhao Lianjia, Xu Hao, Liu Lingchen, Zheng Yiqiang, Han Wei, Wang Lili
State Key Laboratory for Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences & Center of Materials Science and Optoelectronic Engineering, University of Chinese Academy of Sciences, 100083, Beijing, P. R. China.
College of Physics, State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, International Center of Future Science, Jilin University, 130012, Changchun, P. R. China.
Adv Sci (Weinh). 2023 Oct;10(30):e2303922. doi: 10.1002/advs.202303922. Epub 2023 Sep 6.
As water-saturated polymer networks, hydrogels are a growing family of soft materials that have recently become promising candidates for flexible electronics application. However, it remains still difficult for hydrogel-based strain sensors to achieve the organic unity of mechanical properties, electrical conductivity, and water retention. To address this challenge, based on the template, the excellent properties of MXene nanoflakes (rich surface functional groups, high specific surface area, hydrophilicity, and conductivity) are fully utilized in this study to prepare the P(AA-co-AM)/MXene@PDADMAC semi-interpenetrating network (semi-IPN) hydrogel. The proposed hydrogel continues to exhibit excellent strain response and flexibility after 30 days of storage at room temperature, and its performance do not decrease after 1100 cycles. Considering these characteristics, a hydrogel-based device for converting sign language into Chinese characters is successfully developed and optimized using machine learning. Therefore, this study provides novel insight and application directions for hydrogel families.
作为水饱和聚合物网络，水凝胶是一类不断发展的软材料家族，最近已成为柔性电子应用的有前途的候选材料。然而，基于水凝胶的应变传感器仍难以实现机械性能、导电性和保水性的有机统一。为应对这一挑战，本研究基于该模板充分利用了MXene纳米片的优异性能（丰富的表面官能团、高比表面积、亲水性和导电性）来制备P(AA-co-AM)/MXene@PDADMAC半互穿网络（半IPN）水凝胶。所制备的水凝胶在室温下储存30天后仍表现出优异的应变响应和柔韧性，并且在1100次循环后其性能并未下降。考虑到这些特性，成功开发并利用机器学习优化了一种基于水凝胶的将手语转换为汉字的装置。因此，本研究为水凝胶家族提供了新的见解和应用方向。
