Bioinspired extremely rapid self-repairing coatings for long-life repeated features
Bioinspired extremely rapid self-repairing coatings for long-life repeated features
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DOI：
10.1016/j.cej.2021.130568
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发表时间：
2021
影响因子：
15.1
通讯作者：
Kengo Manabe;M. Nakano;K. Miyake;Y. Norikane
中科院分区：
文献类型：
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作者：
Kengo Manabe;M. Nakano;K. Miyake;Y. Norikane
能够对受损区域进行自我修复的新兴材料正吸引着人们对环保和节能的关注。虽然材料弹性在物理上恢复表面凹陷的涂层在实际应用中，但在出现裂纹损伤的情况下，它们不能发挥其自我修复功能。相反，具有重复化学修复能力的涂层却面临着较长的修复时间的挑战。在这里，受头足类动物自我修复机制的启发，开发出了能够超快速修复表面划痕的水诱导自修复涂层。在聚电解质多层膜中引入反离子产生的涂层模仿了头足类动物强烈的β-Sheet结构和非共价分子间相互作用，从而产生了自我修复过程。这些特征导致了强阳离子-多阴离子静电键的减少和非共价聚合物网络的增加。此外，反离子的加入还提高了涂层的吸水性和保水性。离子俘获聚合物网络促进了有疤痕的水平方向的扩张，导致超快自修复率在1岁的S和10岁的S分别达到92%和100%。这些极快的自修复涂层在知识加速和机器学习的情况下具有各种潜在的应用。这里开发的关键技术为构建自修复材料铺平了道路，并为可持续社会的发展做出了贡献。
Emerging materials capable of self-repair to damaged areas are attracting attention for environmental protection and energy reduction. Although coatings whose material elasticity physically restores surface-dents are in practical use, in the case of crack damage, they cannot perform their self-repairing function. Conversely, coatings that exhibit the capacity to repeatedly repair themselves chemically have been challenged by long repair times. Here water-induced, self-repairing coatings inspired by cephalopod self-healing mechanisms were developed that can ultra-rapidly repair surface scratches. The introduction of counter-ions into polyelectrolyte multilayers produced coatings mimicking the strongβ-sheet structures, noncovalent intermolecular interactions, and consequently self-repair process in cephalopods. These features resulted in a decrease in the strong polycation–polyanion electrostatic bonds and an increase in the noncovalent polymer networks. Furthermore, counter-ion addition improved the coating’s water absorption and retention properties. The ion-trapped polymer networks facilitated expansion in the horizontal direction where a scar was present, resulting in ultrafast self-repairing rate of 92% in 1 s and 100% in 10 s. These extremely rapidly self-repairing coatings have various potential applications given knowledge accelerationviamachine learning. The key technology developed here paves the way for novel insights into the construction of self-repairing materials and contributes to the development of a sustainable society.