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Bioinspired strategies for making superior graphene composite coatings

石墨烯 材料科学 纳米技术 复合数 钝化 韧性 复合材料 图层(电子)
作者
Jiheng Ding,Hongran Zhao,Haibin Yu
出处
期刊:Chemical Engineering Journal [Elsevier BV]
卷期号:435: 134808-134808 被引量:31
标识
DOI:10.1016/j.cej.2022.134808
摘要

Graphene is the thinnest, strongest and most conductive material ever identified and the best barrier materials known to date, making it the most ideal building blocks for fabricating polymer composite coatings applied in metal corrosion protection. However, graphene nanosheets are typically constructed into macroscopic composite coatings through traditional blending approaches, their beneficial properties may degrade from the aggregation and random orientation of nanosheets, and galvanic corrosion and many other obstacles. Therefore, it still keeps a huge challenge to assembly graphene nanosheets into high-performance graphene-based composite coatings (GCCs) in practical applications. Natural nacre, which is composed of organic and inorganic components arranged in a complicated but amazingly hierarchical structure, shows a unique combination of excellent strength, toughness, stiffness, antipermeation, self-healing property, and possibly extra functionality, enabling it to live through millions of years in the sea with 3.5 wt% NaCl. This provides a gold example and guideline for preparing graphene nanosheets into high-performance and multifunctional GCCs. Regrettably, to date, relatively rare works were reported on nacre-inspired GCCs, and only a several approaches have been established to construct the bioinspired GCCs. This review summarizes recent research on the nacre-inspired GCCs, and discusses the relationship between alignment and properties in several representative orientation approaches. Fundamental properties of the bioinspired GCCs, including barrier, anticorrosion, and passivation properties, were highlighted. Finally, outlooks and challenges were presented for the future to highlight the strategies on how to fabricate high-performance GCCs with expected multifunction.
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