期刊
CARBON
卷 195, 期 -, 页码 387-394出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.carbon.2022.03.067
关键词
Carbon; Graphene; Foam; Density; Scaling law; Compressive strength; Defect
资金
- National Natural Science Foundation of China [52175095, 51775201, 51605172]
- Natural Science Foundation of Hubei Province [2016CFB191]
- Hong Kong Scholars Program [XJ2020043]
- Department of Civil and Environmental Engineering at Syracuse University
Understanding the structure-mechanics relationships in cellular solids is crucial for achieving better mechanics using the same material. In this study, multiscale modeling and computation were employed to investigate the mechanics of hierarchical carbon nanoarchitectures. The density was found to primarily determine the Young's modulus and tensile strength of the graphene network. Additionally, different scaling laws for compressive strength were observed and attributed to various features of the constituent struts.
Understanding the structure-mechanics relationships in cellular solids is essential for using the same material to achieve better mechanics. We use multiscale modeling and computation to investigate the mechanics of a series of hierarchical carbon nanoarchitectures with structural features quantitatively characterized. We find that the Young's modulus and tensile strength of the graphene network are mainly determined by its density. However, different density scaling laws of compressive strength are observed and they are related to the length, diameter, and surface roughness of the constituent struts, the buckling form of which yields different scaling laws. Therein, the graphene network with struts of a higher length-to-diameter ratio, smoother surface, and failure mode of shell buckling has a higher compressive strength for a given overall density and topology. Besides, the topology, bonding mode, and multiscale defects explain the large variance of scaling laws of different carbon materials. The work reveals the great potential of architected cellular carbons and provides insight into their future design. (C) 2022 Elsevier Ltd. All rights reserved.
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