title: A novel method for the quantitative determination of defects on graphene surfaces.
abstract: In this work, a novel method for the quantitative determination of defects on graphene surfaces has been presented in order to provide accurate, reliable and quantitative information for the defects on graphene products. It was based on the selective adsorption of a specific polar organic ion (Sodium benzenesulfonate) on the edges and defects on graphene surfaces, and the atomic force microscopy (AFM) imaging of the adsorption. By means of an image processing software, the AFM images could be analyzed and the areas as well as area percentages of the defects on the graphene surfaces could be determined.
authors.affiliation: School of Resources and Environmental Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Yi
authors.affiliation: School of Resources and Environmental Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070, China.
authors.forename: Xian
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Hubei Key Laboratory of Mineral Resources Processing and Environment, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070, China.
authors.forename: Yunliang
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Hubei Provincial Collaborative Innovation Center for High Efficient Utilization of Vanadium Resources, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070, China.
authors.forename: Yanyan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: School of Resources and Environmental Engineering, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070, China; Hubei Key Laboratory of Mineral Resources Processing and Environment, Wuhan University of Technology, Luoshi Road 122, Wuhan, Hubei 430070, China. Electronic address: ssx851215@whut.edu.cn.
authors.forename: Shaoxian
authors.initials: S
authors.lastname: Song
keywords: Atomic force microscopy; Graphene defects; Image processing; Quantitative determination