{"title":"Quantifying defects in graphene oxide structures","authors":"Sownyak Mondal, Soumya Ghosh","doi":"10.1016/j.cartre.2024.100323","DOIUrl":null,"url":null,"abstract":"<div><p>Oxidation of graphite and subsequent exfoliation leads to single layer graphene oxide (GO). One of the key structural features of GO is the presence of different kinds of defects that dictates their various physical and chemical properties. Molecular dynamics simulations with ReaxFF force fields have been widely used to generate realistic models of GO. In these simulations, the extent and distribution of the defects are varied by changing the initial oxygen (O)/carbon (C) ratio while the defect density is often measured by the total number of non-graphitic carbon (non-gC) atoms. Our calculations suggest that this parameter overestimates the defect densities at low O/C ratio. Herein, we employ the relative area of the defects as an alternative metric to gauge the defect density. Being exclusive to the defects and sensitive to the structural irregularities, this metric works well at both low and high defect densities. In another example, we consider the reduction of GO to reduced graphene oxide (rGO) for different O/C ratios, where the decrease in the number of non-gC atoms is associated with the formation of comparatively larger defects. Hence, it is unclear whether the extent of reduction in the defect density (if at all) should vary monotonically with the O/C ratio. The defect area, unlike the count of the non-gC atoms, mirrors this ambiguity and the change with respect to O/C ratio is not strictly monotonic. Additionally, we also investigate the dependence of the defect distribution and defect area on the size of the simulation cell.</p></div>","PeriodicalId":52629,"journal":{"name":"Carbon Trends","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266705692400004X/pdfft?md5=dcf53da0c17aa7fddc50bcf02631ec93&pid=1-s2.0-S266705692400004X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Carbon Trends","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266705692400004X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Oxidation of graphite and subsequent exfoliation leads to single layer graphene oxide (GO). One of the key structural features of GO is the presence of different kinds of defects that dictates their various physical and chemical properties. Molecular dynamics simulations with ReaxFF force fields have been widely used to generate realistic models of GO. In these simulations, the extent and distribution of the defects are varied by changing the initial oxygen (O)/carbon (C) ratio while the defect density is often measured by the total number of non-graphitic carbon (non-gC) atoms. Our calculations suggest that this parameter overestimates the defect densities at low O/C ratio. Herein, we employ the relative area of the defects as an alternative metric to gauge the defect density. Being exclusive to the defects and sensitive to the structural irregularities, this metric works well at both low and high defect densities. In another example, we consider the reduction of GO to reduced graphene oxide (rGO) for different O/C ratios, where the decrease in the number of non-gC atoms is associated with the formation of comparatively larger defects. Hence, it is unclear whether the extent of reduction in the defect density (if at all) should vary monotonically with the O/C ratio. The defect area, unlike the count of the non-gC atoms, mirrors this ambiguity and the change with respect to O/C ratio is not strictly monotonic. Additionally, we also investigate the dependence of the defect distribution and defect area on the size of the simulation cell.