新型炭材料（中英文）2026，Vol.41Issue(2)：336-348,13.DOI:10.1016/S1872-5805(25)61036-5
通过完全氧化大片天然石墨实现低成本制备大片氧化石墨烯
Low-cost synthesis of large graphene oxide flakes by the total oxidation of large natural graphite flakes
摘要
Abstract
Large graphene oxide(LGO)sheets have significant advantages over smaller ones in various applications.However,producing them by the Hummers-type oxidation of large natural graphite flakes is challenging.The inherent limiting factors are generally believed to be that large graphite flakes are both diffi-cult to oxidize fully and prone to fragmentation during the pro-cess.By in-situ monitoring the graphite oxidation,we observed that,given sufficient time,large graphite flakes may be fully ox-idized while still remaining largely intact.Graphite oxidation is governed by diffusion of the oxidizer between the layers,and is described by Fick's law,where a high oxidizer concentration gradient increases the diffusion rate.We therefore increased the oxidizer concentration by minimizing the amount of solvent(concentrated H2SO4),achieving full oxidation of gram-scale large graphite flakes in a semi-solid state with significantly reduced reagent consumption.In addition,the reaction temperature was adjusted to balance graphite oxidation and Mn(VII)self-decomposition.Using this approach,gram-scale 200-,100-,and 50-mesh natural graphite were all fully oxidized with a significantly reduced consumption of both H2SO4 and KMnO4.A reduction in size occurs during exfoliation,yielding LGO with average sizes of 27.3,58.7,116.2 μm,respectively.This study not only provides a scalable and cost-effective strategy for LGO production but also advances the understanding of Hummers-type meth-ods.关键词
大片氧化石墨烯/原位监测/氧化/氧化剂浓度Key words
Large graphene oxide/In-situ monitoring/Oxidation/Oxidizer concentration分类
化学化工引用本文复制引用
张元元,吕伟,杜鸿达,康飞宇,麦键彬,陈威,张文龙,刘婧,廖华平,安军伟,王炯辉,黄冬梅..通过完全氧化大片天然石墨实现低成本制备大片氧化石墨烯[J].新型炭材料（中英文）,2026,41(2):336-348,13.基金项目
This work was supported by the National Natur-al Science Foundation of China(52372086),Open Bidding for Selecting the Best Candidates Program of Ulanqab City(2022JB005),Shenzhen Outstanding Talents Training Fund(RCJC20200714114436091),Guangdong Basic and Applied Basic Research Found-ation(2023B1515120047),and Shenzhen Science and Technology Program Project(KJZD20230923114204008). 国家自然科学基金(52372086) （52372086）
乌兰察布揭榜挂帅项目(2022JB005) （2022JB005）
深圳市杰出人才培养项目(RCJC20200714114436091) （RCJC20200714114436091）
广东省基础与应用基础研究基金(2023B1515120047) （2023B1515120047）
深圳市科技计划项目(KJZD20230923114204008). （KJZD20230923114204008）
