氧化石墨烯/水泥复合净浆的化学收缩特性及预测模型

Chemical shrinkage behavior and prediction model of cement-based composite paste with the addition of graphene oxide

  • 摘要: 为了揭示氧化石墨烯/水泥复合净浆(GO/C)的化学收缩特性,采用体积法对不同水灰比(0.3、0.4、0.5)和不同氧化石墨烯(GO)质量分数(0wt%、0.01wt%、0.02wt%、0.03wt%、0.04wt%、0.05wt%)的水泥复合净浆试件化学收缩进行了测定。试验结果显示:随着水灰比的增加,GO/C化学收缩显著增大。同水灰比条件下掺有氧化石墨烯的GO/C试件前期化学收缩较普通水泥净浆有所下降,当GO质量分数为0.04wt%时,收缩值达到最小;在后期水化中,GO/C试件的化学收缩增长速度明显快于普通水泥净浆。分析表明,GO对水泥净浆孔结构的调控作用和对水化产物氢氧化钙晶体的键合行为是其影响水泥净浆化学收缩性能的主要原因。同时,通过收缩模型与试验值对比发现,现有的普通水泥化学收缩模型无法精准预测GO/C的化学收缩情况,因此,为考虑GO的影响,试验在吴浪模型的基础上,引入K(\xi , t)函数作为影响参数,并通过曲线拟合得到其具体表达式,从而建立起适用于GO/C化学收缩的预测模型。

     

    Abstract: In order to reveal the chemical shrinkage characteristics of graphene oxide cement composite paste (GO/C), the chemical shrinkage of cement composite paste with different water-cement ratio (0.3, 0.4, 0.5) and different mass fractions of graphene oxide (GO) (0wt%, 0.01wt%, 0.02wt%, 0.03wt%, 0.04wt% and 0.05wt%). The results show that the chemical shrinkage of GO/C is significantly increased with an increase in water-cement ratio. At the same water-cement ratio, the early chemical shrinkage of GO/C is lower than that of ordinary cement paste, and when the mass fraction of GO is 0.04wt%, the shrinkage value reaches the minimum. However, the growth rate of chemical shrinkage of GO/C specimens is obviously faster than that of ordinary cement paste in later hydration process. The analysis shows that the influence of GO on the chemical shrinkage of cement paste is mainly attributed to the regulation of GO on the pore structure of cement paste and the bonding behavior of GO with calcium hydroxide crystal. Furthermore, based on the comparison results of existing shrinkage models, it is found that the chemical shrinkage models of ordinary cement cannot accurately predict the chemical shrinkage of GO/C. Therefore, in order to consider the effect of GO, K(\xi , t) function is introduced as an influence parameter on the basis of Wu Lang model, and its specific expression is obtained by curve fitting. Finally, a prediction model suitable for GO/C chemical shrinkage was established.

     

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