Hydration of Binary Portland Cement Blends Containing Silica Fume: A Decoupling Method to Estimate Degrees of Hydration and Pozzolanic Reaction

摘要

Determination of degrees of hydration/reaction of components of blended cementitious systems (i.e., cement and SCMs: supplementary cementitious materials) is essential to estimate the systems’ properties. Although the best methods for determining degrees of reaction of different SCMs have been recommended by RILEM TC238, they rely on either expensive equipment (e.g., nuclear magnetic resonance) or time-consuming sample preparation and data processing (e.g., backscattered electron image analysis). Furthermore, these methods cannot simultaneously characterize degree of hydration of cement and degree of reaction of SCMs. A novel decoupling method, which can simultaneously estimate the degree of hydration of cement and the degree of reaction of silica fume in binary cementitious materials, is proposed in this study. Based on experimentally determined and theoretically validated stoichiometric parameters of cement hydration and pozzolanic reaction, the contents of calcium hydroxide and hydrate water in pastes are expressed as functions of degree of hydration of cement and degree of reaction of silica fume. With the two contents determined by thermogravimetric analysis, the two degrees can be solved mathematically. It is found that in binary binders the incorporation of silica fume affects hydration kinetics of cement, leading to lower ultimate degree of hydration, shorter dormant stage, and faster hydration in the acceleration stage. As a result, the degree of hydration of cement in blended paste is higher at early ages (e.g., 3 days) but lower at later ages (e.g., 120 days) than that in plain cement paste. In a given blended paste, the degree of reaction of silica fume can be tied to the degree of hydration of cement. The decoupling method is promising for rapid estimations of degrees of hydration/reaction of cementitious materials in a blended system, since it does not require expensive characterization tools or complex data processing methods.