Effect of particle-size distribution and specific surface area of different binder systems on packing density and flow characteristics of cement paste

Abstract The particle-size distribution (PSD) and specific surface area (SSA) of binders significantly affect the fresh and hardened characteristics of cement-based materials. An experimental investigation was undertaken to evaluate the influence of PSD and calculated SSA of various binary and ternary binder systems on flow characteristics, packing density, and compressive strength development of cement paste. The influence of dispersion state of the binder on packing density was evaluated using the wet packing density approach to determine the optimum water demand (OWD) needed to achieve maximum wet density. The modified Andreasen and Andersen (A&A), Rosin–Rammler (RR), and power law grading models were employed to optimize the PSD of binder system to achieve maximum packing density, while maintaining relatively low water demand. The incorporation of high-range water reducing admixture (HRWRA) is shown to decrease the OWD and increase the packing density resulting from greater degree of dispersion of the binder. The combined effect of lower OWD, greater packing density, and higher SCM reactivity results in higher compressive strength. The increase in SSA from 425 to 1600 m2/kg results in an enhancement in packing density from 0.58 to 0.72, while further increase in SSA from 1600 to 2200 m2/kg reduces the packing density from 0.72 to 0.62. Binder systems using a distribution modulus between 0.21 and 0.235 determined from the A&A model exhibited 18%–40% lower minimum water demand (MWD) to initiate flow, 8%–35% higher OWD to reach maximum wet density, and 15%–25% higher packing density compared to the binder with 100% cement. Binder systems with lower A&A distribution modulus resulted in higher relative water demand (RWD) required to increase fluidity, thus reflecting greater level of robustness. Good correlations were established between the A&A distribution modulus, SSA, RR spread factor, and power law distribution exponent.