Analysis of Hydration Strength and CO2 Emissions of Cement–Quartz Powder Binary Blends Considering the Effects of Water/Binder Ratios and Quartz Contents

Low-carbon design has become increasingly important in the cement and concrete industry. Previous studies have primarily focused on the impact of different types of admixtures on the carbon emissions of concrete while overlooking the influence of the water-to-cementitious materials ratio on concrete carbon emissions. To address this gap, this study aims to investigate the synergistic effects of the water-to-binder ratio and quartz powder dosage on concrete hydration, strength, and carbon emissions and to propose a comprehensive performance prediction model. Our proposed performance prediction model highlights the critical role of the water-to-cementitious materials ratio in low-carbon concrete design. It distinguishes between the dilution and nucleation effects of the quartz filler and evaluates the impact of quartz content (10% and 20%) and water-to-binder ratios (0.5 and 0.2) on the cement hydration rate; consequently, it is able to predict the concrete’s thermal, chemical, mechanical, and environmental properties. The model specifics are as follows: the parameters were determined using hydration heat data from a paste with a water-to-binder ratio of 0.5 over the first 3 days, and the chemically combined water and portlandite production was calculated up to 28 days. The water availability coefficient, derived from hydration product measurements with a ratio of 0.2, shows that lower water-to-binder ratios slow hydration as the coefficient exceeds 1. A linear equation predicts strength development based on the mix ratio and reaction degree. The CO2 emission analysis shows that when the water/binder ratio is 0.50, with a compressive strength of 1 MPa, the carbon emissions change little with an increase in the quartz powder replacement rate. However, when the water/binder ratio is 0.2, the percentage reductions in CO2 emissions per unit strength are 11% and 20% for the 10% and 20% quartz powder replacement rates, respectively, compared with the specimen without quartz powder. The model’s regression method is simple, versatile across mix ratios, and capable of predicting hydration heat, product composition, strength, and CO2 emissions.