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Studies have shown that in an aqueous suspension of inert glass beads, the yield stress is increased as a function of resting time. This study investigates this unexpected phenomenon, focusing on solid surface potentials, PCE size in ionic solutions, and their possible relations to rheological behaviour with resting time. Results indicated that PCE in artificial pore solution will result in a higher yield stress with time. PCE with lower anionic charges and molecular weight can significantly increase the yield stress after 2 h of resting. The absolute value of the zeta potential grows to a certain degree after resting phase. Dynamic light scattering (DLS) results showed that the size of PCE molecules in ionic solutions increases over time, suggesting an enhanced depletion force or bridging force among glass bead particles, which could be the reasons for the increase in yield stress over time. Furthermore, the possible impacts of the depletion force or bridging force resulting from the PCE size change on the rheological properties of cement suspension are discussed. [ABSTRACT FROM AUTHOR]

Copper slag (CS), an industrial by‐product, can be used as supplementary cementitious materials in the mortar to achieve sustainable development of the copper and the cement industries. However, available evaluation and prediction models for CS cementitious material considering the comprehensive effect of multiple factors are very scarce. In this study, a reliable experimental database with 141 sets of data was developed via compressive strength tests and reviews of the literature at first. Subsequently, the gray correlation analysis was performed to evaluate the correlation between the influencing factors and the compressive strength of mortar with CS addition. The results demonstrated that the strength was most sensitive to the water to binder ratio and CS chemical composition, which could not be ignored to compare and evaluate the strength acquired from different works. Besides, for the same batch CS used in this study, the compressive strength at 3 d depended on the curing program; while it was more easily affected by the CS fineness after 28 d. Finally, a reliable prediction model for the compressive strength of the mortar with CS addition was implemented by the back‐propagation neural network. The established network with four neurons in the hidden layer had a high accuracy as well as a good generalization ability, which can be used as an effective tool for detecting trends of the compressive strength and designing CS‐added mortar with a user‐defined compressive strength. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Resting time effect on the rheological behaviour of glass beads and cement suspension: The role of PCE size and ionic strength." The correction addresses errors in the names of three authors: Alexander Mezhov, Regine von Klitzing, and Schmidt Wolfram. The correct names should appear as Alexander Mezhov, Regine von Klitzing, and SchmidtWolfram. The article has been corrected online. The reference for the original article is provided for further reading. [Extracted from the article]