Predicting air-entraining in cement paste from the molecular attributes of nonionic surfactants with a multilayer method

Abstract

The novelty of this study is to present a multilayer framework for predicting the air-entrained porosity of cement paste based on the molecular characteristics of nonionic surfactants. Air-entraining agents enhance concrete durability against freeze–thaw damage; however, their development is labor-intensive and cost-prohibitive. This research implements a multilayer approach by incorporating three hierarchical layers: the molecular properties of nonionic surfactants (Layer 1), their physicochemical characteristics (Layer 2), and the air-entrained microstructural porosity of hardened cement paste (Layer 3). By integrating key molecular parameters—such as hydrocarbon chain length, hydrophobicity, and molecular weight—this model effectively predicts the air-entrained porosity of cement paste. An extensive experimental study was conducted to characterize the physicochemical and microstructural properties of 59 distinct nonionic surfactants. To the best of our knowledge, this represents the first comprehensive dataset of molecular and physicochemical properties of air-entraining agents reported in the literature. Moreover, no prior study has established such a detailed link between the molecular characteristics of nonionic surfactants and cement microstructure. This dataset served as the foundation for developing the predictive model, which demonstrated the feasibility of this approach in predicting the air-entraining performance of nonionic admixtures. The developed model facilitates the rapid screening of candidate surfactants and the optimization of their molecular structure while minimizing the need for extensive experimentation. Furthermore, distinct trends emerged from the dataset, offering new insights into the interdependent properties that govern air entrainment in cementitious materials.