Predicting Dissolution Kinetics of Tricalcium Silicate Using Deep Learning and Analytical Models

oleh: Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar

Format: Article
Diterbitkan: MDPI AG 2022-12-01

Deskripsi

The dissolution kinetics of Portland cement is a critical factor in controlling the hydration reaction and improving the performance of concrete. Tricalcium silicate (C<sub>3</sub>S), the primary phase in Portland cement, is known to have complex dissolution mechanisms that involve multiple reactions and changes to particle surfaces. As a result, current analytical models are unable to accurately predict the dissolution kinetics of C<sub>3</sub>S in various solvents when it is undersaturated with respect to the solvent. This paper employs the deep forest (DF) model to predict the dissolution rate of C<sub>3</sub>S in the undersaturated solvent. The DF model takes into account several variables, including the measurement method (i.e., <i>reactor connected to inductive coupled plasma spectrometer</i> and <i>flow chamber with vertical scanning interferometry</i>), temperature, and physicochemical properties of solvents. Next, the DF model evaluates the influence of each variable on the dissolution rate of C<sub>3</sub>S, and this information is used to develop a closed-form analytical model that can predict the dissolution rate of C<sub>3</sub>S. The coefficients and constant of the analytical model are optimized in two scenarios: <i>generic</i> and <i>alkaline</i> solvents. The results show that both the DF and analytical models are able to produce reliable predictions of the dissolution rate of C<sub>3</sub>S when it is undersaturated and far from equilibrium.