3D Off-Lattice Coarse-Grained Monte Carlo Simulations for Nucleation of Alkaline Aluminosilicate Gels.

This work presents a 3D off-lattice coarse-grained Monte Carlo (CGMC) approach to simulate the nucleation of alkaline aluminosilicate gels, their nanostructure particle size, and their pore size distribution. In this model, four monomer species are coarse-grained with different particle sizes. The novelty is extending the previous on-lattice approach from White et al. (2012 and 2020) by implementing a full off-lattice numerical implementation to consider tetrahedral geometrical constraints when aggregating the particles into clusters. Aggregation of the dissolved silicate and aluminate monomers was simulated until reaching the equilibrium condition of 16.46% and 17.04% in particle number, respectively. The cluster size formation was analyzed as a function of iteration step evolution. The obtained equilibrated nano-structure was digitized to obtain the pore size distribution and this was compared with the on-lattice CGMC and measurement results from White et al. The observed difference highlighted the importance of the developed off-lattice CGMC approach to better describe the nanostructure of aluminosilicate gels.

Coarse-Grained Monte Carlo Simulations with Octree Cells for Geopolymer Nucleation at Different pH Values.

Geopolymers offer a potential alternative to ordinary Portland cement owing to their performance in mechanical and thermal properties, as well as environmental benefits stemming from a reduced carbon footprint. This paper endeavors to build upon prior atomistic computational work delving deeper into the intricate relationship between pH levels and the resulting material's properties, including pore size distribution, geopolymer nucleate cluster dimensions, total system energy, and monomer poly-condensation behavior. Coarse-grained Monte Carlo (CGMC) simulation inputs include tetrahedral geometry and binding energy parameters derived from DFT simulations for aluminate and silicate monomers. Elevated pH values may can alter reactivity and phase stability, or, in the structural concrete application, may passivate the embedded steel reinforcement. Thus, we examine the effects of pH values set at 11, 12, and 13 (based on silicate speciation chemistry), investigating their respective contributions to the nucleation of geopolymers. To simulate a larger system to obtain representative results, we propose the numerical implementation of an Octree cell. Finally, we further digitize the resulting expanded structure to ascertain pore size distribution, facilitating a comparative analysis. The novelty of this study is underscored by its expansion in both system size, more accurate monomer representation, and pH range when compared to previous CGMC simulation approaches. The results unveil a discernible correlation between the number of clusters and pores under specific pH levels. This links geopolymerization mechanisms under varying pH conditions to the resulting chemical properties and final structural state.