Development of coarse-grained potential of silica species

ABSTRACT

Understanding the molecular transformation of silica aggregates during silica polymerisation is crucial to control the properties of final products such as zeolite, nanoparticles, mesoporous silica and other polymorphs. Nevertheless, molecular events during synthesis are challenging to probe using experimental techniques. Computational tools are beneficial to probe molecular length and time scales; however, the complex systems with significant degrees of freedom require significant computational resources. In this work, we have developed coarse-grained (CG) potentials for silica system wherein every silica tetrahedron (Si(OH)${}_{4-z}$O${}_z$) having ‘z’ number of bridging oxygen is mapped to a unique CG silica bead ($B_z$). Different composition of these CG silica beads represent a polymerised silica system with varying degrees of condensation. We performed molecular dynamics (MD) simulations of all-atom silica system to obtain reference radial distribution functions between various silica species ($B_i-B_j$), which was used in Monte Carlo simulations of the CG system to obtain CG potentials. We iteratively refined the CG potentials using iterative Boltzmann inversion and inverse Monte Carlo techniques. We found two attractive minima in the CG potential between $B_i-B_j$ arising due to direct and indirect interactions of species representing first and second coordination shells. The strength of CG potential increases for both of minima with increasing number of bridging oxygen in $B_z$ species. We performed MD simulations of CG silica beads using developed CG potentials at two degree of condensations and found equilibrium structure of spherical silica nanoparticle. We found that $B_3$ and $B_4$ species are predominantly located at the centre of nanoparticles, whereas $B_2$ species are present uniformly.

GRAPHICAL ABSTRACT

KEYWORDS:

• Silica system
• coarse-grained potential
• nanoparticle
• molecular simulations

Acknowledgments

Authors acknowledge the computational support from the HPC facility (spacetime) of IIT Bombay. IS thanks Alexander Mirzoev from NTU, Singapore, for his constructive feedback regarding MagiC package.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary information

The document contains additional information on simulation system size and iterative convergence of CG potential.