Structural evolution of two-dimensional silicates using a "bond-switching" algorithm. Issue 4 (15th December 2020)

• Record Type: Journal Article
• Authors: Boscoboinik, Alejandro M.; Manzi, Sergio J.; Pereyra, Víctor D.; Mas, Walter L.; Boscoboinik, Jorge Anibal
• Is Part Of: Nanoscale. Volume 13:Issue 4(2021)
• Page Start: 2408
• Page End: 2419
• Publication Date: 2020-12-15
• Subjects: Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/d0nr07623f
• Languages: English
• ISSNs: 2040-3364

Abstract

Abstract : Ring size distribution in silicate bilayers obtained from Monte Carlo simulations using a bond-switching algorithm (compared to experimental data) when a temperature gradient is introduced to mimic a crystalline to vitreous domain boundary. Abstract : Silicates are the most abundant materials in the earth's crust. In recent years, two-dimensional (2D) versions of them grown on metal supports (known as bilayer silicates) have allowed their study in detail down to the atomic scale. These structures are self-containing. They are not covalently bound to the metal support but interact with it through van der Waals forces. Like their three-dimensional counterparts, the 2D-silicates can form both crystalline and vitreous structures. Furthermore, the interconversion between vitreous to crystalline structures has been experimentally observed at the nanoscale. While theoretical work has been carried out to try to understand these transformations, a limitation for ab initio methods, and even molecular dynamics methods, is the computational cost of studying large systems and long timescales. In this work, we present a simple and computationally inexpensive approach, that can be used to represent the evolution of bilayer silicates using a bond-switching algorithm. This approach allows reaching equilibrium ring size distributions as a function of a parameter that can be related to the ratio between temperature and the energy required for the bond-switching event. The ring size distributions are compared to experimental data available in the literature.