Polymerization kinetics of a multi-functional silica precursor studied using a novel Monte Carlo simulation technique

Area of Science:

• Materials Science
• Computational Chemistry
• Chemical Engineering

Background:

• Silica polymerization is crucial for synthesizing advanced materials.
• Current methods rely on heuristic parameter adjustments.
• Understanding molecular events is key to controlling silica synthesis.

Purpose of the Study:

• Develop algorithms to simulate molecular events in silica polymerization.
• Capture the kinetics and structural evolution during the process.
• Investigate the effect of precursor functionality on polymerization.

Main Methods:

• Reaction Ensemble Monte Carlo (REMC) technique.
• Algorithms to capture translation, rotation, and reactions.
• Simulations of silica precursors with varying functionalities (f2, f3, f4).

Main Results:

• Algorithms accurately capture polymerization kinetics, validated against experimental data for f4 and f3 precursors.
• Simulations reveal that increasing f2 precursor concentration reduces network formation and cluster size.
• Radius of gyration (Rg) correlates with network formation and cluster collapse, and is linked to primitive ring count.

Conclusions:

• The developed algorithms provide robust molecular-level insights into silica polymerization.
• Understanding precursor functionality effects enables tailored silica nanoparticle design.
• This work bridges simulation and experiment for precise material synthesis.