Generation of Amorphous Silica Surfaces with Controlled Roughness

Area of Science:

• Materials Science
• Computational Chemistry
• Surface Science

Background:

• Amorphous silica (a-SiO2) surfaces functionalized with metals serve as heterogeneous catalysts.
• A key challenge in modeling these catalysts is generating a-SiO2 slab models with controllable surface roughness.
• Existing computational methods produce either flat or periodically corrugated surfaces, failing to capture realistic roughness.

Purpose of the Study:

• To develop a novel computational method for generating amorphous silica slab models with tunable surface roughness.
• To investigate the impact of surface morphology on the properties and reactivity of a-SiO2 surfaces.

Main Methods:

• A new method inspired by capillary fluctuation theory is introduced, cleaving bulk amorphous silica with a Fourier-transformed Gaussian distribution.
• Surface roughness is controlled by a surface roughness parameter (α).
• Models were generated using the BKS force field, characterized for roughness, density, and ring size, and re-equilibrated with ReaxFF for reactivity studies with water.

Main Results:

• The new method successfully generates a-SiO2 surfaces with varying degrees of roughness.
• Increased surface roughness correlates with a higher concentration of surface defects, including under-/overcoordinated atoms and strained rings.
• Rougher surfaces exhibit increased silanol concentrations and bimodal acidity upon exposure to water, indicating higher reactivity.

Conclusions:

• The developed method provides a controllable way to model amorphous silica surface roughness.
• Surface roughness significantly influences the defect concentration and reactivity of a-SiO2 surfaces.
• This work facilitates more accurate molecular modeling of amorphous silica-based heterogeneous catalysts.