DLVO Interactions between Particles and Rough Surfaces: An Extended Surface Element Integration Method

Area of Science:

• Colloid and Surface Science
• Computational Physics
• Materials Science

Background:

• The Surface Element Integration (SEI) method accurately calculates Derjaguin, Landau, Verwey, Overbeek (DLVO) interactions for flat surfaces.
• Surface roughness significantly impacts DLVO interactions, necessitating methods applicable to arbitrary morphologies.
• Existing approximate methods for rough surfaces lack rigor and may not be universally applicable.

Purpose of the Study:

• To derive a more rigorous approximate method for calculating DLVO interactions between particles and surfaces with arbitrary morphology.
• To improve the accuracy of SEI-based calculations for systems with surface roughness.
• To provide a computationally facile yet accurate tool for studying particle adhesion and deposition.

Main Methods:

• Derivation of a new approximate method based on the fundamental scaling laws of DLVO interactions.
• Extension of the Surface Element Integration (SEI) technique to accommodate surface roughness and arbitrary particle/surface shapes.
• Verification of the method by comparing results to exact van der Waals energy calculations for rough surfaces.

Main Results:

• The new approximate method approaches the exact DLVO interaction solution as the separation distance decreases, irrespective of surface morphology.
• The method demonstrates high accuracy at small separations, crucial for modeling adhesion and deposition phenomena.
• Validation confirms the method's reliability when compared against exact calculations for van der Waals forces on rough surfaces.

Conclusions:

• The developed rigorous approximate method offers a significant advancement over previous approaches for calculating DLVO interactions on rough surfaces.
• This method is well-suited for applications in particle adhesion and deposition, where interactions occur at angstrom and nanometer scales.
• The enhanced SEI approach provides a computationally efficient and accurate tool for understanding interfacial phenomena in complex systems.