The effective surface roughness scaling of the gelation surface pattern formation

TL;DR

This paper investigates the surface pattern formation on gelation surfaces, introducing an empirical scaling law for effective surface roughness that depends on temperature, initiator concentration, and oxygen levels.

Contribution

It presents a novel empirical scaling form for surface roughness in gelation patterns, unifying parameter effects into a master curve.

Findings

Surface roughness decreases with lower oxygen and higher initiator concentration.

A unified master curve for surface deformation data is established.

The scaling law enables control over surface patterning degree.

Abstract

The surface pattern formation on a gelation surface is analyzed using an effective surface roughness. The spontaneous surface deformation on DiMethylAcrylAmide (DMAA) gelation surface is controlled by temperature, initiator concentration, and ambient oxygen. The effective surface roughness is defined using 2-dimensional photo data to characterize the surface deformation. Parameter dependence of the effective surface roughness is systematically investigated. We find that decrease of ambient oxygen, increase of initiator concentration, and high temperature tend to suppress the surface deformation in almost similar manner. That trend allows us to collapse all the data to a unified master curve. As a result, we finally obtain an empirical scaling form of the effective surface roughness. This scaling is useful to control the degree of surface patterning. However, the actual dynamics of this pattern formation is not still uncovered.