Quantitative Disorder Analysis and Particle Removal Efficiency of Polypropylene-Based Masks.

ABSTRACT

We demonstrate a methodology for predicting particle removal efficiency of polypropylene-based filters used in personal protective equipment, based on quantification of disorder in the context of methyl group orientation as structural motifs in conjunction with an Ising model. The corresponding Bragg-Williams order parameter is extracted through either Raman spectro-scopy or scanning electron microscopy. Temperature-dependent analysis verifies the presence of an order-disorder transition, and the methodology is applied to published data for multiple samples. The result is a method for predicting the particle removal efficiency of filters used in masks based on a material-level property.