Issue 14, 2024

The fractal geometry of polymeric materials surfaces: surface area and fractal length scales

Abstract

Using three common polymeric materials (polypropylene (PP), polytetrafluoroethylene (PTFE) and polycaprolactone (PCL)), a standard oxygen-plasma treatment and atomic force microscopy (AFM), we performed a scaling analysis of the modified surfaces yielding effective Hurst exponents (H ≃ 0.77 ± 0.02 (PP), ≃0.75 ± 0.02 (PTFE), and ≃0.83 ± 0.02 (PCL)), for the one-dimensional profiles, corresponding to the transversal sections of the surface, by averaging over all possible profiles. The surface fractal dimensions are given by ds = 3 − H, corresponding to ds ≃ 2.23, 2.25, and 2.17, respectively. We present a simple method to obtain the surface area from the AFM images stored in a matrix of 512 × 512 pixels. We show that the considerable increase found in the surface areas of the treated samples w.r.t. to the non-treated ones (43% for PP, 85% for PTFE, and 25% for PCL, with errors of about 2.5% on samples of 2 µm × 2 µm) is consistent with the observed increase in the length scales of the fractal regime to determine H, typically by a factor of about 2, extending from a few to hundreds of nanometres. We stipulate that the intrinsic roughness already present in the original non-treated material surfaces may serve as ‘fractal’ seeds undergoing significant height fluctuations during plasma treatment, suggesting a pathway for the future development of advanced material interfaces with large surface areas at the nanoscale.

Graphical abstract: The fractal geometry of polymeric materials surfaces: surface area and fractal length scales

Supplementary files

Article information

Article type
Paper
Submitted
06 Nov 2023
Accepted
20 Jan 2024
First published
23 Jan 2024
This article is Open Access
Creative Commons BY license

Soft Matter, 2024,20, 3082-3096

The fractal geometry of polymeric materials surfaces: surface area and fractal length scales

H. E. Roman, F. Cesura, R. Maryam, I. Levchenko, K. Alexander and C. Riccardi, Soft Matter, 2024, 20, 3082 DOI: 10.1039/D3SM01497E

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