Quantitative analysis of tribological performance in polyamide 6/nano-zeolite composites for prosthetic and orthotic applications: Integration of computer vision, numerical modeling, and experimental evaluation

R. Mohsenzadeh, Z. Jafari, B. H. Soudmand, F. Hazzazi, A. E. Anqi, A. H. Najafi, K. Shelesh-Nezhad, K. Heydary

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This study investigated the effect of nano-zeolite (NZ) integration on the tribological properties of polyamide 6 (PA6) nanocomposites using a hybrid approach combining image segmentation, experimental techniques, and numerical modeling. Automated SEM image analysis with U-Net segmentation quantified nanoparticle distribution, while pin-on-disc tests assessed wear performance. A support vector regression (SVR) model linked nanoparticle dispersion, load, and hardness to friction and wear rates. A combined dispersion index (CDI) further quantified nanoparticle distribution. Results demonstrated significant wear rate reductions (41 % at 60 N and 54 % at 100 N) with 5 wt% NZ. The SVR model highlighted the importance of nanoparticle dispersion and load on performance, with hardness having minimal influence. Morphological analysis confirmed smoother worn surfaces with NZ inclusion.

Original languageEnglish
Article number110455
JournalTribology International
Volume204
DOIs
StatePublished - Apr 2025

Keywords

  • Computer vision
  • Image segmentation
  • Polymer nanocomposite
  • Wear

Fingerprint

Dive into the research topics of 'Quantitative analysis of tribological performance in polyamide 6/nano-zeolite composites for prosthetic and orthotic applications: Integration of computer vision, numerical modeling, and experimental evaluation'. Together they form a unique fingerprint.

Cite this