Narrowing particle size distributions to enhance powder coating performance by improved classifying

Xinping Zhu, Wei Liu, Haiping Zhang, Hui Zhang, Jesse Zhu

Research output: Journal PublicationArticlepeer-review


Powder coating is a widely utilized and environmentally friendly coating method. It is well known that the particle size distribution (PSD) of a powder coating significantly impacts its properties and film performance. However, current powder coatings generally have wide PSDs, primarily due to the suboptimal classifying function of the grinding system—air classifying mill (ACM). In this study, self-designed ACM classifiers were built and tested to improve the classifying function and attain narrow-PSD powder coatings. These self-designed classifiers contributed to powder coatings with narrower PSDs (span≤1.4), which have significantly decreased D90 and increased D10 compared to the ones prepared by the control classifier (span>1.6). Furthermore, these narrowed-PSD powder coatings demonstrated improved flowability, and the coating films displayed superior gloss and smoothness. Overall, this facile and straightforward modification to the ACM classifier has effectively enhanced the classifying function of ACM, contributing to a narrowed PSD and improved quality of powder coatings.

Original languageEnglish
Article number119443
JournalPowder Technology
Publication statusPublished - 15 Feb 2024
Externally publishedYes


  • Air classifying mill
  • Flowability
  • Particle size distribution
  • Powder classifier

ASJC Scopus subject areas

  • General Chemical Engineering


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