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A reproducible number-based sizing method for pigment-grade titanium dioxide.

Ralf Theissmann1, Manfred Kluwig1, Thomas Koch1

  • 1Research Services / Analytical Intelligence, KRONOS INTERNATIONAL, Inc., Peschstrasse 5, 51373 Leverkusen, Germany.

Beilstein Journal of Nanotechnology
|November 11, 2014
PubMed
Summary
This summary is machine-generated.

This study presents a new method for accurately measuring the size distribution of irregular industrial particles like titanium dioxide. This reliable technique aids in classifying materials for upcoming nanomaterial regulations.

Keywords:
electron microscopyparticle sizepigmentsizingtitanium dioxide

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Analytical Chemistry

Background:

  • Growing demand for nanomaterial characterization methods driven by new regulations.
  • Existing methods struggle with irregular, agglomerated industrial particles.
  • Need for practical, standardized number-based sizing techniques.

Purpose of the Study:

  • To develop and validate a robust method for number-based sizing of industrial particulate materials.
  • To address limitations of current characterization techniques for complex samples.
  • To enable reliable classification of materials under new regulatory frameworks.

Main Methods:

  • Sample preparation involving embedding particles in a polished section.
  • Automated image analysis of the prepared samples.
  • Application of a sophisticated counting algorithm for size distribution determination.

Main Results:

  • Demonstrated overcoming of typical sizing difficulties like irregular shapes and agglomeration.
  • Achieved robust, reproducible, and statistically reliable number-based size distribution.
  • Successfully applied the method to pigment-grade titanium dioxide.

Conclusions:

  • The presented method offers a practical solution for characterizing industrial particulate materials.
  • This approach supports regulatory compliance for nanomaterial classification.
  • The technique provides reliable number-based size distributions for complex materials.