Size Distribution of Industrial Nanoparticles

Size distributions of nanoparticles used for quality assessment or processs monitoring have been established in several forms.

At a growing rate, nanoparticles are being created and have become a crucial building block for the development of new materials with enhanced properties. The performance of the final products depends on their size, and on the ability to maintain a dispersed state throughout the processing stages, in addition to the chemical nature of the nanoparticles.1

Small Angle X-ray Scattering (SAXS) is a non-destructive method with minimal sample preparation which permits material structure determination in the range 1-250 nm. It supplies statistically relevant information over a large volume (generally 1 mm3). So, it is an ideal complement to microscopy methods that supply only local information.

While traditionally SAXS is employed for narrow size distributions on well-defined laboratory batches, this article outlines how SAXS, coupled with a unique data analysis algorithm, can be successfully applied to industrial batches of nanoparticles at numerous process steps.

Nanomakers is a manufacturer of nanosized particles and nanocomposites.2 SAXS is the only method permitting precise nanoscale size determination of dispersions, dry powders, and nanocomposites, supplying Nanomakers with nanostructural information throughout the whole production chain.

Measurements & Results

Particle size distributions obtained by SAXS on the SiC nanoparticles measured as a dry powder, as a dispersion or as a nanocomposite. The solid lines correspond to the cumulated volume fraction. The bin width for the histograms is 1.4 nm.

Figure 1. Particle size distributions obtained by SAXS on the SiC nanoparticles measured as a dry powder, as a dispersion or as a nanocomposite. The solid lines correspond to the cumulated volume fraction. The bin width for the histograms is 1.4 nm.

Using the Nano-inXider, a batch of SiC powder produced by Nanomakers (modal size 33.5 nm according to transmission electron microscopy) has been characterized in three different forms : as a dry powder, as a nanocomposite, and as a dispersion (using ISO Methodology3 for characterizing the dispersions). The experimental scattering profiles were fitted by utilizing the Expectation Maximization algorithm (EM)4,5 after data reduction, implemented in the Xenocs XSACT software to establish the size distribution of the nanoparticles.

Figure 1 shows the size distributions which were established from SAXS data. On all the samples, the modal size of the primary SiC nanoparticles has been properly detected with a size resolution of 1.4 nm. SAXS has shown the presence of residual agglomerates in the dispersion, while most of the SiC nanoparticles are well-dispersed.

Though the polymer matrix contributes with a sharp mode around 5 nm, on the size distribution of the nanocomposite the SiC mode around 35 nm can be seen. This establishes the good dispersion state of the nanoparticles in the polymer matrix. With minimal effort and time compared to other characterization methods, these data confirm the powder synthesis and processing steps utilized by Nanomakers.

Conclusion

SAXS associated with the EM algorithm can establish the size distributions of industrial-grade nanoparticles measured as dispersions, dry powders, or embedded in a matrix accurately. The short measurement times and minimal sample preparation are compatible with the requirements of routine assessment and process monitoring.

SAXS is a powerful and relevant method which is complementary to electron microscopy. The Xenocs XSACT software simplifies data analysis greatly and integrates state-of-the-art SAXS algorithms.

References

  1. S. Logothetidis, “Nanostructured Materials and Their Applications”, NanoScience and Technology, 2012.
  2. https://www.nanomakers.com
  3. Particle size analysis - Small-angle X-ray scattering. ISO 17867:2015, 2015.
  4. F. Benvenuto, H. Haddar, and B. Lantz, SIAM Journal on Applied Mathematics, 2016, 76 (1), pp.276-292.
  5. M. Bakry, H. Haddar, O. Bunau, J. Appl. Cryst. (2019). 52, 926-936

Xenocs

This information has been sourced, reviewed and adapted from materials provided by Xenocs.

For more information on this source, please visit Xenocs.

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