Classifying the Shape
of Colloidal Nanocrystals by
Complex Fourier Descriptor Analysis
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Abstract
The optical, electrical, magnetic, and catalytic properties
of
colloidal nanocrystals are intimately tied to their form, in particular
their physical size and shape. Synthetic techniques have been developed
to produce metallic and semiconducting nanomaterials with well-controlled
forms; however, characterization tools for describing shape have remained
limited to small samples and lack the quantitative rigor necessary
for a universal classification scheme. Here complex Fourier descriptors
are shown to be a quantitative and high-throughput approach for classifying
the shape of colloidal nanocrystals. Large, monodisperse, and polydisperse
ensembles of CdSe nanocrystals are characterized with respect to shape
and categorized as circles, triangles, squares, rods, and pentagonal
or hexagonal platelets. These results suggest that classification
of shape by Fourier descriptor analysis may in the near future be
a powerful tool for continuous monitoring of synthesis, purification,
or packaging/integration processes during industrial-scale production
of nanomaterials
