Automated primary particle sizing of nanoparticle aggregates by TEM image analysis

Abstract

Nanoparticle aggregates formed in colloidal or aerosol processes have complex morphologies. Soot, for example, is formed as aggregates of primary particles. Soot properties are influenced by the diameter (dp) and the arrangement of its constitutive primary particles. Transmission Electron Microscopy (TEM) is commonly used for the characterization of agglomerates' morphology, but manual analysis of the micrographs is extremely labor-intensive. Here, a new method is developed for automatic determination of the average primary particles diameter based on the variation of the 2-D pair correlation function P(r) at different distances r measured from the main skeleton of the aggregates. It is assumed that P⁎=P(dp/2) is nearly constant. The method has been applied to numerical agglomerates and real soot aggregates collected from several operating conditions of a gasoline direct injection engine and a heavy-duty compression-ignition engine. Using a constant value of P⁎ determined from the analysis of TEM images results in primary particle sizing errors (relative to manual sizing) of ~13% for single aggregates. The ensemble-mean values of dp for manual and automatic sizing differed by ~4%.