While nano-scaled intermediate and consumer products are omnipresent in many industries, a huge challenge consists in the development of methods that reliably identify, characterize and quantify nanomaterials both as a substance and in various matrices. For product registration purposes, the European Commission proposed a definition of nanomaterial [1] which requires a quantitative size determination of the primary particles of a sample down to sizes of 1 nm. According to [1] a material is defined as nano if 50% of the primary particles are observed to comprise a smallest dimension <100 nm.  The NanoDefine project [5] was set up to develop and validate a robust, readily implementable and cost-effective measurement approach to obtain a quantitative particle size distribution and to distinguish between nano and non-nano materials according to the definition [1].

In the present study the mean particle size derived from Brunauer, Emmet, Teller (BET) surface measurement by gas adsorption is systematically compared with the particle size derived from TEM images by manual and automated image evaluation. A correlation between mean particle diameters of 10 different organic pigments is given in figure 1. Automated and manual image evaluation lead to consistent results for the D50 particle size (red and blue bars). Automated TEM image evaluation was accomplished by a software package developed within the NanoDefine project which will soon be available as public ImageJ-Plugin [2,3]. Samples were carefully selected to represent typical organic pigment particles of different grinding degrees. Figure 2 shows TEM images of such a series of pigment grades. The red ellipses mark the result of the automated particle detection using direct ellipse fitting. The length of the minor axis of each ellipsis was taken as approximation for the particles minimum feret diameter.

In the present study a tiered approach for particle classification is proposed. BET measurements can be used for a coarse classification of the material including a categorization into nano/non-nano [4]. The presented data help to define the thresholds for this surface-based classification. Automated evaluation of TEM images improves this classification with reliable results for the number-based particle distribution within some remaining constraints. The according limitations are elaborated in the present study by comparison with the D50 size values determined by manually evaluation of TEM images.

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EMC Abstracts - https://emc-proceedings.com/abstract/cost-effective-implementation-of-nanoparticle-size-measurement-for-regulation-purposes/