Nanomaterial identification of powders: comparing volume specific surface area, X-ray diffraction and scanning electron microscopy methods
Nanomaterials in powder forms are widely produced and used in numerous applications. Nanomaterial identification is a growing concern for several areas encountering these substances. The current reference criterion of the European Commission (EC) for nanoparticle identification is the number size distribution of the constituent particles. One example of how the latter can be obtained is by the electron microscopy (EM) method. However, this method is not widely available and is time-consuming to perform and use for analysis. Alternative methods, such as the volume specific surface area (VSSA), also allow nanomaterial identification. The VSSA is the product of the external specific surface area of the powder and its skeletal density, and appears to be adapted more specifically for powders. The techniques required to measure the two parameters used to calculate the VSSA are more widely available than EM, but sample preparation can be delicate. Furthermore, deeper evaluation of the reliability of VSSA for nanomaterial classification as well as a more detailed characterization methodology for its implementation and discussion about the relative merits of this method versus EM are still necessary. Here, we determined, through a detailed and operational characterization strategy, the VSSA for seven metal oxide powders (4 TiO2, 1 SiO2, and 2 CaCO3) and an activated carbon, with all of them produced on an industrial scale. These eight samples covered a range of constituent particle sizes between 10 nm and 18 μm. Equivalent particle sizes determined by the VSSA, X-ray diffraction (XRD) (another method giving access to an equivalent particle size and integrated into our characterization methodology) and scanning electron microscopy (SEM) (reference method) were compared. The results showed that the VSSA can robustly identify nanomaterials in the form of powders (−12% mean bias on equivalent particle sizes relative to SEM).