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A case study on the TEM analysis of the size and shape distribution of TiO2 bipyramidal nanoparticles prepared on TEM grids was included in the recently published ISO standard ISO 21363. It was agreed to organize at a later stage a second inter-lab comparison with the nanoparticles distributed to the participants as a liquid suspension. Protocols for uniform nanoparticle deposition on suited supports developed and optimized within the EMPIR nPSize project are also prepared to be distributed. For this, we have chosen the VAMAS platform (www.vamas.org) which offers an excellent international infrastructure of laboratories with high competence in nanoparticle measurement. The VAMAS technical working area dedicated to nanoparticle measurement is TWA 34 ‘Nanoparticle populations’. For this type of nanoparticles, the size and shape distributions are the primary parameters to be reported. Due to the good deposition protocols developed, an automated image analysis is enabled (in contrast to the manual analysis of irregular TiO2 nanoparticles.
In parallel with the TiO2 nanoparticle exercise, two spherical SiO2 nanoparticle samples with bi-modal size distributions (nominal relative number concentrations of 1:1 and 10:1) are prepared for a second VAMAS inter-lab comparison. Here, the nanoparticle concentration is the primary parameter to be measured. For the imaging methods it is targeted to measure the relative nanoparticle concentrations of the two modes. For the absolute nanoparticle concentration to be measured by imaging methods it is necessary to control the volume of the liquid suspension deposited on the substrate and to obtain such a homogeneous nanoparticle deposition on the substrate which allows to count (or extrapolate) all the deposited particles.
he main objective of the nPSize project is to improve the measurement capabilities for nanoparticle size based on both measurement methods traceable to SI units and new reference materials. Two basic approaches have been used in order to develop measurement procedures resulting in traceable results of the nanoparticle size distribution: physical modelling for the methods used in the project (TSEM, SEM, AFM and SAXS) and machine learning.
Physical modelling: In this part, the physical models associated with different shape measurements for the techniques TSEM, SEM, AFM and SAXS have been collected and further developed with the aim to simulate the resulting signal as measured by the individual methods. Uncertainties and traceability associated with each model were investigated and evaluated. In the following, the progress on these physical models is reported for each individual method.
Machine Learning modelling: The aim of this part is to use machine learning to enable automatic measurement of nanoparticle shape from expert a-priori information only. No physical model will be used as a-priori information in this task.
The accuracy and traceability of the size results obtained by each technique will be analyzed and compared with the physical modelling. A machine learning database will then be used to create automatic detection algorithms.
A Round Robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions, and two from powders.
Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5 % and half of the population width entries within 40 %, respectively. Due to the added complexity of the structure factor, much fewer people submitted answers on the powder datasets.
For those that did, half of the entries for the means and widths were within 44 % and 86 % respectively. This Round Robin experiment highlights several causes for the discrepancies, for which solutions are proposed.