Analytische Chemie
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The main objectives of the new EMPIR project nPSize are to establish EU capability of traceable measurement of NP size and shape, lower uncertainties of NP size measurement by developement of new nano-CRMs, new models (physical and machine learning), 3D method combination, and also by new ISO and CEN standards on accurate NP size measurement and guidance and knowledge transfer. The envisaged outcomes of the project will be presented and their suitability will be discussed to be taken over as pertinent contributions to normative projects within CEN/TC 352 Nanotechnologies.
Small-angle scattering data from particle dispersions with narrow size distributions are usually analysed by fitting a model function to the data, which is composed of a monodisperse form factor with a size distribution and, optionally, a structure factor. For common particle shapes like solid spheres, core-shell particles, ellipsoids or rods, the form factor can be computed analytically, and several software packages are readily available which provide a compilation of form factors.1,2 Recently, highly monodisperse nanoparticles with a variety of shapes have been synthesized, e.g. cubes and bipyramids3,4 with lightly capped edges, for which analytic form factors are harder to derive.
We compute an approximation to the scattering curve of arbitrary shapes by filling the shape with a quasi-random distribution of point scatterers and using Debye’s formula to get the overall scattering curve. The highly optimized debyer code is used to perform an efficient evaluation of Debye’s formula,5 which can perform the evaluation of 500,000 point scatterers in two minutes on commodity hardware. Moderate polydispersity is handled by interpolating the computed scattering curve over q from a master curve. In this way, the code is fast enough to perform data fitting of particle ensembles with moderate polydispersity for arbitrary shapes to experimental data.
This work was partly funded by the 17NRM04 nPSize project of the EMPIR programme co-financed by the EMPIR participating states and by the European Union’s Horizon 2020 research and innovation programme.