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Organisationseinheit der BAM
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.
Effect of fluorescent staining on size measurements of polymeric nanoparticles using DLS and SAXS
(2015)
The influence of fluorescence on nanoparticle size measurements using dynamic light scattering (DLS) and small angle X-ray scattering (SAXS) was investigated. For this purpose, two series of 100 nm-sized polymer nanoparticles stained with different concentrations of the fluorescent dyes DY555 and DY680 were prepared, absorbing/emitting at around 560 nm/590 nm and 695 nm/715 nm, respectively. SAXS measurements of these particle series and a corresponding blank control (without dye) revealed similar sizes of all particles within an uncertainty of 1 nm. DLS measurements carried out at three different laboratories using four different DLS instruments and two different laser wavelengths, i.e., 532 nm and 633 nm, revealed also no significant changes in size (intensity-weighted harmonic mean diameter, ZAverage) and size distribution (polydispersity index, PI) within and between the two dye-stained particle series and the blank sample. Nevertheless, a significant decrease of the detected correlation coefficients was observed with increasing dye concentration, due to the increased absorption of the incident light and thus, less coherent light scattering. This effect was wavelength dependent, i.e. only measurable for the dye-stained particles that absorb at the laser wavelength used for the DLS measurements.
In this paper, the accurate determination of the size and size distribution of bipyramidal anatase nanoparticles (NPs) after deposition as single particles on a silicon substrate by correlative Scanning Electron Microscopy (SEM) with Atomic Force Microscopy (AFM) analysis is described as a new measurement procedure for metrological purposes. The knowledge of the exact orientation of the NPs is a crucial step in extracting the real 3D dimensions of the particles. Two approaches are proposed to determine the geometrical orientation of individual nano‐bipyramides: (i) AFM profiling along the long bipyramid axis and (ii) stage tilting followed by SEM imaging. Furthermore, a recently developed method, Transmission Kikuchi Diffraction (TKD), which needs preparation of the crystalline NPs on electron‐transparent substrates such as TEM grids, has been tested with respect to its capability of identifying the geometrical orientation of the individual NPs. With the NPs prepared homogeneously on a TEM grid, the transmission mode in a SEM, i.e., STEM‐in‐SEM (or T‐SEM), can be also applied to extract accurate projection dimensions of the nanoparticles from the same sample area as that analysed by SEM, TKD and possibly AFM. Finally, Small Angle X‐ray Scattering (SAXS) can be used as an ensemble technique able to measure the NPs in liquid suspension and, with ab‐initio knowledge of the NP shape from the descriptive imaging techniques, to provide traceable NP size distribution and particle concentration.
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
This paper describes the production and characteristics of the nanoparticle test materials prepared for common use in the collaborative research project NanoChOp (Chemical and optical characterization of nanomaterials in biological systems), in casu suspensions of silica nanoparticles and CdSe/CdS/ZnS quantum dots (QDs). This paper is the first to illustrate how to assess whether nanoparticle test materials meet the requirements of a "reference material" (ISO Guide 30, 2015) or rather those of the recently defined category of "representative test material (RTM)" (ISO/TS 16195, 2013). The NanoChOp test materials were investigated with small-angle X-ray scattering (SAXS), dynamic light scattering (DLS), and centrifugal liquid sedimentation (CLS) to establish whether they complied with the required monomodal particle size distribution. The presence of impurities, aggregates, agglomerates, and viable microorganisms in the suspensions was investigated with DLS, CLS, optical and electron microscopy and via plating on nutrient agar. Suitability of surface functionalization was investigated with attenuated total reflection Fourier transform infrared spectrometry (ATR-FTIR) and via the capacity of the nanoparticles to be fluorescently labeled or to bind antibodies. Between-unit homogeneity and stability were investigated in terms of particle size and zeta potential. This paper shows that only based on the outcome of a detailed characterization process one can raise the status of a test material to RTM or reference material, and how this status depends on its intended use.
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.
Digital Volume Correlation (DVC) is a powerful set of techniques used to compute the local shifts of 3D images obtained, for instance, in tomographic experiments. It is utilized to analyze the geometric changes of the investigated object as well as to correct the corresponding image misalignments for further analysis. It can therefore be used to evaluate the local density changes of the same regions of the inspected specimens, which might be shifted between measurements. In recent years, various approaches and corresponding pieces of software were introduced. Accuracies for the computed shift vectors of up to about 1‰of a single voxel size have been reported. These results, however, were based either on synthetic datasets or on an unrealistic setup. In this work, we propose two simple methods to evaluate the accuracy of DVC-techniques using more realistic input data and apply them to several DVC programs. We test these methods on three materials (tuff, sandstone, and concrete) that show different contrast and structural features.
The study described in this paper was conducted in the framework of the European nPSize project (EMPIR program) with the main objective of proposing new reference certified nanomaterials for the market in order to improve the reliability and traceability of nanoparticle size measurements. For this purpose, bimodal populations as well as complexly shaped nanoparticles (bipyramids, cubes, and rods) were synthesized. An inter-laboratory comparison was organized for comparing the size measurements of the selected nanoparticle samples performed with electron microscopy (TEM, SEM, and TSEM), scanning probe microscopy (AFM), or small-angle X-ray scattering (SAXS). The results demonstrate good consistency of the measured size by the different techniques in cases where special care was taken for sample preparation, instrument calibration, and the clear definition of the measurand. For each characterization method, the calibration process is described and a semi-quantitative table grouping the main error sources is proposed for estimating the uncertainties associated with the measurements. Regarding microscopy-based techniques applied to complexly shaped nanoparticles, data dispersion can be observed when the size measurements are affected by the orientation of the nanoparticles on the substrate. For the most complex materials, hybrid approaches combining several complementary techniques were tested, with the outcome being that the reliability of the size results was improved.