Filtern
Dokumenttyp
Sprache
- Englisch (5) (entfernen)
Schlagworte
- Electron microscopy (5) (entfernen)
Organisationseinheit der BAM
The authors have tested the prototype of an electrospray deposition system developed by the company RAMEM under its trademark IONER. To test the prototype and assess its performance, several materials have been sprayed onto TEM grids and the resulting particle distributions were compared to more traditional sample preparation strategies like the “drop on grid” method. Operation parameters such as the sample flow-rate, capillary – substrate distance, electric field strength and sampling period length have been optimized. It was found that the particles deposited by electrospray generally show a much more homogeneous spatial distribution on the substrate and a substantial increase of the number of single particles, which are much better suited to an automatic image evaluation procedure than the agglomerated particles observed otherwise. The applicability of the technique to a broad range of materials is demonstrated by various examples, but also the influence of the substrate, the choice of the particular TEM grid, on the obtained spatial particle distribution is assessed.
Evaluation of electron microscopy techniques for the purpose of classification of nanomaterials
(2016)
One current and much-debated topic in the characterization of nanomaterials (NM) is the implementation of the recently introduced recommendation on a definition of a nanomaterial by the European Commission.
All currently available sizing techniques able to address nanoparticles were systematically evaluated. It was demonstrated that particle sizing techniques like: analytical centrifugation, particle tracking analysis, single-particle inductively coupled plasma mass-spectrometry, differential electrical mobility analysis, dynamic light scattering, small angle X-ray scattering, ultrasonic attenuation spectrometry, but also gas Adsorption analysis based on the BET-method can be applied for a screening classification. However, the quality of the results depends on the individual material to be classified. For well-dispersed, nearly spherical (nano)particles most of the sizing techniques can be applied in a quick and reliable way. In contrast, the classification of most real-world materials is a challenging task, mainly due to non-spherical particle shape, large polydispersity or strong agglomeration/ aggregation of the particles. In the present study it was shown that these issues can be resolved in most cases by electron microscopy as a confirmatory classification technique.
Electron microscopy techniques such as TEM, STEM, SEM or TSEM transmission in SEM) are capable of assessing the size of individual nanoparticles accurately (see Figures 1 and 2). Nevertheless the challenging aspect is sample preparation from powder or liquid form on the substrate, so that a homogeneous distribution of well-separated (deagglomerated) particles is attained. The systematic study in this work shows examples where the extraction of the critical, smallest particle dimension - as the decisive particle parameter for the classification as a NM - is possible by analysing the sample after its simple, dry preparation. The consequences of additional typical issues like loss of information due to Screening of smaller particles by larger ones or the (in)ability to access the constituent particles in aggregates are discussed.
Evaluation of electron microscopy techniques for the purpose of classification of nanomaterials
(2016)
Electron microscopy techniques such as TEM, STEM, SEM or TSEM (transmission in SEM) are capable of assessing the size of individual nanoparticles accurately. Nevertheless, the challenging aspect is sample preparation from powder or liquid form on the substrate, so that a
homogeneous distribution of well-separated (deagglomerated) particles is attained. The systematic study in this work shows examples where the extraction of the critical, smallest particle dimension - as the decisive particle parameter for the classification as a NM - is possible by analysing the sample after ist simple, dry preparation. The consequences of additional typical issues like loss of information due to screening of smaller particles by larger ones or the (in)ability to access the constituent particles in aggregates are discussed.
In this paper one refined approach is applied to determine the exact orientation of bipyramidal TiO2 nanoparticles prepared with good dispersion as almost isolated particles on a carbon TEM grid. The advantages of the recently developed high-throughput Transmission Kikuchi Diffraction (TKD) are used to identify quickly and reliably the geometrical orientation of the crystalline TiO2 nanoparticle bipyramids (anatase) on a statistically relevant number of particles.
Core-shell (CS) particles with a polymeric core and a silica shell play an important role in the materials and (bio)analytical sciences. Besides the establishment of reliable synthesis procedures, comprehensive particle characterization is essential for batch-to-batch reproducibility and objective performance assessment across architectures, protocols, and laboratories. Particle characterization with respect to size, size distribution, shell thickness and texture, surface area and roughness or materials composition is commonly conducted with different analytical methods, often on different samples. Our approach uses a dual-mode TSEM/SEM set-up with an EDX detector to obtain a complementary data set with sufficient statistical confidence of one and the same sample on a single instrument. Our protocol reveals information about size, size distribution and shell thickness of the various particles employed from overview images, while an increased field of view (FOV) and high-resolution EDX analysis yields detailed information on shell texture and elemental composition. An image analysis tool was developed to derive and quantify the profile roughness of CS particles from individual beads. Comparison with surface roughness data from AFM showed a similar trend in roughness across the series of particles. Reliable classification into smooth and rough is proposed and roughness changes within different particle batches were tracked systematically.