Single particle analytical characterization

For the analytical characterization of single particles, deposition of the particle on very flat surfaces is necessary (e.g., Nucleopore filters or organic foils) (McCrone and Delly 1973 Grasserbauer 1978a Spumy etal. 1979 Chatfield 1984). 

Up-to-date analytical techniques used in nuclear forensics for safeguards in support of non-proliferation, including single particle characterization... 

Jn the preceding chapters we discussed the experimental and analytical techniques available for the characterization of reaction systems involving single particles. On the basis of this material we can relate the rate of reaction of a single particle to the structural parameters, the kinetic parameters, and the factors that determine gas-solid heat and mass transfer. 

As the analytical, synthetic, and physical characterization techniques of the chemical sciences have advanced, the scale of material control moves to smaller sizes. Nanoscience is the examination of objects—particles, liquid droplets, crystals, fibers—with sizes that are larger than molecules but smaller than structures commonly prepared by photolithographic microfabrication. The definition of nanomaterials is neither sharp nor easy, nor need it be. Single molecules can be considered components of nanosystems (and are considered as such in fields such as molecular electronics and molecular motors). So can objects that have dimensions of >100 nm, even though such objects can be fabricated—albeit with substantial technical difficulty—by photolithography. We will define (somewhat arbitrarily) nanoscience as the study of the preparation, characterization, and use of substances having dimensions in the range of 1 to 100 nm. Many types of chemical systems, such as self-assembled monolayers (with only one dimension small) or carbon nanotubes (buckytubes) (with two dimensions small), are considered nanosystems. 

The principal limitations of ESCA include the inability to detect elements present at trace concentrations within the analytical volume, and insufficient lateral resolution to characterize single micrometer-sized particles. The inability to characterize trace species is illustrated in Figure 10 for a sample of coal fly ash particles (11). The fly ash results from the noncombustible mineral components of the coal and consists largely of fused iron oxides and aluminosilicates (42). In addition, most elements are present in at least trace concentrations (22, 42), and many of these elements are highly enriched in the surface region of the particles (evidence for this will be discussed in the next section). However, the ESCA spectrum acquired over several hours of counting time indicates only the presence of detectable surface S and Ca in addition to the fly ash matrix constituents. 

The next reasonable step in studying our chemical games is to consider ensembles of A s and B s (e.g., topers and policemen), when they are randomly and homogeneously distributed in the reaction volume and are characterized by macroscopic densities of a number of particles. The peculiarity of the A + B -y B reaction is that the solution of a problem with a single A could be extrapolated for an ensemble of A s (in other words, a problem is linear in particles A). As it was said above, it is analytically solvable for Da = 0 but turns out to be essentially many-particle for Db = 0. It is useful to analyze a form of the solution obtained for the particle concentration tia (t) in terms of the basic postulates of standard chemical kinetics (i.e., the mean-field theory). 

S-FFF has been compared with analytical ultracentrifugation (AUC) with respect to the fractionation of a 10-component latex standard mixture with narrow particle size distribution, known diameters (67-1220 nm) and concentration [ 127]. With an analytical ultracentrifuge, the particle sizes as well as their quantities could be accurately determined in a single experiment whereas in S-FFF deviations from the ideal retention behavior were found for particles >500 nm resulting in smaller particle size determination in the normal as well as in the programmed operation. It was concluded that, without a modified retention equation which accounts for hydrodynamic lift forces and steric exclusion effects, S-FFF cannot successfully be used for the size characterization of samples in that size range. 

In a previous paper (Anderson and Benjamin accepted for publication in Environmental Science and Technology), surface and bulk characteristics of amorphous oxides of silica, aluminum, and iron, both singly and in binary mixtures were described. The solids were characterized with an array of complementary analytical and experimental techniques, including scanning electron microscopy, particle size distribution, x-ray photoelectron spectroscopy (XPS),... 

When an analytical solution is not available for r, there is no gain in the use of t from the reactor design and computational viewpoint. The only advantage of r then is its possibility of characterizing the situation inside the particle by means of a single number. For reactions with an order different from 1 but isothermal... 

The three main analytical methods used for characterization of the isotopic composition of single uranium-containing particles—LA-ICPMS, FT-TIMS, and SIMS—were compared (Pointurier et al. 2013). The variability of the measurements of several particles from the Nusimep-7 intercomparison exercise by each method and the error bars for each individual particle measurement were presented. The results obtained by LA-ICP-QMS were inferior to the other two methods, but it was noted that the signal intensity obtained in the LA-ICPMS measurements with a quadrupole-based mass spectrometer was lower by a factor of 10-20 than the SIMS and FT-TIMS, which accounted for the relative uncertainties. In an earlier work by the same group, the isotopic composition of UOjFj particles from the Nusimep-6 intercomparison exercise was analyzed by the three methods. The time needed for analysis of two samples, each with 30 uranium particles, was estimated for SIMS, SEM-LA-ICPMS, ET-TIMS, and FT-LA-ICPMS to be 4, 3.5, 21, and 13 days, respectively (Pointurier et al. 2011), in partial agreement with the estimates given above (Esaka et al. 2009). 

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