Quantitative EPMA (electron probe microanalysis) intensity measurements require an accurate correction for the X-ray continuum (or background) created by the Bremsstrahlung effect from the primary electron beam. This X-ray continuum, as measured on a wavelength-dispersive spectrometer at any particular wavelength, is primarily a function of the mean atomic number of the material being analyzed. One can calibrate the dependence of the continuum on mean atomic number by measuring and curve fitting the X-ray intensities at the analytical peak in pure elements, oxides, and binary compound standards that do not contain any of the analyte or any interfering elements and use that calibration to calculate the X-ray background correction. For unknown samples, the mean atomic number is determined from the elemental concentrations calculated by the ZAF or φ(ρz) matrix correction, and the fit regression coefficients are used iteratively to calculate the actual background correction. Over a large range of mean atomic number we find that the dependence of the continuum intensity on mean atomic number is well described by a second-order polynomial fit. In the case of low-energy X-ray lines (<1 to 2 keV), this fit is significantly improved by correcting the X-ray continuum intensities for absorption. For major and most minor element analyses, the improved mean atomic number background correction procedure presented in this paper is accurate and robust for a wide variety of samples. Empirical mean atomic number background data are presented for a typical 10-element silicate and a 15-element sulfide analytical set up that demonstrate the validity of the technique as well as some potential limitations.

The use of a thin annular detector in a scanning transmission electron microscope is shown, theoretically and experimentally, to allow several imaging modes that may be of value for the study of thin specimens. The diffraction pattern on the detector plane may be expanded or contracted by means of post-specimen lenses to vary the collection angle of the thin annular detector to form dark- or bright-field images. Dark-field images obtained from annuli of various radii in the diffraction pattern can selectively reveal different components of the sample, as illustrated in the case of a sample containing platinum crystallites, amorphous carbon, and carbon nanotubes. Amorphous materials of different composition can be distinguished by selecting the main maxima in their diffraction patterns. If the central beam is enlarged so that it just fills the inner aperture of the detector, the “marginal” imaging mode so achieved gives an image contrast that is proportional to the square of the differential of the projected potential distribution. Any deflection of the incident beam spot due to a change of the projected potential gives bright contrast in the image.

We examine the problem of building quantitative elemental maps from X-ray absorption images (radiography). As we suggested in a previous publication in Microbeam Analysis, factorial analysis of correspondence is shown to be an optimal method, in the least squares sense, for solving the multilinear equation system given by Beer's law: it relates to an efficient description of the problem in the concentration phase space. We explain how factorial analysis is related to singular value decomposition and we give a complete description of the algorithm. The method can be applied to any multilinear analytical technique as well. Programs are written in C and Mathematica® languages. Academic users may obtain the relevant software (source and code) as freeware directly from the authors.

Depth profiling has been performed by using Auger electron spectrometry and X-ray photoelectron spectrometry in combination with Ar-ion sputtering. The data obtained by both surface-analytical methods have been evaluated by means of factor analysis and partly by applying artificial neural network in order to determine the compositional layering of different thin-films such as TiNx on Ti, Cr2O3/CrN sandwich layer, and copper oxide on Cu. Both multivariate statistical methods applied to the same data sets lead to results that agree well within statistical deviations provided that the structure of the artificial neural network is constructed appropriate to the actual problem.

Several examples are presented that show the successful application of uranyl acetate and ammonium molybdate negative staining in the presence of trehalose for TEM studies of filamentous and tubular structures. The principal benefit to be gained from the inclusion of trehalose stems from the considerably reduced flattening of the large tubular structures and the greater orientational freedom of single molecules due to an increased depth of the negative stain in the presence of trehalose. Trehalose is likely to provide considerable protection to protein molecules and their assemblies during the drying of negatively stained specimens. Some reduction in the excessive density imparted by uranyl acetate around large assemblies is also achieved. Nevertheless, in the presence of 1% (w/v) trehalose, it is desirable to increase the concentration of negative stain to 5% (w/v) for ammonium molybdate and to 4% for uranyl acetate to produce satisfactory image contrast. In general, the ammonium molybdate-trehalose negative stain is more satisfactory than the uranyl acetate-trehalose combination, because of the greater electron beam sensitivity of the uranyl negative stain. Reassembled taxol-stabilized pig brain microtubules, together with collagen fibrils, sperm tails, helical filaments, and reassociated hemocyanin (KLH2), all from the giant keyhole limpet Megathura crenulata, have been studied by negative staining in the presence of trehalose. In all cases satisfactory TEM imaging conditions were readily obtained on the specimens, as long as regions of excessively deep stain were avoided.