Total reflection X-ray fluorescence analysis (TXRF) is an established technique for trace element analysis in various sample types. Restricted in the past to expensive large-scale systems, in this study the capability of a benchtop system for trace element analysis is reported. By analysing various heavy metals in raw and digested sewage as well as mercury in recycling glass, the suitability of the TXRF system for these kinds of applications could be proven. Based on this data, the benefits, disadvantages, and restrictions of the benchtop system in comparison to other trace element techniques like inductively coupled plasma optical emission spectroscopy (ICP-OES) and atomic adsorption spectroscopy (AAS) are evaluated.

The microstructure of materials is generally, macroscopically, anisotropic and/or inhomogeneous. Traditional diffraction analyses do not take into account this anisotropy and/or inhomogeneity of microstructural features. Thus obtained results can be incomplete, ambiguous, or even erroneous. In this work instrumental requirements (application of parallel beam diffractometers with X-ray lenses or X-ray mirrors and parallel-plate collimators in the laboratory and at synchrotron beam lines) and methodological approaches for the diffraction analysis of anisotropic and inhomogeneous microstructures have been discussed and have been illustrated on the basis of two experimental examples: analysis of the anisotropic nature of the structural imperfection of a sputterdeposited Ti3Al layer and analysis of the anisotropic and inhomogeneous elastic grain interaction in a sputter-deposited Ni layer.

The Monte Carlo—Library Least-Squares (MCLLS) approach has now been developed, implemented, and tested for solving the inverse problem of EDXRF sample analysis. It consists of a linear library least-squares code and a comprehensive Monte Carlo code named CEARXRF that is capable of calculating the unknown sample spectrum, all the elemental library spectra in the sample, and the differential operators for each library spectrum with respect to each element. Two codes with graphical user interface have been designed to implement the MCLLS approach and benchmark results are presented for the two stainless steel samples; SS304 and SS316. The results are accurate, the system is easy to use, and all indications are that this approach will be very useful for the EDXRF practitioner.

The analysis of the distribution of pharmaceutical materials in tablet formulations, such as drugs and matrix elements, is critical to product performance and is used in such areas as quality control, impurity testing, and process monitoring. Recently imaging techniques, such as Raman, near-IR, and fluorescence imaging, have become popular for “visualization” of pharmaceutical formulations, allowing for spatial and chemical composition information to be obtained simultaneously. These methods have been primarily focused on molecular imaging, or spatial analysis of the molecular characteristics of the tablet formulation. However, elemental species are also an important part of pharmaceuticals. Micro X-ray fluorescence (MXRF) elemental imaging offers complementary information to molecular imaging techniques. In this study, MXRF was used for the elemental imaging of various commercial pharmaceutical drug and vitamin supplements. Specifically, elemental composition and heterogeneity were monitored for each different tablet.

Cognitive deficits are repeatedly described with Pb exposure, but little is known about the distribution of lead in brain. To determine the local distribution of lead (Pb) and other trace elements, X-ray fluorescence spectroscopy measurements have been performed, using a microbeam setup and highest flux synchrotron radiation. Experiments have been carried out at ID-22, ESRF, Grenoble, France. The installed microprobe setup provides a monochromatic beam (16 keV) from an undulator station focused by Kirkpatrick-Baez X-ray optics to a spot size of 5 μm×3 μm. Brain slices from frontal cortex, thalamus, and hippocampus have been investigated (20 μm thickness, imbedded in paraffin and mounted on kapton foils). In general no significant increase in fluorescence intensities could be detected in one of the investigated brain compartments. Pb and other (trace) elements such as S, Ca, Fe, Cu, Zn, and Br could be detected in all samples and showed strong inhomogeneities within the analysed areas. While S, Ca, Fe, Cu, Zn, and Br could be clearly assigned to brain vessel structures (blood vessels, plexus choroidei), Pb was very inhomogeneously distributed. The local distribution of the detected elements in various brain structures will be discussed.

As complementary metal oxide semiconductor devices continue to scale along the rapid pace of Moore’s law, gate dielectric materials with significantly higher dielectric constant (k=10–25) are being evaluated as replacements for conventional silicon dioxide, SiO2 (k=3.9), and silicon oxynitride. This allows for the introduction of a physically thicker film with lower leakage current and with capacitance equivalent to a thinner (1.0 nm and below) SiO2 layer (Schlom and Haeni, 2002; Wilk et al., 2001; Kingon et al., 2001). Although binary metal oxide films such as HfO2 and ZrO2 exhibit higher permittivity than their corresponding silicates and aluminates, alloyed with various molecular percents of SiO2 or Al2O3, respectively, they are compromised by lower onset of crystallization temperature which contributes a higher degree of interfacial microroughness and increased gate leakage current due to dislocations and oxygen vacancies generated along grain boundaries. Accordingly, development of hafnium silicate has been the subject of intense investigation as an advanced gate dielectric thin film designed to meet the device manufacturing requirements of thermal stability in direct contact with substrate silicon and metal gate electrode materials. In this paper, we present results corresponding to the utilization of total reflection X-ray fluorescence spectroscopy (TXRF) as a quick, accurate, nondestructive technique for hafnium silicate composition determination based on detection of the Hf:Si ratio of (HfO2)x(SiO2)1−x, where x varies over the range 0.2–1.0.