X-ray standing wave characterization of the strong metal-support interaction in Co/TiOx model catalysts

The strong metal-support interaction (SMSI) is a phenomenon observed in supported metal catalyst systems in which reducible metal oxide supports can form overlayers over the surface of active metal nanoparticles (NPs) under a hydrogen (H2) environment at elevated temperatures. SMSI has been shown to affect catalyst performance in many reactions by changing the type and number of active sites on the catalyst surface. Laboratory methods for the analysis of SMSI at the nanoparticle-ensemble level are lacking and mostly based on indirect evidence, such as gas chemisorption. Here, we demonstrate the possibility to detect and characterize SMSIs in Co/TiOx model catalysts using the laboratory X-ray standing wave (XSW) technique for a large ensemble of NPs at the bulk scale. We designed a thermally stable MoNx/SiNx periodic multilayer to retain XSW generation after reduction with H2 gas at 600°C. The model catalyst system was synthesized here by deposition of a thin TiOx layer on top of the periodic multilayer, followed by Co NP deposition via spare ablation. A partial encapsulation of Co NPs by TiOx was identified by analyzing the change in Ti atomic distribution. This novel methodological approach can be extended to observe surface restructuring of model catalysts in situ at high temperature (up to 1000°C) and pressure (≤3 mbar), and can also be relevant for fundamental studies in the thermal stability of membranes, as well as metallurgy.

Elemental analysis of hourly collected air filters with X-ray fluorescence under grazing incidence

The X-ray fluorescence under grazing incidence condition (XRF-UGI) was applied for the direct analysis of aerosol filters. Particulate matter less than 2.5 microns (PM2.5) was collected hourly on polytetrafluoroethylene filters using a continuous PM monitor with a virtual impactor method. Although the sampling mass is in trace amounts of 5-30 μg, the metallic contents, such as V, Cr, Mn, Fe, Zn, and Pb, can be measured at sub-ng m-3 detection limits. The effects of the non-uniformity and poor flatness of the PM filters were discussed with regard to the measurement repeatability. The relationship between the XRF-UGI intensities and the mass concentrations obtained via conventional X-ray fluorescence (XRF) analysis was confirmed using the fundamental parameter method. Finally, quantification was successfully demonstrated using the XRF-UGI results with the relative sensitivity factors.

Shape- and Element-Sensitive Reconstruction of Periodic Nanostructures with Grazing Incidence X-ray Fluorescence Analysis and Machine Learning

The characterization of nanostructured surfaces with sensitivity in the sub-nm range is of high importance for the development of current and next-generation integrated electronic circuits. Modern transistor architectures for, e.g., FinFETs are realized by lithographic fabrication of complex, well-ordered nanostructures. Recently, a novel characterization technique based on X-ray fluorescence measurements in grazing incidence geometry was proposed for such applications. This technique uses the X-ray standing wave field, arising from an interference between incident and the reflected radiation, as a nanoscale sensor for the dimensional and compositional parameters of the nanostructure. The element sensitivity of the X-ray fluorescence technique allows for a reconstruction of the spatial element distribution using a finite element method. Due to a high computational time, intelligent optimization methods employing machine learning algorithms are essential for timely provision of results. Here, a sampling of the probability distributions by Bayesian optimization is not only fast, but it also provides an initial estimate of the parameter uncertainties and sensitivities. The high sensitivity of the method requires a precise knowledge of the material parameters in the modeling of the dimensional shape provided that some physical properties of the material are known or determined beforehand. The unknown optical constants were extracted from an unstructured but otherwise identical layer system by means of soft X-ray reflectometry. The spatial distribution profiles of the different elements contained in the grating structure were compared to scanning electron and atomic force microscopy and the influence of carbon surface contamination on the modeling results were discussed. This novel approach enables the element sensitive and destruction-free characterization of nanostructures made of silicon nitride and silicon oxide with sub-nm resolution.

Combined evaluation of grazing incidence X-ray fluorescence and X-ray reflectivity data for improved profiling of ultra-shallow depth distributions

The continuous downscaling of the process size for semiconductor devices pushes the junction depths and consequentially the implantation depths to the top few nanometers of the Si substrate. This motivates the need for sensitive methods capable of analyzing dopant distribution, total dose and possible impurities. X-ray techniques utilizing the external reflection of X-rays are very surface sensitive, hence providing a non-destructive tool for process analysis and control. X-ray reflectometry (XRR) is an established technique for the characterization of single- and multi-layered thin film structures with layer thicknesses in the nanometer range. XRR spectra are acquired by varying the incident angle in the grazing incidence regime while measuring the specular reflected X-ray beam. The shape of the resulting angle-dependent curve is correlated to changes of the electron density in the sample, but does not provide direct information on the presence or distribution of chemical elements in the sample. Grazing Incidence XRF (GIXRF) measures the X-ray fluorescence induced by an X-ray beam incident under grazing angles. The resulting angle dependent intensity curves are correlated to the depth distribution and mass density of the elements in the sample. GIXRF provides information on contaminations, total implanted dose and to some extent on the depth of the dopant distribution, but is ambiguous with regard to the exact distribution function. Both techniques use similar measurement procedures and data evaluation strategies, i.e. optimization of a sample model by fitting measured and calculated angle curves. Moreover, the applied sample models can be derived from the same physical properties, like atomic scattering/form factors and elemental concentrations; a simultaneous analysis is therefore a straightforward approach. This combined analysis in turn reduces the uncertainties of the individual techniques, allowing a determination of dose and depth profile of the implanted elements with drastically increased confidence level. Silicon wafers implanted with Arsenic at different implantation energies were measured by XRR and GIXRF using a combined, simultaneous measurement and data evaluation procedure. The data were processed using a self-developed software package (JGIXA), designed for simultaneous fitting of GIXRF and XRR data. The results were compared with depth profiles obtained by Secondary Ion Mass Spectrometry (SIMS).

Characterization of High-k Nanolayers by Grazing Incidence X-ray Spectrometry

The accurate characterization of nanolayered systems is an essential topic for today's developments in many fields of material research. Thin high-k layers and gate stacks are technologically required for the design of current and future electronic devices and can be deposited, e.g., by Atomic Layer Deposition (ALD). However, the metrological challenges to characterize such systems demand further development of analytical techniques. Reference-free Grazing Incidence X-ray Fluorescence (GIXRF) based on synchrotron radiation can significantly contribute to the characterization of such nanolayered systems. GIXRF takes advantage of the incident angle dependence of XRF, in particular below the substrate's critical angle where changes in the X-ray Standing Wave field (XSW) intensity influence the angular intensity profile. The reliable modeling of the XSW in conjunction with the radiometrically calibrated instrumentation at the PTB allows for reference-free, fundamental parameter-based quantitative analysis. This approach is very well suited for the characterization of nanoscaled materials, especially when no reference samples with sufficient quality are available. The capabilities of this method are demonstrated by means of two systems for transistor gate stacks, i.e., Al₂O₃ high-k layers grown on Si or Si/SiO₂ and Sc₂O₃ layers on InGaAs/InP substrates.