Alloys SIMS analysis

Metals and alloys are in principle good materials for SIMS analysis. They are highly electric conductive materials and can easily be handled so as to obtain clean, flat, and smooth analyzable surfaces, and they are also usually ultrahigh-vacuum-friendly. However, archaeological and/or artistic metal objects do not always possess all of these properties due to degradation processes, which may chemically modify the external surface and deep regions of the samples. Nonconductive patinas and infiltrated compounds may often form as a result of long burial in soil or exposure to the atmosphere, and these have very different characteristics compared with those observed for metal materials. 

SIMS analysis as carried out in our previous work [12,39] provides a qualitative analysis of Cr enrichment of the surface. Based on such qualitative analysis of Cr content, a Cr203 oxide layer was proposed to develop in nanocrystalline alloy, whereas, it was proposed that a mixed Fe-Cr oxide layer forms in case of microcrystalline alloy. A Future study quantifying the Cr, Fe and O contents of oxide layer and their oxidation states using techniques such as X-ray photoelectron spectroscopy (XPS) must provide a better understanding of the effect of nanocrystalline structure on the chemical composition of oxide layer. 

X-ray scattering studies at a renewed pc-Ag/electrolyte interface366,823 provide evidence for assuming that fast relaxation and diffu-sional processes are probable at a renewed Sn + Pb alloy surface. Investigations by secondary-ion mass spectroscopy (SIMS) of the Pb concentration profile in a thin Sn + Pb alloy surface layer show that the concentration penetration depth in the solid phase is on the order of 0.2 pm, which leads to an estimate of a surface diffusion coefficient for Pb atoms in the Sn + Pb alloy surface layer on the order of 10"13 to lCT12 cm2 s i 820 ( p,emicai analysis by electron spectroscopy for chemical analysis (ESCA) and Auger ofjust-renewed Sn + Pb alloy surfaces in a vacuum confirms that enrichment with Pb of the surface layer is probable.810... 

The technique is referred to by several acronyms including LAMMA (Laser Microprobe Mass Analysis), LIMA (Laser Ionisation Mass Analysis), and LIMS (Laser Ionisation Mass Spectrometry). It provides a sensitive elemental and/or molecular detection capability which can be used for materials such as semiconductor devices, integrated optical components, alloys, ceramic composites as well as biological materials. The unique microanalytical capabilities that the technique provides in comparison with SIMS, AES and EPMA are that it provides a rapid, sensitive, elemental survey microanalysis, that it is able to analyse electrically insulating materials and that it has the potential for providing molecular or chemical bonding information from the analytical volume. 

The application of SIMS, SNMS, SSMS and GDMS in quantitative trace analysis for conducting bulk material is restricted to matrices where standard reference materials (SRMs) are available. For quantification purposes, the well characterized multi-element SRMs (e.g., from NIST) are useful. In Table 9.5 the results of the analysis by SNMS and the RSCs (relative sensitivity coefficients) for different elements in a low alloy steel standard (NBS 467) are compared with those of SSMS. Both solid-state mass spectrometric techniques with high vacuum ion sources allow the determination of light non-metals such as C, N, and P in steel, and the RSCs for the elements measured vary from 0.5 to 3 (except C). RSCs are applied as a correction factor in the analytical method used to obtain... 

Ion beams provide useful information either as a diagnostic tool or as a precision etching method in. adhesive bonding research. The combination of SIMS with complementary methods such as ISS or AF.S provides a powerful tool for elemental end limited structural characterization of metals, alloys and adhesives. The results shown here indicate that surface chemistry (and interface chemistry) can be decidedly different from bulk chemistry. Often it is this chemistry which governs the quality and durability of an adhesive bond. These same surface techniques also allow an analysis of the locus of failure of bonded materials which fail in service or test. 

The analytical signal obtained in SIMS depends on a number of factors, namely, the abundance of the isotope examined on the surface, the properties of the surface, and the bombarding ion. The relationship is complex calibration curves may or may not be continuous. Certihed calibration standards that are matrix-matched and cover the analytical range are required. For bulk analysis using dynamic SIMS, certified standards can be obtained from sources such as NIST or commercial standards firms for many metals and alloys and for some ceramics and glasses, but such standards are rarely available for surfaces, thin layers, and multilayered materials. The excellent sensitivity of SIMS allows it to distinguish between ppb and ppm concentrations of analyte in solids. SIMS is not used for quantitative analysis at the % level XPS or methods such as XRF are better suited to this purpose. 

SNMS is particularly suitable for the analysis of alloys in which a wide range of concentrations must be measured. Semiconductors can also be analyzed, because the detection limits of SNMS are of the. same order of magnitude as in SIMS. Finally, as the depth re.solution is better in SNMS than in SIMS or AES, SNMS is particularly suitable for the. study of interfaces [136]. 

Where experiments are conducted which simulate process conditions, the effectiveness of electrochemical testing is more controversial. Postreaction EIS studies of alloys exposed to autoclave corrosion were not able to illuminate differences in the performance of the alloys. By contrast, imaging SIMS provided u.seful insight into the structural and compositional differences, leading to a characterization that might possibly be used to qualify other alloy specimens. Alternatively, one could consider the surface techniques to be at their best when performing a postfailure analysis. 

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