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Towards nanometric resolution in multilayer depth profiling: a comparative study of RBS, SIMS, XPS and GDOES

期刊

ANALYTICAL AND BIOANALYTICAL CHEMISTRY
卷 396, 期 8, 页码 2725-2740

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00216-009-3339-y

关键词

Depth profiling; XPS; SIMS; GDOES; RBS; Multilayer; High resolution

资金

  1. Spanish Ministry of Science and Innovation [MAT2008-06618-C02-01, FUNCOAT CSD2008-00023, RyC2007-0026]

向作者/读者索取更多资源

An increasing amount of effort is currently being directed towards the development of new functionalized nanostructured materials (i.e., multilayers and nanocomposites). Using an appropriate combination of composition and microstructure, it is possible to optimize and tailor the final properties of the material to its final application. The analytical characterization of these new complex nanostructures requires high-resolution analytical techniques that are able to provide information about surface and depth composition at the nanometric level. In this work, we comparatively review the state of the art in four different depth-profiling characterization techniques: Rutherford backscattering spectroscopy (RBS), secondary ion mass spectrometry (SIMS), X-ray photoelectron spectroscopy (XPS) and glow discharge optical emission spectroscopy (GDOES). In addition, we predict future trends in these techniques regarding improvements in their depth resolutions. Subnanometric resolution can now be achieved in RBS using magnetic spectrometry systems. In SIMS, the use of rotating sample holders and oxygen flooding during analysis as well as the optimization of floating low-energy ion guns to lower the impact energy of the primary ions improves the depth resolution of the technique. Angle-resolved XPS provides a very powerful and nondestructive technique for obtaining depth profiling and chemical information within the range of a few monolayers. Finally, the application of mathematical tools (deconvolution algorithms and a depth-profiling model), pulsed sources and surface plasma cleaning procedures is expected to greatly improve GDOES depth resolution.

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