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Updated: May 19, 2026

Energy Dispersive X-ray Tomography for 3D Elemental Mapping of Individual Nanoparticles
Published on: July 5, 2016
Is scanning electron microscopy/energy dispersive X-ray spectrometry (SEM/EDS) quantitative?
Dale E Newbury1, Nicholas W M Ritchie
1Surface and Microanalysis Science Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA. dale.newbury@nist.gov
Abstract:
Scanning electron microscopy/energy dispersive X-ray spectrometry (SEM/EDS) is a widely applied elemental microanalysis method capable of identifying and quantifying all elements in the periodic table except H, He, and Li. By following the "k-ratio" (unknown/standard) measurement protocol development for electron-excited wavelength dispersive spectrometry (WDS), SEM/EDS can achieve accuracy and precision equivalent to WDS and at substantially lower electron dose, even when severe X-ray peak overlaps occur, provided sufficient counts are recorded. Achieving this level of performance is now much more practical with the advent of the high-throughput silicon drift detector energy dispersive X-ray spectrometer (SDD-EDS). However, three measurement issues continue to diminish the impact of SEM/EDS: (1) In the qualitative analysis (i.e., element identification) that must precede quantitative analysis, at least some current and many legacy software systems are vulnerable to occasional misidentification of major constituent peaks, with the frequency of misidentifications rising significantly for minor and trace constituents. (2) The use of standardless analysis, which is subject to much broader systematic errors, leads to quantitative results that, while useful, do not have sufficient accuracy to solve critical problems, e.g. determining the formula of a compound. (3) EDS spectrometers have such a large volume of acceptance that apparently credible spectra can be obtained from specimens with complex topography that introduce uncontrolled geometric factors that modify X-ray generation and propagation, resulting in very large systematic errors, often a factor of ten or more.
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