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Quantification of boundary segregation in the analytical electron microscope
1Department of Materials Science and Metallurgy, Cambridge University, Pembroke Street, Cambridge, CB2 3QZ, U.K., Department of Materials Science and Engineering, Whitaker Lab 5, Lehigh University, Bethlehem, PA 18015, USA.
Journal of Microscopy
|July 8, 2000
Summary
Accurate quantification of grain-boundary segregation using scanning transmission electron microscopy requires careful modeling of the electron beam-specimen interaction volume. Optimizing experimental parameters like electron energy and rastering can improve detection limits and accuracy.
Area of Science:
- Materials Science
- Analytical Chemistry
- Physics
Background:
- Equilibrium grain-boundary segregation is crucial for material properties.
- Scanning transmission electron microscopy (STEM) with X-ray energy dispersive spectroscopy (XEDS) is used to study segregation.
- Quantification errors arise from assumptions about the electron beam-specimen interaction volume.
Purpose of the Study:
- To investigate errors in quantifying grain-boundary segregation using STEM-XEDS.
- To determine the optimal model for the electron beam-specimen interaction volume.
- To identify experimental parameters that affect quantification accuracy and sensitivity.
Main Methods:
- Comparison of experimental segregation profiles with theoretical models.
- Modeling the electron beam-specimen interaction volume.
- Calculation of minimum detectable segregation levels under varying conditions (probe size, sample thickness, electron energy, rastering).
Main Results:
- The Gaussian model best describes the electron distribution within the interaction volume.
- Optimum sensitivity is not achieved with the thinnest samples or smallest probe sizes.
- Increasing electron energy to 300 keV halves the minimum detectable segregation level.
- Rastering improves quantification accuracy but reduces sensitivity by at least a factor of three.
Conclusions:
- Accurate quantification of grain-boundary segregation requires appropriate modeling of the interaction volume, preferably using a Gaussian distribution.
- Experimental parameters significantly influence the accuracy and sensitivity of segregation measurements.
- Operating at higher electron energies and optimizing rastering strategies are key for improved detection limits.