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Low-magnification Quantitative X-ray Mapping of Grain-boundary Segregation in Aluminum–4 wt.% Copper by Analytical Electron Microscopy

Published online by Cambridge University Press:  29 January 2003

D.T. Carpenter
Affiliation:
Department of Materials Science and Engineering, Lehigh University, 5 East Packer Avenue, Bethlehem, PA 18015
M. Watanabe
Affiliation:
Research Laboratory for High Voltage Electron Microscopy, Kyushu University, Fukuoka 812-8581, Japan
K. Barmak
Affiliation:
Department of Materials Science and Engineering, Lehigh University, 5 East Packer Avenue, Bethlehem, PA 18015
D.B. Williams
Affiliation:
Department of Materials Science and Engineering, Lehigh University, 5 East Packer Avenue, Bethlehem, PA 18015
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Abstract

Abstract: Quantitative X-ray mapping in the analytical electron microscope (AEM) could improve the statistics of grain-boundary segregation measurements if high spatial resolution can be maintained at lower magnifications (<500 kX). Typically, only about 10 boundaries are analyzed because of the difficulty of conventional AEM measurements; however, a low-magnification quantitative X-ray map could contain twice this number of boundaries in a single field of view. Microscope conditions and mapping parameters have been explored for operation at ∼250 kX, under a variety of conditions to illustrate the trade-offs between various characteristics, such as analytical resolution, counting statistics, magnification, and acquisition time. From these data, it is possible to extrapolate to maps generated under different conditions and estimate their limitations with respect to these characteristics. A simple model has been developed to describe the behavior of inclined grain boundaries that can be used to estimate the detectability of segregant as a function of boundary tilt. Using quantitative X-ray maps, grain boundary Cu coverage has been measured from 55 boundaries in Al–4 wt.% Cu with minimal user effort. For fine-grained thin films, mapping is substantially more efficient than other methods of data acquisition and may be used to measure segregation at large numbers of boundaries.

Type
Research Article
Copyright
2001 Cambridge University Press

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