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Quantitative methods for the APT analysis of thermally aged RPV steels
Paul D Styman1, Jonathan M Hyde, Keith Wilford
1Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, UK.
Ultramicroscopy
|January 29, 2013
Summary
Atom Probe Tomography (APT) analysis of RPV steels is improved by a new method to distinguish real solute clusters from random statistical noise. This enhances sensitivity for detecting small clusters in aged or irradiated materials.
Area of Science:
- Materials Science
- Metallurgy
- Analytical Chemistry
Background:
- Atom Probe Tomography (APT) is crucial for analyzing RPV steels.
- Varied analysis methods and parameters hinder inter-dataset comparisons.
- Distinguishing true solute clusters from statistical artifacts is challenging.
Purpose of the Study:
- To investigate suitable parameters (d(max), N(min)) for the maximum separation method in APT.
- To develop a method for identifying and excluding statistically random "background" clusters in APT data.
- To improve the sensitivity of APT analysis for small solute clusters in RPV steels.
Main Methods:
- Investigated the probability of random solute clusters based on d(max) and N(min) parameters.
- Developed a method to identify background clusters in experimental APT datasets based on size and composition.
- Applied the method to real APT data from aged or irradiated RPV steel samples.
Main Results:
- Established criteria for differentiating statistically random clusters from genuine aged/irradiated clusters.
- Demonstrated that background clusters are random statistical coincidences.
- The presented method significantly improves sensitivity to small clusters.
Conclusions:
- A robust method for identifying background clusters in APT data is presented.
- This method enhances the reliability of APT analysis for RPV steels.
- Improved sensitivity allows for better characterization of microstructural changes in aged/irradiated materials.
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