Analysis of Radiation Damage in Light Water Reactors: Comparison of Cluster Analysis Methods for the Analysis of Atom Probe Data

Abstract

Irradiation of reactor pressure vessel (RPV) steels causes the formation of nanoscale microstructural features (termed radiation damage), which affect the mechanical properties of the vessel. A key tool for characterizing these nanoscale features is atom probe tomography (APT), due to its high spatial resolution and the ability to identify different chemical species in three dimensions. Microstructural observations using APT can underpin development of a mechanistic understanding of defect formation. However, with atom probe analyses there are currently multiple methods for analyzing the data. This can result in inconsistencies between results obtained from different researchers and unnecessary scatter when combining data from multiple sources. This makes interpretation of results more complex and calibration of radiation damage models challenging. In this work simulations of a range of different microstructures are used to directly compare different cluster analysis algorithms and identify their strengths and weaknesses.

Comparison between SANS and APT measurements in a thermally aged Fe-19 at.%Cr alloy

“…Data treatments were performed thanks to the 3D Data Software for Atom Probe Tomography developed by the GPM research group in Rouen, France. Measurement of the size and number density of clusters was performed using the "isoposition" concentration data filter [17,30,31]. The filter enables to distinguish the particles from the surrounding matrix owing to their chemical composition.…”

“…The parameters used were: concentration threshold X Cr > 28 at.%, grid pattern of 1 nm, separation distance d = 0.2 nm and a minimum number of atoms in the particles of 95. This method is shown to be the most efficient to discriminate clusters from the surrounding matrix [17]. The cluster composition was measured using erosion profile [16].…”

“…However, the small size of the probed volume (typically 80 × 80 × 250 nm 3 ) limits APT ability to detect objects with a low density (D v > 6.25 · 10 20 m −3 in this case). Moreover, APT relying on physics of field evaporation of atoms, artefacts may appear that can artificially modify shape and composition of the observed particles [14][15][16][17][18][19]. Respective weaknesses and strengths of SANS and APT make them complementary techniques and cross-checking results obtained for the same alloys is of a large interest [20][21][22].…”

Quantification of APT physical limitations on chemical composition of precipitates in Fe–Cr alloys

“…If the higher lateral resolution of ECoTAP is an advantage, the much smaller analysed volume is not. This lateral uncertainty on the position of the atoms creates some lateral scatter which can bias the chemical composition measurements [28]. In order to study and quantify the influence of the lateral resolution on measurements, the numerical approach presented in Ref.…”

“…In the second section, the APT chemical biases are quantified for the two cases listed above. Quantification of composition bias due to APT spatial resolution was determined using the data numerically generated according to the method developed at the Groupe de Physique des Mat eriaux (France) [28]. Quantification of composition bias due to local magnification effect was undertaken by two methods: modelling of field evaporation using the method developed by Vurpillot et al [25,32,33] on the one hand and using the analytical model of Hatzoglou et al [29,34] on the other hand.…”