Evaluation of Clusters in a RPV Weld 377
to use is dependent on the choice of dmax (Hyde et al., 2011b). Random fluctuations (noise) in the solute distribution in the matrix might be classified as clusters with an unsuitable choice of parameters, especially with a too small value of Nmin. Several methods have been proposed for choosing the
parameters for the MSM, often based on comparing the reconstructed atom distribution with random distributions (Cerezo & Davin, 2007; Styman et al., 2013). The MSM has also been compared with other methods, for instance, the use of isoconcentration surfaces, that with the right parameters might give similar results, for example in the case of Cu clusters in Fe (Kolli & Seidman, 2007). Data sets have been simulated in order to further understand the influence of the choice ofMSMparameters (Hyde et al., 2011b), that is, when “the correct answer” is known. The results have also been compared with other techniques, for instance small angle neutron scattering, positron annihilation spectroscopy, and transmission electron microscopy (Meslin et al., 2010a). The irradiated RPV weld material of interest in this
paper contains clusters of mainlyNi, Mn, and Si. Some of the clusters also contain Cu. The material has been exposed to accelerated neutron irradiation in a test reactor. The rela- tively high concentration ofNi and Mnin the matrix and the small size (some down to ~1 nm) make the clusters hard to identify and define. This paper is concerned with discussing the identification of these small and diffuse clusters and with comparing some different methods for choosing the dmax and Nmin parameters for the MSM. Most of the previous APT studies of RPV steel have applied voltage pulsing. Voltage pulsing has some benefits over laser pulsing; in particular it gives less surface diffusion of P and Si related to the crystallography (Hyde et al., 2011a). However, the risk of specimen fracture is experienced to be higher, especially for specimens prepared using the focused ion beam (FIB) lift-out technique. Laser pulsing might be used to increase the probability of finding grain boundaries or other sparse features like dislocations. Here, very long laser pulsed runs are also analyzed and comparedwith voltage pulsed analyses.
MATERIALS ANDMETHODS
The two materials studied are practically identical to the RPV welds of the pressurized water reactor (PWR) Ringhals R4 in Sweden. The welds were post weld heat treated at 620°C in order to relieve internal stresses. They were irradiated to 2.0 and 6.4 ×1023 n/m2 in high flux [2.3 and 3.8 ×1016 n/(m2s), respectively] in the research reactor in Halden, Norway. In this test reactor, the spectrum for neutronswith energies above 1MeV, that damage thematerial, can be considered to impact the material in the same way as the neutrons of a PWR in operation (Efsing et al., 2014). The temperature in the reactor was 290–295°C. The nominal chemical composition of the welds can be seen in Table 1. Samples for APT were prepared in a FIB/scanning
electron microscope (FIB/SEM), an FEI Versa 3D (FEI, Hills- boro, OR, USA), using a standard lift-out method and annularmilling (Larson et al., 1999) as thematerialwas slightly
Table 1. Chemical Composition of the Ringhals R4 Welds in at%.
Cu Ni Mn Mo Si C P S Cr Al Co Fe 0.04 1.58 1.37 0.29 0.28 0.31 0.027 0.007 0.04 0.05 0.01 Bal. Data from Efsing et al. (2007).
active, electropolishing was problematic. The analyses were performed using a LEAP 3000X HR (Imago Scientific Instruments, Madison, WI, USA), which has a detection efficiency of about 37%, according to the supplier. Both laser and voltage pulsing were used in order to get good statistics and to get the correct Si and P distribution (reference Hyde et al., 2011a shows effects of surface migration in similar materials), respectively. Voltage analyses were performed at 50K with a pulse fraction of 20% and a target evaporation rate of 0.2%. In laser mode, the temperature was 30K, the laser energy 0.3nJ and the target evaporation rate 0.5%. In both cases the pulse frequencywas 200 kHz. For voltage pulsed analyses, around 2 million atoms were collected before specimen fracture, whereas 25–70million atomswere collected forthe laserpulsedanalysesbeforetheywerestopped. The data analysis was performed in the IVAS 3.6.10
software (Cameca Inc., Madison, WI, USA). Reconstruction parameters were chosen so that the plane distance at low index poles corresponded to a lattice parameter of 0.287nm (bcc α-iron). These parameters gave the clusters a basically spherical shape. For laser analyses an evaporation field of 23V/nm was used with a k-factor of 4.0 and for voltage analyses 33V/nm and 5.3 were found to be the best parameters. An image compression factor of 1.65 was used for all reconstructions.
RESULTS Microstructure
A reconstruction of a full analysis of the material irradiated to 6.4 ×1023 n/m2 can be seen in Figure 1a, where Cu atoms, as well as 8.2% Ni+Mn+Si isoconcentration surfaces, are shown. In the middle part a dislocation line is evident (marked by an arrow). The dislocation line is enriched in P and cuts the edges of the analysis volume. For further analysis of clusters, similar lines are removed as the forma- tion mechanism, composition, number densities, and shapes may be different for clusters in the matrix and at disloca- tions. Apart from at the dislocations, the clusters are evenly distributed in the volume. One of the larger clusters is cut from the analysis and
the Ni,Mn, Si, andCuatoms are shown in Figure 1b. As seen, the number of Cu atoms is relatively low. In Figure 1c, two or three small clusters are shown, depending on what cluster definition is used. These clusters are rather diffuse, and hence harder to identify than the larger clusters. The matrix contains significant amounts of Ni, Mn, and Si, whereas the Cu concentration outside clusters is small, due to the low Cu bulk concentration.
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