CRPs formed in 17-4 PH SS after an industrially common heat treatment, in order to better understand the Cu precipitation mechanism and to make it possible to further refine the composition and processing of this steel.
EXPERIMENTAL PROCEDURES
The commercial 17-4 PH SS used in this investigation was supplied in the form of hot-rolled bars with a diameter of ~20mm. The composition of the steel measured by APT is 16.00±0.02 Cr, 4.50±0.01 Ni, 2.74±0.01 Cu, 0.824±0.003 Mn, 1.241±0.004 Si, 0.37±0.02 Mo, 0.023±0.001 Nb, 0.111±0.001 Co, 0.065±0.001 V, 0.202±0.001 C, 0.03± 0.001 Al, 73.80±0.04 Fe (all in at%), which is close to the nominal composition of 17-4 PH SS. The steel was solution treated at 1,040°C for 1 h followed by water quenching and tempering at 350–570°C for 4 h. The bars were cut into rods with a cross-section of
0.5×0.5mm2, and needle-like samples for APT analysis were prepared by a standard two-step electro-polishing procedure (Miller, 2000). APT was performed in a LEAP 4000X HR (CAMECA Instrument Inc., Madison, WI, USA) at a residual pressure of about 3×10−9 Pa and a specimen temperature of 50 K, and with a laser pulse frequency of 200kHz and a voltage pulse fraction of 15%. The detection efficiency of the instrument is ~37%, according to the manufacturer. The reconstruction and quantitative analysis of APT data were performed using the IVAS 3.4.3 software. Nearest-neighbor distribution (NND) analysis (Stephenson et al., 2007) was employed to reveal the distribution of solute atoms during early stage ageing. In order to determine the existence of solute clusters/precipitates, a cluster search algorithm based on the maximumseparationmethod (MSM) was used (Miller, 2000). The separation distance (dmax), the surround distance (L), the erosion distance (dero) and the minimum number of atoms (Nmin) in clusters, were selected to be 0.6, 0.4, 0.4, and 50nm, respectively, in line with previous studies (Kolli & Seidman, 2007;Morley et al., 2009; Wang et al., 2015). The average radius Rp and number density Nv of the
precipitates can be calculated using equations (1) and (2), respectively (Miller, 2000):
Rp = sffiffiffiffiffiffiffiffiffiffiffi 3
3npΩ 4πf
Nv = Npf naΩ;
; (1) (2)
where the atomic volume, Ω, is 1.178×10−2nm3 for body-centered cubic (BCC) Fe, ƒ is the overall estimated detection efficiency estimated to be 0.37. Np the number of precipitates in the analyzed volume, np and na the numbers of atoms detected in each precipitate determined by the MSM and the total number of atoms in the data set, respectively.
Atom Probe Tomographic Characterization of Nanoscale Cu-Rich Precipitates 341 RESULTS
Hardness and tensile strength Figure 1 shows the room temperature mechanical properties of 17-4 PH SS tempered for 4 h as a function of tempering temperature. A similar tendency is found in the hardness and the tensile strength curves. The solution-treated sample pos- sesses minimum hardness and tensile strength (33.7 rockwell hardness, C scale (HRC) and 1,200MPa, respectively), which both increase rapidly as the tempering temperature is increased and have their peak value (44.3HRCand 1456MPa, respectively) at 450°C. With increasing temperature, hard- ness, and tensile strength decrease up to 570°C. The strength– temperature behavior during tempering is in general agree- ment with observations reported in previous studies (Hsiao et al., 2002; Mirzadeh & Najafizadeh, 2009).
Solution Treatment
Figure 2 shows NND analysis of the solution-treated sample of 17-4 PH SS. The solute elements are generally homo- genously distributed in the matrix, which illustrates that no clusters or precipitates are
present.Any deviation between the experimental and randomcurves would reflect a non-random distribution of selected element in the data, i.e. the occurrence of solute clustering. The coincidence of the data and random curves for Cu, Ni, and Mn suggests that there are no sig- nificant fluctuations of the solute concentrations or clustering of alloying elements in the solution-treated sample.
Tempering at 420°C
Figure 3 shows the atom maps and the corresponding NND analysis of the sample tempered at 420°C. Similar to the results from the solution-treated sample, Cu,Ni, Al,Mn, and Si atoms (Figs. 3a–3e) appear to be uniformly distributed by visual inspection, especially for Cu and Ni (Figs. 3a, 3b). However, the NND analysis shows significant deviation between the data curve and the random curve for Cu atoms
Figure 1. Variation in hardness (red) and tensile strength (blue) of 17-4 PH stainless steel (SS) tempered at different temperatures for 4 h.
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