Effect of Cu on Nanoscale Precipitation Evolution 351
Table 1. Chemical Composition of the Experimental Model Alloys (wt%).
Model Alloys Fe–NiAl
Fe–NiAl–Cu Ni
3.26 3.25
Al
1.07 1.09
Cu —
1.63 Fe
Bal. Bal.
Thereportedhardnesswas theaverage valueofseven mea- surements from each sample. Tensile tests were performed using anMTSCMT5205 machine (MTS, Songjiang, Shanghai, China) at a strain rate of 10−3 s−1. The dog bone-shaped tensile samples with a gauge length of 25mm, awidth of 3.2mmand a thickness of 1.6mm, were cut by electro-discharge machining. Thesurfaces of thetensile sampleswerepolisheddowntoa
2,500-grit SiC paper, and then electro-polished to a mirror finish to eliminate scratches and residual stresses. Fracture surfaces of the tensile-tested specimens were examined by scanning electron microscopy. The yield strength was deter- mined using the 0.2% offset plastic strain method. Specimens for APT experiments were prepared by a
two-stage electro-polishing method (Miller, 2000a). The APT analyses were performed in a LEAP 4000 HR (Cameca, Madison, WI, USA) at 50K with a target evaporation rate of 0.5%, a voltage pulse fraction of 20%, and an ultra-high vacuum of ∼10−9 Pa. The pulse repetition rate was 200 kHz. Data reconstructions and analyses were conducted with IVASTM 3.6.8 software. The maximum separation algorithm (Vaumousse et al., 2003) was employed to identify NiAl precipitates and to work out their number density and size distribution. The NiAl precipitates were present as individual particles in the alloys, using Ni and Al as target solute atoms, we selected a separation distance (dmax)of 0.4 nm, and a minimum cluster size of Nmin = 40 solute atoms by using the envelope method (Miller, 2000b; Miller& Kenik, 2004). The mean equivalent radius of precipitates, rp, was calculated using equation (1) (Kolli & Seidman, 2007):
rp = sffiffiffiffiffiffiffiffiffi 3
3nΩ 4πf
; (1)
where the atomic volume, Ω, is 1.178×10−2nm3 for body- centered cubic (bcc) Fe, and ƒ the estimated detection efficiency of the multichannel plate detector in the LEAP system, which is 0.37. The value of n is the number of atoms detected within each precipitate determined by the maximum separation method. As the Fe and Cu contents in these precipitates are not taken into account, the calculation presumably underestimates the equivalent radius of each precipitate.
RESULTS
Mechanical Properties The variation ofmicrohardness as a function of aging time for the Fe–NiAl and Fe–NiAl–Cu alloys are shown in Figure 1. The Fe–NiAl alloy shows a hardness of ~186HV in the
Figure 1. Microhardness as a function of aging time at 500°C for the Fe–NiAl and Fe–NiAl–Cu alloys.
Figure 2. Room temperature tensile stress–strain curves for the as-quenched and 4-h-aged Fe–NiAl and Fe–NiAl–Cu alloys.
as-quenched (AQ) condition. At the aging temperature of 500°C, the hardness decreases slightly in the initial stage of aging. Then the hardness gradually increases and reaches the peak value of ~255HV after 256 h, which is ~69HV higher than that of the AQ sample. With increasing aging time, the hardness decreases due to an over-aging effect. Owing to the solid solution hardening of Cu, the hardness of the Fe–NiAl– Cu alloy in the AQcondition is ~32HVhigher than that of the Fe–NiAl alloy. Upon aging, the Fe–NiAl–Cu alloy shows a significant increase in hardness at the first 0.5h aging period. Subsequently, the Cu addition shifts the hardness peak toward shorter periods of time. The hardness increases to the peak hardness value of ~337HV after 2h aging, followed by a hardness plateau from 2 to 32h. In addition, Cu plays an important role in enhancing the age-hardening ability of the Fe–NiAl–Cu alloy, resulting in a pronounced increase (~82HV) of the peak hardness, as compared with the Fe–NiAl alloy. The tensile engineering stress–strain curves of the
Fe–NiAl and Fe–NiAl–Cu alloys are presented in Figure 2, and the yield strength, ultimate tensile strength, and
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