Effects of NiAl Precipitation on the Stability of Retained Austenite and Mechanical Properties of a Quenching-partitioning-tempering Treated Medium-manganese Steel

Abstract

The effect of NiAl-type nanoparticles on the austenite stability was investigated during quenching-partitioning-tempering (QPT) processes in a cold rolled medium-manganese steel. A good combination of ductility (total elongation: 37.9%) and strength (yield strength: 995 MPa/ultimate tensile strength: 1260 MPa) is obtained after the first step of partitioning treatment at 630°C/1 h (P₆₃₀) due to appropriate austenite stability and multiple strengthening mechanisms. Moreover, the yield strength and ductility increase further after the second step of tempering treatment at 500°C/2 h by about 113 MPa and 8.5% respectively. It was found that high density of intragranular NiAl-type nanoparticles precipitated during tempering improve the ductility from two aspects. NiAl-type nanoparticles could provide a harder and work-hardenable martensite matrix, which is beneficial for the stability and sustainability of the retained austenite during tensile deformations.

1. Introduction

Cold rolling prior to the reversion treatment is often used to obtain ultrafine grained (UFG) microstructures in medium-Mn steels, which exhibit both high strength and high ductility.^1,2) The competition between recrystallization and reverse transformation of martensite determines the morphology of martensite and reversion austenite, which is strongly influenced by the intercritical annealing temperature.^3,4,5) Though considerable amount of retained austenite (γ) can be obtained by intercritical annealing treatment,^6,7) the increment of annealing time may increase the grain size of reverted austenite and reduce its mechanical stability.⁸⁾

It is well known that nano-sized particles can effectively hinder dislocation motion,⁹⁾ which has been used as a choice for hardening the soft ferrite. In the medium-Mn steels, carbides,^10,11) Ni₃(Ti,Al),¹²⁾ NiAl-type and Cu¹³⁾ nanoparticles have been often applied to strengthen the matrix, but only the non-shearable B2 nanoparticles were found to improve the strain hardening as well as the strength without deteriorating the ductility.¹⁴⁾ Hence, it is a promising way to combine the TRIP effect with the precipitation strengthening from the B2 nanoparticles to improve the strength and ductility of medium manganese steels.

In our previous work, it is found that the NiAl nanoprecipitation can suppress the ferrite transformation during the tempering process.¹⁵⁾ This work focuses mainly on the effect of NiAl-type nanoparticles on the stability of austenite and the corresponding relationship between the microstructure and the mechanical properties during deformation.

2. Materials and Experimental Methods

The hot forged Fe-0.1C-9.12Mn-3.18Ni-1.31Al (wt.%) medium-manganese steel bar was soaked at 1200°C for 1 h and hot rolled into a 5 mm thick plate (quenched in water). Subsequently, the hot rolled steel plate was cold rolled from 5 to 1.5 mm (about a 68% thickness reduction). The heat treatment windows were determined according to the Thermocalc calculation results. Partitioning (P) treatment was carried at 610, 630 and 650°C for 1 h, which are denoted by P₆₁₀, P₆₃₀ and P₆₅₀ respectively. Based on the thermodynamic analysis, tempering (T) treatment was conducted at 500°C for 2 h to introduce more NiAl-type nanoparticles and avoid the precipitation of carbides. For instance, 630°C/1 h+500°C/2 h is denoted by PT₆₃₀. Finally, tensile tests were performed at ambient temperature using a Zwick (BTC-T1-FR020 TN.A50) universal testing machine (strain rate~4×10⁻⁴ s⁻¹). The tensile direction was parallel to the rolling direction. The bone-shaped flat tensile specimens had a gage length of 16 mm and cross-section with dimensions of 5 mm × 1.4 mm.

Detailed microstructure of precipitates, martensite and austenite were characterized by Transmission electron microscope (TEM JEOL JEM 2100F). Thin foils for TEM observations were prepared by electropolishing in a twin-jet apparatus using a 7% solution of perchloric acid and 93% ethanol at 30 V and −20°C. The phase distribution and orientation relationship of martensite and austenite were investigated by electron back-scattered diffraction (EBSD Oxford) at step size ~50 nm and voltage ~20 kV. The austenite volume fraction and dislocation density in the specimens were measured using X-Ray diffractometer (Rigaku D/max-2500, CuKα, λ=1.5418 Å). Before XRD scanning, all specimens were required to electropolish and the same parameters as previous EBSD preparation were used. The scanning parameters were voltage ~40 kV, current ~40 mA, scan speed ~1°/min and angular interval ~40°≤2θ≤100°. Atom probe tomography (APT) measurements were conducted on a local electrode atom probe (LEAP 3000 HR) for obtaining spatial distribution of elements, the number density and size of nanoparticles.¹⁵⁾

3. Results

3.1. Mechanical Properties

The typical engineering stress-strain curves of the alloy under different partitioning and tempering conditions are shown in Fig. 1. It is worth noting that after partitioning at 630°C/1 h and tempering at 500°C/2 h (PT₆₃₀), the alloy exhibits an excellent combination of strength (YS: 1108 MPa/UTS: 1241 MPa) and ductility (TEL: 46.4%), i.e. a significant increase in YS and TEL upon tempering.

Fig. 1.

Engineering stress-strain curves of the alloys under different partitioning and tempering conditions. (a) Tensile curves for P₆₁₀, P₆₃₀ and P₆₅₀. (b) Tensile curves for P₆₃₀ and PT₆₃₀. (Online version in color.)

3.2. Evolution of Microstructures during Partitioning and Tempering

Figures 2(a)–2(d) show the EBSD phase mappings for the specimens treated at P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ respectively. It is noted that the size and volume fraction of the reverted austenite significantly increased from the P₆₁₀ treatment to the P₆₅₀ treatment, but remained nearly unaffected from the P₆₃₀ treatment to the PT₆₃₀ treatment. The grain size was calculated based on the misorientation greater than 15° from EBSD results. The measured average size and standard deviation of austenite grains in the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens were shown in Fig. 3.

Fig. 2.

Phase images and austenite size distributions of the alloys under different partitioning and tempering conditions (Black lines in graph are grain boundaries with misorientation larger than 15°). (a) P₆₁₀. (b) P₆₃₀. (c) P₆₅₀. (d) PT₆₃₀. (Online version in color.)

Fig. 3.

Evolutions of average size of the alloys under different partitioning and tempering conditions. (a) Evolution of austenite average size. (b) Evolution of martenite average size.

Austenite volume fraction of the specimens under different conditions were analyzed by XRD using the integrated intensities of (200)_γ, (220)_γ, (311)_γ, (200)_α, and (211)_α diffraction peaks.¹⁶⁾ Before tensile tests, as shown in Fig. 4, the fractions of austenite steadily increased as the temperature increased from 610 to 650°C, while it remained nearly unchanged from the P₆₃₀ treatment to the PT₆₃₀ treatment. After tensile fracture, samples locating near the fractured end but mainly the uniform elongation section were prepared for XRD analysis. In order to ensure the accuracy of measured results, each sample (about 5 mm×10 mm) was measured 3 times under the same XRD scanning parameters, and finally the average value was taken to obtain the volume fraction of retained austenite. The transformation ratio of austenite after fracture in the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens were 8.39%, 33.56%, 51.33% and 33.41%, respectively.

Fig. 4.

Evolutions of austenite volume fraction before fracture and after fracture, and transformation ratio of austenite under different partitioning and tempering conditions. (a) Evolutions of austenite volume fraction. (b) Evolution of transformation ratio of austenite. (Online version in color.)

Dislocation density was calculated by the modified Williamson-Hall equation.^17,18,19) Considering that the broadening of diffraction peak mainly results from the dislocations, the modified Williamson-Hall plot¹⁷⁾ can be expressed as:   

$$\mathrm{\Delta }K\cong \frac{1}{d}+{\left(\frac{\pi M^2{b}^2}{2}\right)}^{\text{1/2}}{\rho }^{1/2}(K{\overline{C}}^{\text{1/2}})+O(K^{\text{2}}\overline{C})$$(1)

where K = 2sinθ/λ, ΔK = 2cosθΔθ/λ, θ and Δθ represent the diffraction angle and the integral breadth of the diffraction peak, d, b and ρ are the average grain size, the Burgers vector and the dislocation density respectively. M is a constant and O represents non-interpreted higher order terms. The C is the average contrast factor of the dislocations for a particular reflection. The ΔK for each (hkl) peak is plotted as a function of KC^1/2 according to the modified Williamson-Hall equation, as shown in Figs. 5(a) and 5(c). The dislocation density (ρ) can be estimated by the equation below:   

$$\rho =2\frac{m^2}{\pi M^2{b}^2}$$(2)

where m is the slope corresponding to the fitted curve from ΔK vs. KC^1/2 plot.

Fig. 5.

Dislocation density analysis for austenite and martensite under different partitioning and tempering conditions using the modified Williamson-Hall plot. (a), (c) The integral breadth of the diffraction peaks. (b), (d) Dislocation density. (Online version in color.)

The evolution of the dislocation density in austenite and martensite during partitioning and tempering can be seen in Figs. 5(b) and 5(d). The dislocation densities in both austenite and martensite obviously decreased when the temperature increased from 610 to 650°C, while they slightly decreased from the P₆₃₀ treatment to the PT₆₃₀ treatment.

Figure 6 shows TEM images of the specimens after P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ treatment respectively. High densities of precipitates were observed in the P₆₁₀ and P₆₃₀ specimens, which are identified as NiAl-type B2 phase by selected area electron diffraction (SAED) as shown by embedded picture in Fig. 6(a). However, no precipitate was detected in the P₆₅₀ specimen, which indicates that they gradually dissolved as the temperature increased from 610 to 650°C. It should be noted that the NiAl-type particles abundantly precipitated after the PT₆₃₀ treatment, whose number density is the highest. These NiAl-type B2 phase mainly precipitated in interior of grains.

Fig. 6.

TEM BF images Selected Area Electron Diffraction (SAED) patterns of the alloys under different partitioning and tempering conditions. (a) P₆₁₀. (b) P₆₃₀. (c) P₆₅₀. (d) PT₆₃₀. (Online version in color.)

Table 1 shows the equivalent spherical particle radius (R) and particle number density (N_v) of NiAl precipitates of P₆₁₀, P₆₃₀ and PT₆₃₀ samples that were obtained from APT analysis.¹⁵⁾ The R of NiAl-type nanoparticles decreased from 0.96 ± 0.09 nm for the P₆₁₀ specimen to 0.91 ± 0.08 nm for the P₆₃₀ specimen, but increased to 1.12 ± 0.09 nm for the PT₆₃₀ specimen. The N_v of NiAl-type nanoparticles decreased from 0.97 ± 0.09×10²⁴ m⁻³ for the P₆₁₀ specimen to 0.73 ± 0.12×10²⁴ m⁻³ for the P₆₃₀ specimen, but increased to 1.22 ± 0.10×10²⁴ m⁻³ for the PT₆₃₀ specimen.¹⁵⁾

Table 1. Precipitation parameters such as equivalent spherical particle radius (R) and particle number density (N_v) of NiAl-type nanoparticles under different treatment conditions.

Precipitation conditions	Equivalent spherical particle radius (R/nm)	Particle number density (Nv/×1024 m−3)
610°C/1 h	0.96 ± 0.09	0.97 ± 0.09
630°C/1 h	0.91 ± 0.08	0.73 ± 0.12
630°C/1 h+500°C/2 h	1.12 ± 0.09	1.22 ± 0.10

4. Discussion

4.1. Strengthening Mechanism

To clarify the relationship between microstructures and yield strength during partitioning and tempering, the theoretical strength were calculated using a compounding model. Solid solution strengthening for austenite and martensite were estimated by empirical relations^20,21) which are given by   

$${\sigma }_{\gamma }=68+354C+20Si+3.7Cr$$(3)

  

$$\begin{array}{c}{\sigma }_{\alpha }=77+32Mn+678P+83Si+39Cu\\ -31Cr+11Mo+5\mathrm{\hspace{0.17em} }544(N+C)\end{array}$$(4)

Weight percentage of each alloy is used in both equations. The solid solution strengthening effect was estimated to be about 60–80 MPa by simple addition of σ_γ and σ_α with few variations of different samples.

Therefore, the effect of grain boundary strengthening, dislocation strengthening and precipitation strengthening were considered to be the main contributions to the yield strength, which were estimated quantitatively by the Hall-Petch type relation,^22,23) Taylor hardening law²⁴⁾ and the particle shearing mechanism^25,26) respectively.

The contribution of grain boundary strengthening originating from martensite and austenite was assumed to be based on the simple mixture rule,²⁷⁾ expressed as:   

$${\sigma }_g=f_{\gamma }\frac{k_{y_{\gamma }}}{\sqrt{d_{\gamma }}}+f_{\alpha }\frac{k_{y\alpha }}{\sqrt{d_{\alpha }}}$$(5)

where f_γ and f_α are the volume fractions of austenite and martensite respectively. k_yγ and k_yα are the strengthening coefficients of austenite and martensite, which are 274 MPa·m^1/2 and 100 MPa·m^1/2 respectively.²⁸⁾ d represents the grain size. According to the above equation, the grain boundary strengthening for the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens were calculated to be 533, 603, 597 and 584 MPa respectively.

Dislocation strengthening was estimated by Taylor hardening law,²⁴⁾ the combined effect of the two phases, austenite and martensite, was described by the simple mixture rule,²⁷⁾ as follows:   

$${\sigma }_{\rho }=f_{\alpha }\alpha M{G}_{\alpha }{b}_{\alpha }\sqrt{{\rho }_{\alpha }}+f_{\gamma }\alpha M{G}_{\gamma }{b}_{\gamma }\sqrt{{\rho }_{\gamma }}$$(6)

In the present work, f_γ and f_α are the volume fraction of austenite and martensite respectively, the following constants were used: α=0.4 (interaction strength between dislocations),²³⁾ M=3 (Taylor factor); G_α=78500 MPa (shear modulus for body-centered cubic), G_γ=72000 MPa (shear modulus for face-centered cubic), b_α=2.48×10⁻¹⁰ m (Burgers vector in α-Fe), and b_γ=2.58×10⁻¹⁰ m (Burgers vector in γ-Fe). According to Eq. (6), the dislocation strengthening for the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens were calculated to be 381, 225, 134 and 187 MPa respectively.

For the particle shearing mechanism of the NiAl-type nanoparticles, the increase in yield strength resulted mainly from the contributions of order strengthening (Δσ_order), coherency strengthening (Δσ_coherency), and modulus strengthening (Δσ_modulus). The equations for these contributions are:^25,26)   

$$\mathrm{\Delta }{\sigma }_{order}=M\left(\frac{{\gamma }_{apb}^{3/2}}{b}\right){\left(\frac{4r_{s}f}{\pi T}\right)}^{1/2}$$(7)

  

$$\mathrm{\Delta }{\sigma }_{modulus}=M\frac{Gb}{L}{\left[1-{\left(\frac{E_p}{E_m}\right)}^2\right]}^{\frac{3}{4}}$$(8)

  

$$\mathrm{\Delta }{\sigma }_{coherency}=4.1MG{\epsilon }^{3/2}{f}^{1/2}{\left(\frac{R}{b}\right)}^{1/2}$$(9)

where M = 3 is the Taylor factor, γ_apb = 0.5Jm⁻² is average value of the anti-phase boundary energies of NiAl,²⁹⁾ b=0.248 nm is the Burgers vector, r_s = (2/3)^1/2 R is the average particle radius in the glide plane,²⁵⁾ f = 4/3πR³N is the volume fraction of NiAl-type nanoparticles, where R and N are the nanoparticle radius and number density, respectively, T is the line tension of the dislocation, usually expressed by Gb²/2,²⁵⁾ where G=78.5 GPa is the shear modulus of the matrix, ε = 2/3(Δa/a) is the constrained lattice parameter mismatch, with Δa/a ≈ 0.002 as the lattice parameter mismatch between the NiAl-type nanoparticles and matrix,³⁰⁾ L is the mean particle spacing in the slip plane and can be calculated from the equation L = 0.866/(RN)^1/2,²⁵⁾ E_p and E_m are the dislocation line energies in the matrix and the nanoparticles, respectively.²⁶⁾ The experimental data for R and N were determined by APT analysis and are summarized in Table 1. The values of precipitation strengthening were multiplied by the volume fraction of martensite for calculating the overall contribution. The total strengths were calculated to be 1142, 961, 731 and 1016 MPa for the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens, respectively (Fig. 7(b)), while the corresponding experimental results of the yield strength were 1152, 995, 666 and 1108 MPa. The lowest yield strength (666 MPa) in the P₆₅₀ specimen was mainly due to the lack of precipitation strengthening caused by the almost complete dissolution of NiAl-type nanoparticles. Comparing the P₆₃₀ specimen with the PT₆₃₀ specimen, the increase in yield strength (113 MPa) was mainly caused by precipitation of more NiAl-type nanoparticles.

Fig. 7.

Calculated strengthening contributions. (a) Precipitation strengthening contributions of P₆₁₀, P₆₃₀ and PT₆₃₀. (b) Total strengthening contributions of P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀. (Online version in color.)

4.2. The Stability of Austenite and Mechanical Properties

The chemical composition, such as the amounts of C and Mn, of austenite measured from APT in the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens, are summarized in Table 2. In addition, the concentration profiles of Mn, Al, Ni and C with distance were investigated by STEM, as shown in Fig. 8. The Mn and C contents of austenite in the P₆₃₀ specimen (Mn: 12.62 ± 0.29 at.%/C: 0.73 ± 0.03 at.%) were similar to those of austenite in the PT₆₃₀ specimen (Mn: 12.24 ± 0.23 at.%/C: 0.70 ± 0.02 at.%), consistent with the APT results, which suggests that almost no element partitioning occurs from the P₆₃₀ treatment to the PT₆₃₀ treatment.

Table 2. Chemical composition such as Mn and C in austenite under different treatment conditions.

Treatment conditions	Mn (at.%)	C (at.%)
610°C/1 h	12.83 ± 0.28	0.72 ± 0.04
630°C/1 h	12.47 ± 0.30	0.69 ± 0.04
650°C/1 h	11.16 ± 0.23	0.54 ± 0.03
630°C/1 h+500°C/2 h	12.29 ± 0.31	0.67 ± 0.03

Fig. 8.

STEM BF images including line scanning of the alloys under different partitioning and tempering conditions. (a), (b) P₆₃₀. (c), (d) PT₆₃₀. (Online version in color.)

The martensite transformation start temperature (M_s) is a key parameter for estimating the austenite stability. The effect of alloying elements on M_s is calculated using the following empirical equation:³¹⁾   

$$M_s\left(°\mathrm{C}\right)=539-423C-30.4Mn-7.5Si-7.5Mo$$(10)

Using the above equation and corresponding C and Mn contents, the calculated M_s values are 84, 98, 151 and 104°C for the P₆₁₀, P₆₃₀, P₆₅₀ and PT₆₃₀ specimens, respectively. In terms of austenite grain size, it is reported that the M_s of austenite decreases as the grain size decreases,^32,33) which improves the austenite stability and is beneficial to the TRIP effect.^32,34,35) This indicates that the austenite in the P₆₁₀ specimen had the highest stability, and the P₆₃₀ and PT₆₃₀ specimens have similarly moderate stability. It is also demonstrated that high dislocation density can stabilize austenite grain by acting as barriers for glissile martensite interface.¹⁰⁾ According to the calculated dislocation density in austenite (Fig. 5(b)) the dislocation density of P₆₃₀ is slightly higher than PT₆₃₀. Consequently, it is deduced that the stability of austenite of the P₆₃₀ specimen is slightly higher than PT₆₃₀ specimen.

Although the P₆₃₀ and PT₆₃₀ specimens have similar volume fraction of austenite before fracture and similar transformed fraction of austenite after fracture, it is worth noting that the ductility increased about 8.5% from the P₆₃₀ specimen to the PT₆₃₀ specimen.

Figure 9(a) shows the evolution of volume fraction of retained austenite with plastic deformation under two heat treatment conditions. It is found that although the samples for the two conditions contained roughly the similar initial volume fractions of austenite, the rates of austenite transformation during plastic deformation were different. The austenite content decreased more gently under the condition of PT₆₃₀. Moreover, the austenite transformation continued for the entire strain range, in particular, at high strain of 0.32. For the P₆₃₀ treatment, the austenite transformation mainly occurred in a low strain range from 0 to 0.24, and the volume fraction of retained austenite remained unchanged after the strain of 0.24. The work hardening rate, defined as the change rate of the true stress to the true strain dσ/dε, during tensile deformation is shown in Fig. 9(c). The value of strain hardening rate for PT₆₃₀ may be slightly lower than P₆₃₀ but extends to larger strain, indicating a slower but more lasting austenite transformation during deformation.

Fig. 9.

(a) Changes of austenite volume fraction with engineering strain under two conditions of P₆₃₀ and PT₆₃₀. (b) Changes of austenite transformation rate with engineering strain under P₆₃₀ and PT₆₃₀. (c) Evolutions of work hardening rate and austenite volume fraction with true strain under P₆₃₀ and PT₆₃₀. (Online version in color.)

To estimate the transformation rate of austenite during plastic deformation, the following equation was used:³⁶⁾   

$$\frac{V_{\gamma \epsilon }}{V_{\gamma 0}}=k{e}^{-n\epsilon }$$(11)

where V_γε is the volume fraction of austenite at strain ε, V_γ0 is the initial volume fraction of austenite, k is a constant, and n represents the transformation rate of austenite. The exponential fit of the variations of the transformable austenite as a function of strain is shown in Fig. 9(b). The transformation rates of austenite were obtained by an exponential fit, and were found to be about 0.069 and 0.023 for the P₆₃₀ and PT₆₃₀ specimens, respectively. Therefore, it was inferred that improvement of ductility of about 8.5% from the P₆₃₀ specimen to PT₆₃₀ specimen was mainly attributed to a lower transformation rate of austenite and the persisting austenite transformation for the entire strain range.

Austenitic stability is also affected by the surrounding martensite matrix and the strengthening of the matrix could decrease the austenite transformation rate during deformation.^37,38,39) A stronger matrix delays the initiation of the martensitic transformation due to a smaller mean-stress level in the austenite. Furthermore, the strengthening of the matrix can lead to a stress shield effect. The contributions of the calculated yield stress for the surrounding martensite in the P₆₃₀ specimen were 403 MPa (σ_α−g), 219 MPa (σ_α−ρ) and 238 MPa (σ_α−NiAl), while the corresponding values for the PT₆₃₀ specimen were 392 MPa (σ_α−g), 184 MPa (σ_α−ρ) and 409 MPa (σ_α−NiAl), which indicates that the harder martensite matrix in the PT₆₃₀ specimen was mainly due to precipitation strengthening from NiAl-type nanoparticles.

Samples locating near the fracture end of the failed tensile specimens were prepared for EBSD analysis. Figure 10 shows IQ, Phase and KAM images of the specimens under two heat treatment conditions. After tensile failure deformation, there was an obvious <110> // RD texture (RD corresponds to the tensile direction) in the P₆₃₀ specimen and PT₆₃₀ specimens. Similar phase distributions and homogeneous strain distributions after tensile deformation were observed for the two conditions. However, it is found that the strain level in martensite was higher in the PT₆₃₀ specimen according to the KAM values (Fig. 10(h)), mainly owing to precipitation of more NiAl-type nanoparticles, which leads to dislocation pile-up at the phase interface during deformation. It should be noted that the martensite transformed from austenite during deformation is useful as it reallocate the stress distribution and relieve the stress concentration with TRIP effect, though this type of martensite might not be included in the EBSD analysis due to its high density of dislocation. Consequently, this result indicated that the PT₆₃₀ specimen had a harder and more work-hardenable martensite matrix caused by precipitation strengthening from NiAl-type nanoparticles.

Fig. 10.

IQ, Phase images and KAM of the alloys under two conditions of P₆₃₀ and PT₆₃₀. (a), (c), (e) IQ, Phase image and KAM image for P₆₃₀ (after tensile deformation). (b), (d), (f) IQ, Phase image and KAM image for PT₆₃₀ (after tensile deformation). (g) Texture figures of IPFs for the two conditions. (h) The KAM values for the two conditions. (Online version in color.)

Figure 11 shows TEM images of the PT₆₃₀ specimen after tensile failure. It can be seen that the NiAl-type nanoparticles, acting as obstacles against matrix dislocations, are mainly bypassed in the Orowan mechanism. The dislocations cannot penetrate the particles, thus the storage of dislocation loops leads to high strain hardening rate during plastic deformation. With the increased density of nanoparticles in PT₆₃₀, Orowan hardening operates at higher stress due to reduced inter-particle spacing, thus benefiting the increase of ductility.¹²⁾ Therefore, the improvement of ductility from the P₆₃₀ specimen to the PT₆₃₀ specimen can be attributed to the introduction of more NiAl-type nanoparticles, which not only stabilize the austenite by the shield effect but also lead to an effective Orowan hardening mechanism.

Fig. 11.

TEM BF images including SAED pattern of the alloys under the condition of PT₆₃₀ after tensile deformation. (a) TEM BF image including SAED pattern. (b) Partial enlargement in (a). (Online version in color.)

Therefore, a harder and work-hardenable martensite matrix in the PT₆₃₀ specimen (985 MPa) induced a lower transformation rate of austenite compared to that of the P₆₃₀ specimen (860 MPa), resulting in a stronger shield effect and higher austenite stability, which is an important reason for the increase of ductility. Therefore, an excellent combination of strength (yield strength: 1108 MPa/ultimate tensile strength: 1241 MPa) and ductility (total elongation: 46.4%) was achieved.

5. Conclusions

The results can be summarized as follows:

(1) Through the partitioning treatment, different austenite stability was achieved in P₆₁₀, P₆₃₀ and P₆₅₀ specimens based on the effect of chemical composition, grain size and the yield stress of surrounding martensite. An appropriate austenite stability was found in the P₆₃₀ specimen, which contributed to a good combination of ductility and strength.

(2) Both the yield strength and ductility increased after further tempering treatment at 500°C/2 h, NiAl-type nanoparticles could provide a harder and work-hardenable martensite matrix and reduce transformation rate of austenite which is beneficial for the strength and ductility.

Acknowledgments

The authors are thankful to the financial support of the National Key R&D Program of China (No. 2016YFB0300601), National Natural Science Foundation of China (No. 51831002) The authors gratefully acknowledge the support provided by the Tescan China.

Data Availability Statement

The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

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