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Development of Al-TiCN nanocomposites via ultrasonic assisted casting route
Ultrasonics - Sonochemistry 58 (2019) 104626
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Development of Al-TiCN nanocomposites via ultrasonic assisted casting route ⁎
T
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K. Wang , G.P. Xu, H.Y. Jiang , Q.D. Wang, B. Ye, W.J. Ding National Engineering Research Center of Light Alloys, Net Forming, Shanghai Jiao Tong University, 200240 Shanghai, PR China State Key Laboratory of Metal Matrix Composite, Shanghai Jiao Tong University, 200240 Shanghai, PR China
A R T I C LE I N FO
A B S T R A C T
Keywords: Nanoparticle Nanocomposite Cooling rates Ultrasonic dispersion
This work provides a promising approach to achieve the uniform distribution of TiCN nanoparticles (NPs) in aluminum matrix via a combination of ultrasonic dispersion and fast cooling processing. Microstructure analysis demonstrates that as the cooling rate is increased, the NP distribution in the matrix varies from intergranular to intragranular at micro scale and the NP-matrix interface from incoherent to coherent at nano scale. An analytical model is proposed to unveil the effects of cooling rates on the behavior of NPs at the solidification front. The theoretical analysis reveals that the NP size and cooling rate are the two prominent factors determining the NP distribution during solidification of nanocomposites. The experimental results yield an insight into the understanding of NP-induced microstructural evolution and shed new light on the development of high-performance nanocomposites.
1. Introduction
fronts (SFs) during conventional solidification [16]. Therefore, the NP dispersion in the melt and the NP capture by the SF are the two predominant factors in achieving the macroscopically and microscopically uniform NP distribution, respectively. Whether particles can be pushed or captured by the SF depends primarily on the interaction between particles and the advancing SF during solidification. A number of theories [17–19] have been developed to account for the physics of particle-SF interaction, based on which three major criteria have been proposed for particle capture, i.e. thermodynamics, thermal and kinetics. In the thermodynamics criterion [17], free energy change of the particles moving from the liquid to the solid determines whether the particles are pushed or captured. In the thermal criterion [18], the ratio between the thermal conductivity of the particle and the melt affects the SF shape, which in turn determines the particle behaviour. In the kinetics criterion [19], there exists a critical velocity for the particle pushing/capture transition, derived by balancing the repulsive and attractive forces acting on the particles, below which particles are pushed, and above which particle capture occurs. Recently, Xu et al. [20] have proposed a theoretical model for NP capture by taking into consideration Hamaker constant and nanoscale viscosity effect, according to which a low critical velocity can be obtained by increasing the melt viscosity or Hamaker constant of NPs. The effects of cooling rate on NP capture are, however, not considered in their model, presumably because the cooling rate is generally
The demand of metal materials with superior strength and ductility has stimulated the research on metal matrix composites (MMCs) [1,2]. In MMCs, the particulate-reinforced MMCs have been increasingly practised in automotive, aerospace and military industries due to ease of fabrication, potentially low cost and relatively isotropic properties [3–5]. Although metallic composites containing ceramic particles could exhibit high strength, when it comes to micro-sized particles, because coarse particles or particle agglomerates can not only result in the formation of microvoids but also induce high stress concentration during plasticity deformation, the degradation of ductility may occur with increasing the content of microparticles [6,7]. To circumvent the strength-ductility trade-off in MMCs, metal matrix nanocomposites (MMNCs) incorporating nanoparticles (NPs) have been developed in the past few decades [8–10]. Of the multifarious MMNC synthesis methods, solidification processing, capable of mass-producing MMNCs with complex shapes and limitless sizes, is of great practical importance [11–13]. Nowadays, the chief challenge posed by solidification processing is the dispersion of NPs. Normally, NPs tend to agglomerate and form clusters due to the presence of attractive van der Waals forces [14,15]. Effective as ultrasonic treatment is in alleviating it, NPs can readily re-agglomerate into clusters after ultrasonic treatment and are in all probability pushed to grain or phase boundaries by solidification
⁎
Corresponding authors. E-mail addresses: [email protected] (K. Wang), [email protected] (H.Y. Jiang).
https://doi.org/10.1016/j.ultsonch.2019.104626 Received 17 April 2019; Received in revised form 3 June 2019; Accepted 3 June 2019 Available online 04 June 2019 1350-4177/ © 2019 Elsevier B.V. All rights reserved.
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respectively. To achieve solidification at high cooling rates, a wedge chill casting technique was adopted to prepare the samples that experienced a wide range of cooling rates. In this study, the composite slurry was cast into a wedge-shaped copper mold that provides a gradient of cooling rates ranging from 10 to 250 K/s (see Ref. [33]). Three K-type thermocouples were introduced at different positions from the tip to the bottom of the wedge mold to measure the cooling rate. From the measurements, an empirical relationship between the cooling rate (T ̇ ) and the half-thickness of the wedge (d) was obtained as
quite low under routine solidification conditions. In fact, apart from reducing the critical velocity, an alternative way for NP capture is to increase the SF velocity by increasing cooling rate. In the light of the kinetics criterion [19], NPs can be captured by the SF, provided the SF velocity is sufficiently high to exceed the critical velocity. Fast cooling processing [21,22], whereby high solidification rates are obtainable, provides a potential avenue for promoting the NP capture. It is, thus, vital to in-depth understand the mechanism underling the NP capture during solidification of MMNCs. It is well documented that NPs can induce the microstructure evolution of MMNCs [8–11,16,23–25]. Our previous studies [26–29] demonstrate that the NPs pushed by the SF can form a NP layer coating on the growing grain or phase to impede the solutal diffusion physically, leading to the grain or phase growth restriction. In general, the investigations into NP effects on the evolving microstructure during solidification are mainly concentrated on the NP-induced growth restriction rather than the heterogeneous nucleation – that is, NPs are considered to act more as growth-restrictors than nucleants. Because their activation for grain initiation requires a relatively high undercooling (7 K for an 80 nm particle, compared to 0.2 K for a conventional refiner, based on the free growth model [30]), NPs are not usually deemed as very efficient nucleants, even if possessing high nucleation potency. Unlike the conventional solidification processing, NPs may reach the undercooling at which they can become active at enhanced cooling conditions. In addition, the growth restriction effect of NPs may be weakened significantly as the SF at high cooling rates would capture an increasing number of NPs [22]. It is reasonably expected that the roles of NPs in the microstructure evolution are inevitable to vary with the increase of cooling rates. Hence, it is of great necessity to investigate the effects of NPs on the microstructure evolution of MMNCs at various cooling rates as much from the perspective of heterogeneous nucleation as from the growth restriction. In the present work, the uniform dispersion of TiCN NPs in aluminum can be achieved by a combination of ultrasonic dispersion and fast cooling processing. A theoretical analysis was performed to unveil the effects of cooling rates on the behavior of NPs at the SF. The mechanisms underlying the microstructure evolution of Al-TiCN nanocomposites at different cooling rates were then proposed based on the analysis above. The relationship between the microstructure and mechanical properties of Al-TiCN nanocomposites was discussed as well.
T ̇ = 250d−2
(1)
2.2. Microstructural characterization The cast wedge-formed samples were ground, polished, and then etched. The etched samples were imaged using a polarized light optical microscope. The grain sizes were measured using the linear intercept method. The JEOL JSM-7600F FEG-SEM coupled with energy disperse X-ray spectra (EDX) was used to analyze the microstructure and the distribution of nanoparticles. The ion-beammilled TEM foils prepared using a Gatan Precision Ion Polishing System (PIPS, Gatan 691) were examined in a JEOL 2100 TEM at 200 kV. HRTEM analysis was performed using a JEOL 2100F FEGTEM at 300 kV. The TEM samples for the observation of the interfacial structures between α-Al and TiC0.5N0.5 were fabricated using a dual-beam focused ion beam (FIB, Helios Nanolab, FEI). 2.3. Mechanical characterization Nanoindentation tests were performed in load control mode on a Hysitron TI 950 TriboIndenter nanoindenter at a constant loading rate of 200 μN/s up to a maximum load of 50 mN with a Berkovich threesided pyramidal diamond indenter (nominal angle of 65.3° and tip curvature radius of 100 nm). The in-situ scanning probe microscopy (SPM) equipped on TI 950 can offer an in-situ scanning at high magnification mode for microstructure identification before and after each nanoindentation test. The indentations were carried out on the longitudinal sections of the sample, i.e. onto the transverse plane, at a load of 10 mN with the loading and unloading cycle of 30 s each. Tensile tests were performed at ambient temperature on an INSTRON-5689 universal testing machine. Tensile properties measured included ultimate tensile strength (UTS), the 0.2% offset yield strength (YS) and percent elongation or strain to fracture (El.%). Tensile tests were conducted three times for each specimen and an average of three readings was reported. The sampling locations and dimensions of tensile specimens are shown in Supplementary.
2. Experimental material and procedures 2.1. Sample preparation The commercial-purity (CP) Al was used as matrix material. TiC0.5N0.5 nanoparticles with an average diameter of ~80 nm were selected as reinforcements because TiCN is a solid solution for FCC TiN and FCC TiC, possessing the features from both sides such as the high thermal and chemical stability, strong oxidation resistance and desirable compatibility with the aluminum matrix [31,32]. The synthesis of Al-TiCN nanocomposites was conducted first by ultrasonic dispersion and then by fast cooling processing. The pure aluminum was melted in an alumina crucible using an electric resistance furnace. To prepare the nanocomposites, 0, 0.5, 1.0, 1.5, and 2.0 vol.% TiCN nanoparticles were wrapped with thin foils and incorporated into the melt. The ultrasonic treatment system that consists of a transducer, booster and sonotrode, shown schematically in Ref. [29], was employed to disperse TiCN nanoparticles. The ultrasonic treatment was carried out at 993 K for 20 min in an inert atmosphere of argon gas. After dispersing the nanoparticles, the ultrasonic probe was lifted out of the melt, and then the melt was heated to 1013 K for pouring. The melt was cast into a cylindrical permanent mold (25 mm in diameter and 150 mm in height) preheated to 623 K. To achieve solidification at a low cooling rate, the melt in the alumina crucible was allowed to cool in the air. The average cooling rates for the two cases were estimated to be 6 K/s and 1.5 K/s,
3. Results 3.1. Microstructural evolution The anodized micrographs obtained from four locations of the wedge samples with and without NP addition are displayed in Fig. 1(a)–(d) and (g)–(j), which correspond to the cooling rates of 12, 21, 34 and 71 K/s, respectively. The as-cast microstructure of CP Al shows columnar growth, with the coarse grains growing perpendicularly to the mold walls. As the cooling rate is increased, the α-Al grains become finer, while still maintaining the columnar structure. After addition of 2 vol.% NPs, a marked transformation from bulky columnar grain to fine equiaxed grain occurs and the equiaxed grains are more significantly refined with increasing cooling rate. The macrostructural evolution shown in Fig. 1(e) and (f) also confirms that it is the NP addition that can induce the morphological transition of α-Al grains rather than the cooling rate, even if which is increased up to 71 K/s. The grain size of the samples with various NP additions is plotted in Fig. 1(k) as a function of cooling rate. It is evident that the α-Al grain 2
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Fig. 1. Macrographs and micrographs of wedge-formed samples: (a)–(e) Matrix alloy; (f)–(j) 2 vol.%; (k) Grain diameters as functions of the cooling rates; (l) Refinement efficiency as functions of the cooling rates.
uniform microstructure, with the equiaxed grains prevailing in the matrix. Also notable is a clear decreasing trend of the GRE with the cooling rate, indicating that the NP effect may be compromised at high cooling rates.
size decreases with the increment of cooling rate and NP addition level. When the cooling rate increases from 1.5 to 71 K/s, the average grain size decreases from 1500 to 700 μm while it is further reduced to 78 μm as the NP addition level reaches up to 2.0 vol.%. Fig. 1(l) exhibits the variation of grain refinement efficiency (GRE = (dCP Al − dNP)/dCP Al) with the cooling rate at different NP addition levels. As shown in Fig. 1(l), the GRE increases notably with the NP addition level, but decreases linearly with the cooling rate. The 2.0 vol.% NP addition combined with the cooling rate of 1.5 K/s can give the maximum GRE of 91% in this study. The results above suggest that the NP addition has a more pronounced influence on the α-Al grain refinement than the cooling rate. Even though a high cooling rate can promote the grain refinement of CP Al by providing a large undercooling, the coarse columnar grains still develop predominantly during solidification due to the lack of potent nucleants. Conversely, the Al-TiCN nanocomposite exhibits a fine and
3.2. Nanoparticle distribution To investigate the effects of cooling rate on the NP distribution, the wedge sample with 2.0 vol.% NP addition are redivided into three zones, i.e. Zone I (10 K/s ≤ T ̇ ≤ 20 K/s), Zone II (20 K/s ≤ T ̇ ≤ 40 K/s) and Zone III (40 K/s ≤ T ̇ ≤ 111 K/s). Fig. 2 illustrates three sets of SEM micrographs revealing the different distribution patterns of NPs. In Zone I, a large quantity of NPs, whose average size is less than 100 nm, are distributed along the grain boundary. The adsorption of NPs onto the grain boundary can form a NP layer by which the grain growth is restricted. In Zone II, a majority of NPs are located at the grain 3
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Fig. 2. SEM micrographs of the wedge-formed sample with 2.0 vol.% NP addition: (a)–(c) Zone I; (d)–(f) Zone II; (g)–(i) Zone III.
boundary while a small amount of NPs is dispersed in the interior of αAl grain. These NPs exist in the form of either discrete NPs or large NPclusters with the size of a few hundred nanometers. The NP accumulation at grain boundaries can still lead to the grain growth restriction. In stark contrast to Zone I and II, NPs are hardly observed at the grain boundary in Zone III; instead, they are distributed uniformly inside the grain. Overall, it can be concluded from Fig. 2 that as the cooling rate is increased, the pattern of NP distribution varies from the intergranular distribution in Zone I, to the intergranular-intragranular mixture distribution in Zone II, and eventually to the intragranular distribution in Zone III.
interplanar spacings of (1 1 1) are 0.2475 and 0.2338 nm, respectively. From Fig. 3(d), it is clearly visible that there is no crystallographic orientation relationship between the intergranular NP and the matrix, meaning that the NP has an incoherent interface with the α-Al. With the increment of cooling rate, an increasing number of NPs are dispersed inside the grain. Compared with the intergranular NPs, which are randomly orientated to the advancing solid, the intragranular ones are more likely to possess a specific orientation relationship with the solid though some of them may still have incoherent interfaces with the matrix if they expose to the Al melt certain planes that have a large interplanar misfit with the Al matrix. As shown in Fig. 3(e), the NPmatrix interface is smooth and taintless, where no intermediate phase is observed. More significantly, the TiC0.5N0.5 nanoparticle is perfectly coherent with the Al matrix, and a parallel orientation relationship between TiCN and Al can be obtained as (11¯1)Al [1¯12 ]Al//(1¯11¯)NP [1¯12 ]NP. The atomically smooth and coherent interface can give high interfacial bonding strength between the TiCN nanoparticle and the Al matrix, thus improving the load transfer efficiency. On the other hand, the well-defined OR is applicable to the determination of the lattice misfit between Al and TiCN. The estimated lattice misfit is determined to be around 5.85%, verifying the high potency of TiCN as heterogeneous nucleation site for Al. At low cooling rates, the NPs that are distributed intergranularly throughout the matrix can form a NP layer to restrict the grain growth physically. Also, because the melt undercooling is small, a large proportion of NPs may never reach the free-growth undercooling at which they would become
3.3. TEM analysis Fig. 3 presents the TEM analysis of the TiC0.5N0.5 nanoparticles distributed in different zones of the wedge sample with 2.0 vol.% NP addition. Fig. 3(a) exhibits the assembly of NPs onto the grain boundary in Zone I, which is typical of the intergranular distribution. Fig. 3(b) shows that in addition to the grain boundary, the NPs in Zone II are distributed inside the α-Al grain, i.e. the intergranular-intragranular mixture distribution. Fig. 3(c) displays the NPs located in the interior of α-Al grain in Zone III, i.e. intragranular distribution. Fig. 3(d) and (e) are the HRTEM images highlighting the interfaces between the Al matrix and the nanoparticles at the grain boundary in Zone I and inside the grain in Zone III, respectively. The crystallographic information provided in Fig. 3(f)–(i) is consistent with TiC0.5N0.5 and α-Al, whose 4
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Fig. 3. (a)–(c) TEM bright-field images showing the different NP distribution in the three zones; (d) and (e) HRTEM images of the NP/Al interfaces; (f) and (h) Fast Fourier transformation (FFT) of NP and Al, respectively; (g) and (i) Inverse Fourier transformation (IFFT) of NP and Al, respectively.
3.4. Nanoindentation test
active [30]. For this reason, the grain refinement in Zone I is mainly attributed to NP-induced growth restriction. As the cooling rate is increased, an increasing number of NPs are captured by SF and the NP layer can hardly be formed. At high cooling rates, the undercooling in the liquid is high enough for NP activation that NPs can promote the heterogeneous nucleation of α-Al. Thus, the NP-induced growth restriction would take a back seat to NP-induced heterogeneous nucleation for the grain refinement that occurs in Zone III. Note that according to classic nucleation theory, there is only one nucleation site for an individual grain. Therefore, only a limited fraction of NPs are involved in the nucleation events, in spite of the NPs distributed intragranularly throughout the matrix in Zone III.
The nanoindentation test results obtained from Zone I to III in the 2.0 vol.% Al-TiCN wedge sample are illustrated in Fig. 4. Given the wedge sample with the same alloy composition and NP addition level, the cooling rate may be taken as the sole factor in determining the mechanical property evolution of the nanocomposite. It is manifest from Fig. 4(a) that the nanoindentation hardness (H) is increased from 0.48 GPa to 0.98 GPa with increasing the cooling rate from 11 to 85 K/s. The inset in Fig. 4(a) shows the load-displacement curves during cycles of loading and unloading for the three typical zones of the nanocomposite as a function of cooling rate. There is an evident trend that
5
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Fig. 4. (a) Nanoindentation hardness measurement in the three zones of the wedge-formed sample with 2.0 vol.% NP addition. The inset is the load-displacement curves for the typical three zones of the wedge-formed sample; (b) Modulus measurement in the three zones of the wedge-formed sample; (c) Engineering stress-strain curves of CP Al and nanocomposites; (d) Comparison of the tensile strength and elongation of the nanocomposites with previously reported materials.
which in turn leads to the enhanced grain boundary strengthening and resistance to crack propagation, thus facilitating improvement in strength and ductility. Another reason for the high hardness and strength of the nanocomposite produced at high cooling rates is attributed to the interfacial bonding strength between the NPs and the matrix. During plastic deformation, a strong bonding coherence can improve the ability for load transfer from the matrix to TiCN nanoparticles leading to a more efficient strengthening of the nanocomposite [41].
the indenter penetration depth decreases with increasing cooling rate, implying that the nanocomposite solidified at high cooling rates can exhibit the enhanced resistance to indentation. The dependence of nanocomposite modulus on cooling rate is plotted in Fig. 4(b). The nanocomposite modulus increases almost monotonically with the cooling rate. As the cooling rate ranges from 11 to 85 K/s, the average elastic modulus of the nanocomposite is increased from 67.4 to 81.9 GPa. The engineering stress-strain curves of the CP Al and Al-TiCN nanocomposites are shown in Fig. 4(c). It is obvious that at the same NP addition level, both the tensile strength and ductility of the nanocomposite increase significantly with the cooling rate. When the average cooling rate reaches 60 K/s, the average tensile strength and elongation of the 2.0 vol.% Al-TiCN nanocomposite are improved from 60 MPa and 30% to 295 MPa and 35%, respectively. Fig. 4(d) presents the relationship between the strength and elongation of the Al-TiCN nanocomposites and the Al matrix composites reported in literature [34–39]. The present results reveal that the 2.0 vol.% Al-TiCN nanocomposite produced at high cooling rates can offer excellent mechanical properties. Based on the microstructural analysis, the TiCN nanoparticles in Zone III are uniformly dispersed in the interiors of fined grains, whereas those in Zone I are distributed along the grain boundaries. As a consequence, the rigid TiCN nanoparticles in Zone III can act as a more robust barrier to dislocation movement through the matrix and offer higher resistance to local plastic deformation in comparison to those in Zone I, triggering enhanced hardness and strength [40]. Moreover, a refined grain size will induce an increased number of grain boundaries,
4. Discussion 4.1. Solidification mechanism During the undercooled liquid solidification of Al-TiCN nanocomposite, the NPs are initially assumed to be homogeneously distributed in the liquid, and the SF is considered flat behind a nanoparticle. As the SF is advancing, the NPs with a lower thermal conductivity than the liquid may stifle the latent heat release from the SF and thereby have a higher temperature than the surrounding liquid, inducing a locally distorted temperature field in the vicinity of the NP, as illustrated in Fig. 5(a). In the nanoparticle capture model, the van der Waals interaction potential between a nanoparticle and an advancing solid/liquid interface is given by [42] 6
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Fig. 5. (a) Schematic of the interaction between a nanoparticle and the solid-liquid interface; (b) Interrelations among undercooling, the added particle size and the velocity (the SF velocity and the critical velocity) in the three-dimensional coordinate system; (c) NP behaviour map.
Wvdw = −
A⎛R R D ⎞ + + ln 6 ⎝D 2R + D 2R + D ⎠
η=
(2)
AAl (liquid) )( ATiCN −
AAl (liquid) )
(3)
where Asys is the system Hamaker constant, R is the TiCN nanoparticle radius, and D is the nanoparticle/interface separation. Assuming D < < R, Eq. (2) reduces to
Wvdw = −
FD + FR = 0
(4)
Vcr =
Given that AAl(liquid) < AAl(solid), and ATiCN < AAl(liquid), Wvdw > 0. As a consequence, TiCN NPs are subjected to the repulsive van der Waals forces (FR) exerted by the SF, which can be determined by
FR = −
Asys R dWvdw =− dD 6D 2
R2 D
Asys (Dcr − 2D0 ) 36πRηb Dcr2
(9)
For crystal growth into a highly undercooled alloy melt, as obtained in fast cooling processing, an equiaxed grain structure develops and the dendrite growth kinetics can be described by Lipton-Kurz-Trivedi (LKT) model, in which the SF velocity Vt is given by [46]
(5)
Vt = μΔT n
The other force acting on a TiCN nanoparticle in Fig. 5(a) is the attractive viscous drag force (FD) imposed by the flow in the particle/ interface separation, which can be calculated by [44]
FD = 6πην
(8)
Substituting Eqs. (5)–(7) into Eq. (8) and rearranging gives the critical velocity Vcr as
Asys R 6D
(7)
where ηb is the bulk liquid viscosity, v is the interface velocity, and D0 is the atomic diameter of liquid metal. When the SF reaches a critical distance Dcr, the force equilibrium is established as
and for the Al-TiCN system [43]
Asys ≈ ( AAl (solid) −
D η D − D0 b
(10)
where μ and n are constants, independent on the undercooling, and ΔT is the melt undercooling. The predicted critical velocities combined with the calculated SF velocities are presented in Fig. 5(b), and the parameters used are listed in Table 1. There are two curved surfaces in Fig. 5(b) – one representing the critical velocity Vcr versus the nanoparticle radius R and the other
(6)
Here η is given by [45] 7
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the Burgers vector, dNP is the mean NP size and VNP is the volume fraction of NPs. In this work, M = 3, G = 27 GPa, b = 0.286 nm, dNP = 80 nm and VNP = 0.02. The contribution from Orowan strengthening is estimated to be 98 MPa.
Table 1 Parameters used for the calculation of critical velocity and SF velocity. Parameter
Units
Value −2
ηb AAl(liquid) AAl(solid) ATiCN Dcr D0 μ n
NSm zJ zJ zJ nm nm – –
0.85 × 10 266 333 157 0.58 0.3 4 × 10−8 0.4
Reference −3
[47] [48] [49] [50] [20] [20] [51] [51]
4.2.3. Coefficient of thermal expansion (CTE) mismatch strengthening The mismatch between the thermal expansion coefficient of the matrix and nanoparticles can produce geometrically necessary dislocations around nanoparticles to accommodate the CTE difference, which in turn leads to an enhancement in yield strength of MMNCs. The CTE mismatch contribution can be determined by [55]
ΔσCTE =
the SF velocity Vt versus the undercooling ΔT, the intersecting line of which (the blue line) consists of all the critical points satisfying the critical criterion that for the given ΔT and R, Vcr = Vt. The projection onto the R-ΔT plane of the intersecting line is plotted in Fig. 5(c), which is divided into two regions by the projection line (the red line), i.e. Region I and II. For any given R and ΔT in Region I, Vcr > Vt, and NPs are pushed, similarly to those in Zone I of the wedge sample, where NPs exhibit intergranular distribution. On the contrary, for any given R and ΔT in Region II, Vcr < Vt, and NPs are captured, in which case NPs are expected to manifest intragranular distribution that is identical to the NP distribution in Zone III of the wedge sample. Accordingly, it is theorized that the NP size and cooling rate are the two prominent factors determining the NP distribution during solidification of MMNCs. In validating the accuracy of the theoretical model, it is pivotal to make a quantitative comparison between theoretical predictions and experimental results. As discussed in 3.2, the pattern of particle distribution varies with the cooling rate. In this work, the average radius of added NPs is 40 nm, and the corresponding critical undercooling is approximately 39 K. For NPs in Zone I, ΔT is estimated to be much less than 39 K, and thus NPs are in all probability pushed. On the other hand, for NPs in Zone III, ΔT may reach or even exceed 39 K, especially when the cooling rate is increased up to 111 K/s, meaning that NPs are highly likely to be captured. The model prediction agrees well with experimental observations.
ρCTE =
To predict the strength of Al-TiCN nanocomposites, in determining the NP contribution on strength improvement, a generalized model [40] was introduced by taking into consideration grain refinement strengthening (ΔσHP ), Orowan strengthening (ΔσOrowan ) and coefficient of thermal expansion (CTE) mismatch strengthening (ΔσCTE ).
(ΔσOrowan )2 + (ΔσCTE )2
(11)
4.2.1. Grain refinement strengthening A well-established Hall-Petch relationship [52] can be used to evaluate the increased yield strength due to grain refinement:
ΔσHP = kd−1/2
(12)
(14a)
The uniform dispersion of 2.0 vol.% TiCN nanoparticles has been achieved in CP aluminum through a combination of ultrasonic dispersion and fast cooling processing. The intragranular distribution of NPs obtained by tuning cooling rates can yield about 391% and 18% enhancement in tensile strength and ductility, respectively, compared to that of CP Al. The matrix structure over a large cooling rate range consists of fine equiaxed α-Al grains, whose size decreases with increasing cooling rate. The NP distribution in the matrix also varies with the cooling rate: an increase of the cooling rate from 10 to 111 K/s can result in the variation of NP distribution from intergranular to intragranular at micro scale and the transition of NP-matrix interface from incoherent to coherent at nano scale. A numerical model was
4.2.2. Orowan strengthening The strengthening contribution from the interactions between moving dislocations and NPs in the matrix can be described by the Orowan strengthening mechanism, which is given by [54]
MGb 6VNP 1/3 ⎛ ⎞ dNP ⎝ π ⎠
12VNP Δα ΔT (1 − VNP ) bdNP
5. Conclusions
where k is a constant and d is the average grain size. For the 2.0 vol.% Al-TiCN nanocomposite produced at 60 K/s, k is 0.326 MPa m1/2 [53] and d is 82 μm. Therefore, the ΔσHB has shown an increment of 36 MPa in yield strength.
ΔσOrowan =
(14)
where β is the dislocation strengthening coefficient, ρCTE is the dislocation density induced by the CTE mismatch, Δα is the CTE difference between the matrix and the nanoparticles and ΔT is the temperature change. Considering that β = 1.25, Δα = 15.6 × 10−6 K−1 and ΔT = 310 K, the ΔσCTE is calculated to be around 120 MPa, which is much larger than other strengthening contributions. This result highlights the predominant role in strengthening the matrix of the CTE mismatch strengthening. Substituting the predicted values obtained by Eqs. (12)–(14) into Eq. (11) approximates the yield strength of 191 MPa, showing good overall agreement (within 4.4%) with the experimental value of 183 MPa. By evaluating the contribution of individual strengthening mechanism, it is plausible that the full activation of grain refinement, Orowan mechanism and CTE mismatch strengthening mechanism is highly likely to occur in Al-TiCN nanocomposites, thus greatly enhancing the overall strength. Of them, the CTE mismatch strengthening is the most dominant contributor to the increase in yield strength, followed by the Orowan mechanism. Both outperform the grain refinement. A set of TEM images in Fig. 6 illustrate the interactions between dislocations and TiCN nanoparticles in the Al-TiCN nanocomposite that had previously been deformed by 0.2%. As shown in Fig. 6(a), the dislocations circumvent the nanoparticles and leave several Orowan loops surrounding them after crossing. The dislocation in Fig. 6(b) is bypassing a nanoparticle through the Orowan mechanism and an Orowan loop is formed incipiently around it. The bowing out of the dislocation can also be observed in the matrix (Fig. 6(c) and (d)). Driven by the applied stress, the dislocation bowing is caused by the resistance force exerted by the nanoparticles which in turn depends on the NPmatrix bonding and the hardness of nanoparticles [56]. From Fig. 6, it is salient that the rigid TiCN nanoparticles can not be sheared by the gliding dislocations. The unshearable nature of the TiCN nanoparticles combined with a strong coherent Al/TiCN interface results in the high resistance to the dislocation motion and thereby the great improvement in the yield strength of Al-TiCN nanocomposites.
4.2. Strengthening mechanisms
ΔσTotal = ΔσHP +
3 βG ρCTE
(13)
where M is the Taylor factor, G is the shear modulus of the matrix, b is 8
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Fig. 6. TEM images of the nanocomposite solidified at the average cooling rate of 60 K/s after tensile deformation (0.2% strained): (a) (b) Dislocations circumvent nanoparticles and leave Orowan loops around them. (c) (d) Dislocations bow out at the NP-matrix interface.
proposed to estimate the extent to which the cooling rate can influence the behavior of NPs at the solidification front. The theoretical analysis reveals that the NP size and cooling rate are the two prominent factors determining the NP distribution during solidification of nanocomposites. Experimental work and theoretical analysis substantiate that the CTE mismatch and Orowan strengthening are the predominant contributors to the great improvement in yield strength of Al-TiCN nanocomposites.
[2]
[3]
[4]
Acknowledgement [5]
The present study was sponsored by the National Natural Science Foundation of China, People’s Republic of China (NSFC) under Grant no. 51804197.
[6]
Appendix A. Supplementary data
[7]
Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ultsonch.2019.104626.
[8]
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Ultrasonics - Sonochemistry journal homepage: www.elsevier.com/locate/ultson
Development of Al-TiCN nanocomposites via ultrasonic assisted casting route ⁎
T
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K. Wang , G.P. Xu, H.Y. Jiang , Q.D. Wang, B. Ye, W.J. Ding National Engineering Research Center of Light Alloys, Net Forming, Shanghai Jiao Tong University, 200240 Shanghai, PR China State Key Laboratory of Metal Matrix Composite, Shanghai Jiao Tong University, 200240 Shanghai, PR China
A R T I C LE I N FO
A B S T R A C T
Keywords: Nanoparticle Nanocomposite Cooling rates Ultrasonic dispersion
This work provides a promising approach to achieve the uniform distribution of TiCN nanoparticles (NPs) in aluminum matrix via a combination of ultrasonic dispersion and fast cooling processing. Microstructure analysis demonstrates that as the cooling rate is increased, the NP distribution in the matrix varies from intergranular to intragranular at micro scale and the NP-matrix interface from incoherent to coherent at nano scale. An analytical model is proposed to unveil the effects of cooling rates on the behavior of NPs at the solidification front. The theoretical analysis reveals that the NP size and cooling rate are the two prominent factors determining the NP distribution during solidification of nanocomposites. The experimental results yield an insight into the understanding of NP-induced microstructural evolution and shed new light on the development of high-performance nanocomposites.
1. Introduction
fronts (SFs) during conventional solidification [16]. Therefore, the NP dispersion in the melt and the NP capture by the SF are the two predominant factors in achieving the macroscopically and microscopically uniform NP distribution, respectively. Whether particles can be pushed or captured by the SF depends primarily on the interaction between particles and the advancing SF during solidification. A number of theories [17–19] have been developed to account for the physics of particle-SF interaction, based on which three major criteria have been proposed for particle capture, i.e. thermodynamics, thermal and kinetics. In the thermodynamics criterion [17], free energy change of the particles moving from the liquid to the solid determines whether the particles are pushed or captured. In the thermal criterion [18], the ratio between the thermal conductivity of the particle and the melt affects the SF shape, which in turn determines the particle behaviour. In the kinetics criterion [19], there exists a critical velocity for the particle pushing/capture transition, derived by balancing the repulsive and attractive forces acting on the particles, below which particles are pushed, and above which particle capture occurs. Recently, Xu et al. [20] have proposed a theoretical model for NP capture by taking into consideration Hamaker constant and nanoscale viscosity effect, according to which a low critical velocity can be obtained by increasing the melt viscosity or Hamaker constant of NPs. The effects of cooling rate on NP capture are, however, not considered in their model, presumably because the cooling rate is generally
The demand of metal materials with superior strength and ductility has stimulated the research on metal matrix composites (MMCs) [1,2]. In MMCs, the particulate-reinforced MMCs have been increasingly practised in automotive, aerospace and military industries due to ease of fabrication, potentially low cost and relatively isotropic properties [3–5]. Although metallic composites containing ceramic particles could exhibit high strength, when it comes to micro-sized particles, because coarse particles or particle agglomerates can not only result in the formation of microvoids but also induce high stress concentration during plasticity deformation, the degradation of ductility may occur with increasing the content of microparticles [6,7]. To circumvent the strength-ductility trade-off in MMCs, metal matrix nanocomposites (MMNCs) incorporating nanoparticles (NPs) have been developed in the past few decades [8–10]. Of the multifarious MMNC synthesis methods, solidification processing, capable of mass-producing MMNCs with complex shapes and limitless sizes, is of great practical importance [11–13]. Nowadays, the chief challenge posed by solidification processing is the dispersion of NPs. Normally, NPs tend to agglomerate and form clusters due to the presence of attractive van der Waals forces [14,15]. Effective as ultrasonic treatment is in alleviating it, NPs can readily re-agglomerate into clusters after ultrasonic treatment and are in all probability pushed to grain or phase boundaries by solidification
⁎
Corresponding authors. E-mail addresses: [email protected] (K. Wang), [email protected] (H.Y. Jiang).
https://doi.org/10.1016/j.ultsonch.2019.104626 Received 17 April 2019; Received in revised form 3 June 2019; Accepted 3 June 2019 Available online 04 June 2019 1350-4177/ © 2019 Elsevier B.V. All rights reserved.
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respectively. To achieve solidification at high cooling rates, a wedge chill casting technique was adopted to prepare the samples that experienced a wide range of cooling rates. In this study, the composite slurry was cast into a wedge-shaped copper mold that provides a gradient of cooling rates ranging from 10 to 250 K/s (see Ref. [33]). Three K-type thermocouples were introduced at different positions from the tip to the bottom of the wedge mold to measure the cooling rate. From the measurements, an empirical relationship between the cooling rate (T ̇ ) and the half-thickness of the wedge (d) was obtained as
quite low under routine solidification conditions. In fact, apart from reducing the critical velocity, an alternative way for NP capture is to increase the SF velocity by increasing cooling rate. In the light of the kinetics criterion [19], NPs can be captured by the SF, provided the SF velocity is sufficiently high to exceed the critical velocity. Fast cooling processing [21,22], whereby high solidification rates are obtainable, provides a potential avenue for promoting the NP capture. It is, thus, vital to in-depth understand the mechanism underling the NP capture during solidification of MMNCs. It is well documented that NPs can induce the microstructure evolution of MMNCs [8–11,16,23–25]. Our previous studies [26–29] demonstrate that the NPs pushed by the SF can form a NP layer coating on the growing grain or phase to impede the solutal diffusion physically, leading to the grain or phase growth restriction. In general, the investigations into NP effects on the evolving microstructure during solidification are mainly concentrated on the NP-induced growth restriction rather than the heterogeneous nucleation – that is, NPs are considered to act more as growth-restrictors than nucleants. Because their activation for grain initiation requires a relatively high undercooling (7 K for an 80 nm particle, compared to 0.2 K for a conventional refiner, based on the free growth model [30]), NPs are not usually deemed as very efficient nucleants, even if possessing high nucleation potency. Unlike the conventional solidification processing, NPs may reach the undercooling at which they can become active at enhanced cooling conditions. In addition, the growth restriction effect of NPs may be weakened significantly as the SF at high cooling rates would capture an increasing number of NPs [22]. It is reasonably expected that the roles of NPs in the microstructure evolution are inevitable to vary with the increase of cooling rates. Hence, it is of great necessity to investigate the effects of NPs on the microstructure evolution of MMNCs at various cooling rates as much from the perspective of heterogeneous nucleation as from the growth restriction. In the present work, the uniform dispersion of TiCN NPs in aluminum can be achieved by a combination of ultrasonic dispersion and fast cooling processing. A theoretical analysis was performed to unveil the effects of cooling rates on the behavior of NPs at the SF. The mechanisms underlying the microstructure evolution of Al-TiCN nanocomposites at different cooling rates were then proposed based on the analysis above. The relationship between the microstructure and mechanical properties of Al-TiCN nanocomposites was discussed as well.
T ̇ = 250d−2
(1)
2.2. Microstructural characterization The cast wedge-formed samples were ground, polished, and then etched. The etched samples were imaged using a polarized light optical microscope. The grain sizes were measured using the linear intercept method. The JEOL JSM-7600F FEG-SEM coupled with energy disperse X-ray spectra (EDX) was used to analyze the microstructure and the distribution of nanoparticles. The ion-beammilled TEM foils prepared using a Gatan Precision Ion Polishing System (PIPS, Gatan 691) were examined in a JEOL 2100 TEM at 200 kV. HRTEM analysis was performed using a JEOL 2100F FEGTEM at 300 kV. The TEM samples for the observation of the interfacial structures between α-Al and TiC0.5N0.5 were fabricated using a dual-beam focused ion beam (FIB, Helios Nanolab, FEI). 2.3. Mechanical characterization Nanoindentation tests were performed in load control mode on a Hysitron TI 950 TriboIndenter nanoindenter at a constant loading rate of 200 μN/s up to a maximum load of 50 mN with a Berkovich threesided pyramidal diamond indenter (nominal angle of 65.3° and tip curvature radius of 100 nm). The in-situ scanning probe microscopy (SPM) equipped on TI 950 can offer an in-situ scanning at high magnification mode for microstructure identification before and after each nanoindentation test. The indentations were carried out on the longitudinal sections of the sample, i.e. onto the transverse plane, at a load of 10 mN with the loading and unloading cycle of 30 s each. Tensile tests were performed at ambient temperature on an INSTRON-5689 universal testing machine. Tensile properties measured included ultimate tensile strength (UTS), the 0.2% offset yield strength (YS) and percent elongation or strain to fracture (El.%). Tensile tests were conducted three times for each specimen and an average of three readings was reported. The sampling locations and dimensions of tensile specimens are shown in Supplementary.
2. Experimental material and procedures 2.1. Sample preparation The commercial-purity (CP) Al was used as matrix material. TiC0.5N0.5 nanoparticles with an average diameter of ~80 nm were selected as reinforcements because TiCN is a solid solution for FCC TiN and FCC TiC, possessing the features from both sides such as the high thermal and chemical stability, strong oxidation resistance and desirable compatibility with the aluminum matrix [31,32]. The synthesis of Al-TiCN nanocomposites was conducted first by ultrasonic dispersion and then by fast cooling processing. The pure aluminum was melted in an alumina crucible using an electric resistance furnace. To prepare the nanocomposites, 0, 0.5, 1.0, 1.5, and 2.0 vol.% TiCN nanoparticles were wrapped with thin foils and incorporated into the melt. The ultrasonic treatment system that consists of a transducer, booster and sonotrode, shown schematically in Ref. [29], was employed to disperse TiCN nanoparticles. The ultrasonic treatment was carried out at 993 K for 20 min in an inert atmosphere of argon gas. After dispersing the nanoparticles, the ultrasonic probe was lifted out of the melt, and then the melt was heated to 1013 K for pouring. The melt was cast into a cylindrical permanent mold (25 mm in diameter and 150 mm in height) preheated to 623 K. To achieve solidification at a low cooling rate, the melt in the alumina crucible was allowed to cool in the air. The average cooling rates for the two cases were estimated to be 6 K/s and 1.5 K/s,
3. Results 3.1. Microstructural evolution The anodized micrographs obtained from four locations of the wedge samples with and without NP addition are displayed in Fig. 1(a)–(d) and (g)–(j), which correspond to the cooling rates of 12, 21, 34 and 71 K/s, respectively. The as-cast microstructure of CP Al shows columnar growth, with the coarse grains growing perpendicularly to the mold walls. As the cooling rate is increased, the α-Al grains become finer, while still maintaining the columnar structure. After addition of 2 vol.% NPs, a marked transformation from bulky columnar grain to fine equiaxed grain occurs and the equiaxed grains are more significantly refined with increasing cooling rate. The macrostructural evolution shown in Fig. 1(e) and (f) also confirms that it is the NP addition that can induce the morphological transition of α-Al grains rather than the cooling rate, even if which is increased up to 71 K/s. The grain size of the samples with various NP additions is plotted in Fig. 1(k) as a function of cooling rate. It is evident that the α-Al grain 2
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Fig. 1. Macrographs and micrographs of wedge-formed samples: (a)–(e) Matrix alloy; (f)–(j) 2 vol.%; (k) Grain diameters as functions of the cooling rates; (l) Refinement efficiency as functions of the cooling rates.
uniform microstructure, with the equiaxed grains prevailing in the matrix. Also notable is a clear decreasing trend of the GRE with the cooling rate, indicating that the NP effect may be compromised at high cooling rates.
size decreases with the increment of cooling rate and NP addition level. When the cooling rate increases from 1.5 to 71 K/s, the average grain size decreases from 1500 to 700 μm while it is further reduced to 78 μm as the NP addition level reaches up to 2.0 vol.%. Fig. 1(l) exhibits the variation of grain refinement efficiency (GRE = (dCP Al − dNP)/dCP Al) with the cooling rate at different NP addition levels. As shown in Fig. 1(l), the GRE increases notably with the NP addition level, but decreases linearly with the cooling rate. The 2.0 vol.% NP addition combined with the cooling rate of 1.5 K/s can give the maximum GRE of 91% in this study. The results above suggest that the NP addition has a more pronounced influence on the α-Al grain refinement than the cooling rate. Even though a high cooling rate can promote the grain refinement of CP Al by providing a large undercooling, the coarse columnar grains still develop predominantly during solidification due to the lack of potent nucleants. Conversely, the Al-TiCN nanocomposite exhibits a fine and
3.2. Nanoparticle distribution To investigate the effects of cooling rate on the NP distribution, the wedge sample with 2.0 vol.% NP addition are redivided into three zones, i.e. Zone I (10 K/s ≤ T ̇ ≤ 20 K/s), Zone II (20 K/s ≤ T ̇ ≤ 40 K/s) and Zone III (40 K/s ≤ T ̇ ≤ 111 K/s). Fig. 2 illustrates three sets of SEM micrographs revealing the different distribution patterns of NPs. In Zone I, a large quantity of NPs, whose average size is less than 100 nm, are distributed along the grain boundary. The adsorption of NPs onto the grain boundary can form a NP layer by which the grain growth is restricted. In Zone II, a majority of NPs are located at the grain 3
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Fig. 2. SEM micrographs of the wedge-formed sample with 2.0 vol.% NP addition: (a)–(c) Zone I; (d)–(f) Zone II; (g)–(i) Zone III.
boundary while a small amount of NPs is dispersed in the interior of αAl grain. These NPs exist in the form of either discrete NPs or large NPclusters with the size of a few hundred nanometers. The NP accumulation at grain boundaries can still lead to the grain growth restriction. In stark contrast to Zone I and II, NPs are hardly observed at the grain boundary in Zone III; instead, they are distributed uniformly inside the grain. Overall, it can be concluded from Fig. 2 that as the cooling rate is increased, the pattern of NP distribution varies from the intergranular distribution in Zone I, to the intergranular-intragranular mixture distribution in Zone II, and eventually to the intragranular distribution in Zone III.
interplanar spacings of (1 1 1) are 0.2475 and 0.2338 nm, respectively. From Fig. 3(d), it is clearly visible that there is no crystallographic orientation relationship between the intergranular NP and the matrix, meaning that the NP has an incoherent interface with the α-Al. With the increment of cooling rate, an increasing number of NPs are dispersed inside the grain. Compared with the intergranular NPs, which are randomly orientated to the advancing solid, the intragranular ones are more likely to possess a specific orientation relationship with the solid though some of them may still have incoherent interfaces with the matrix if they expose to the Al melt certain planes that have a large interplanar misfit with the Al matrix. As shown in Fig. 3(e), the NPmatrix interface is smooth and taintless, where no intermediate phase is observed. More significantly, the TiC0.5N0.5 nanoparticle is perfectly coherent with the Al matrix, and a parallel orientation relationship between TiCN and Al can be obtained as (11¯1)Al [1¯12 ]Al//(1¯11¯)NP [1¯12 ]NP. The atomically smooth and coherent interface can give high interfacial bonding strength between the TiCN nanoparticle and the Al matrix, thus improving the load transfer efficiency. On the other hand, the well-defined OR is applicable to the determination of the lattice misfit between Al and TiCN. The estimated lattice misfit is determined to be around 5.85%, verifying the high potency of TiCN as heterogeneous nucleation site for Al. At low cooling rates, the NPs that are distributed intergranularly throughout the matrix can form a NP layer to restrict the grain growth physically. Also, because the melt undercooling is small, a large proportion of NPs may never reach the free-growth undercooling at which they would become
3.3. TEM analysis Fig. 3 presents the TEM analysis of the TiC0.5N0.5 nanoparticles distributed in different zones of the wedge sample with 2.0 vol.% NP addition. Fig. 3(a) exhibits the assembly of NPs onto the grain boundary in Zone I, which is typical of the intergranular distribution. Fig. 3(b) shows that in addition to the grain boundary, the NPs in Zone II are distributed inside the α-Al grain, i.e. the intergranular-intragranular mixture distribution. Fig. 3(c) displays the NPs located in the interior of α-Al grain in Zone III, i.e. intragranular distribution. Fig. 3(d) and (e) are the HRTEM images highlighting the interfaces between the Al matrix and the nanoparticles at the grain boundary in Zone I and inside the grain in Zone III, respectively. The crystallographic information provided in Fig. 3(f)–(i) is consistent with TiC0.5N0.5 and α-Al, whose 4
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Fig. 3. (a)–(c) TEM bright-field images showing the different NP distribution in the three zones; (d) and (e) HRTEM images of the NP/Al interfaces; (f) and (h) Fast Fourier transformation (FFT) of NP and Al, respectively; (g) and (i) Inverse Fourier transformation (IFFT) of NP and Al, respectively.
3.4. Nanoindentation test
active [30]. For this reason, the grain refinement in Zone I is mainly attributed to NP-induced growth restriction. As the cooling rate is increased, an increasing number of NPs are captured by SF and the NP layer can hardly be formed. At high cooling rates, the undercooling in the liquid is high enough for NP activation that NPs can promote the heterogeneous nucleation of α-Al. Thus, the NP-induced growth restriction would take a back seat to NP-induced heterogeneous nucleation for the grain refinement that occurs in Zone III. Note that according to classic nucleation theory, there is only one nucleation site for an individual grain. Therefore, only a limited fraction of NPs are involved in the nucleation events, in spite of the NPs distributed intragranularly throughout the matrix in Zone III.
The nanoindentation test results obtained from Zone I to III in the 2.0 vol.% Al-TiCN wedge sample are illustrated in Fig. 4. Given the wedge sample with the same alloy composition and NP addition level, the cooling rate may be taken as the sole factor in determining the mechanical property evolution of the nanocomposite. It is manifest from Fig. 4(a) that the nanoindentation hardness (H) is increased from 0.48 GPa to 0.98 GPa with increasing the cooling rate from 11 to 85 K/s. The inset in Fig. 4(a) shows the load-displacement curves during cycles of loading and unloading for the three typical zones of the nanocomposite as a function of cooling rate. There is an evident trend that
5
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Fig. 4. (a) Nanoindentation hardness measurement in the three zones of the wedge-formed sample with 2.0 vol.% NP addition. The inset is the load-displacement curves for the typical three zones of the wedge-formed sample; (b) Modulus measurement in the three zones of the wedge-formed sample; (c) Engineering stress-strain curves of CP Al and nanocomposites; (d) Comparison of the tensile strength and elongation of the nanocomposites with previously reported materials.
which in turn leads to the enhanced grain boundary strengthening and resistance to crack propagation, thus facilitating improvement in strength and ductility. Another reason for the high hardness and strength of the nanocomposite produced at high cooling rates is attributed to the interfacial bonding strength between the NPs and the matrix. During plastic deformation, a strong bonding coherence can improve the ability for load transfer from the matrix to TiCN nanoparticles leading to a more efficient strengthening of the nanocomposite [41].
the indenter penetration depth decreases with increasing cooling rate, implying that the nanocomposite solidified at high cooling rates can exhibit the enhanced resistance to indentation. The dependence of nanocomposite modulus on cooling rate is plotted in Fig. 4(b). The nanocomposite modulus increases almost monotonically with the cooling rate. As the cooling rate ranges from 11 to 85 K/s, the average elastic modulus of the nanocomposite is increased from 67.4 to 81.9 GPa. The engineering stress-strain curves of the CP Al and Al-TiCN nanocomposites are shown in Fig. 4(c). It is obvious that at the same NP addition level, both the tensile strength and ductility of the nanocomposite increase significantly with the cooling rate. When the average cooling rate reaches 60 K/s, the average tensile strength and elongation of the 2.0 vol.% Al-TiCN nanocomposite are improved from 60 MPa and 30% to 295 MPa and 35%, respectively. Fig. 4(d) presents the relationship between the strength and elongation of the Al-TiCN nanocomposites and the Al matrix composites reported in literature [34–39]. The present results reveal that the 2.0 vol.% Al-TiCN nanocomposite produced at high cooling rates can offer excellent mechanical properties. Based on the microstructural analysis, the TiCN nanoparticles in Zone III are uniformly dispersed in the interiors of fined grains, whereas those in Zone I are distributed along the grain boundaries. As a consequence, the rigid TiCN nanoparticles in Zone III can act as a more robust barrier to dislocation movement through the matrix and offer higher resistance to local plastic deformation in comparison to those in Zone I, triggering enhanced hardness and strength [40]. Moreover, a refined grain size will induce an increased number of grain boundaries,
4. Discussion 4.1. Solidification mechanism During the undercooled liquid solidification of Al-TiCN nanocomposite, the NPs are initially assumed to be homogeneously distributed in the liquid, and the SF is considered flat behind a nanoparticle. As the SF is advancing, the NPs with a lower thermal conductivity than the liquid may stifle the latent heat release from the SF and thereby have a higher temperature than the surrounding liquid, inducing a locally distorted temperature field in the vicinity of the NP, as illustrated in Fig. 5(a). In the nanoparticle capture model, the van der Waals interaction potential between a nanoparticle and an advancing solid/liquid interface is given by [42] 6
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Fig. 5. (a) Schematic of the interaction between a nanoparticle and the solid-liquid interface; (b) Interrelations among undercooling, the added particle size and the velocity (the SF velocity and the critical velocity) in the three-dimensional coordinate system; (c) NP behaviour map.
Wvdw = −
A⎛R R D ⎞ + + ln 6 ⎝D 2R + D 2R + D ⎠
η=
(2)
AAl (liquid) )( ATiCN −
AAl (liquid) )
(3)
where Asys is the system Hamaker constant, R is the TiCN nanoparticle radius, and D is the nanoparticle/interface separation. Assuming D < < R, Eq. (2) reduces to
Wvdw = −
FD + FR = 0
(4)
Vcr =
Given that AAl(liquid) < AAl(solid), and ATiCN < AAl(liquid), Wvdw > 0. As a consequence, TiCN NPs are subjected to the repulsive van der Waals forces (FR) exerted by the SF, which can be determined by
FR = −
Asys R dWvdw =− dD 6D 2
R2 D
Asys (Dcr − 2D0 ) 36πRηb Dcr2
(9)
For crystal growth into a highly undercooled alloy melt, as obtained in fast cooling processing, an equiaxed grain structure develops and the dendrite growth kinetics can be described by Lipton-Kurz-Trivedi (LKT) model, in which the SF velocity Vt is given by [46]
(5)
Vt = μΔT n
The other force acting on a TiCN nanoparticle in Fig. 5(a) is the attractive viscous drag force (FD) imposed by the flow in the particle/ interface separation, which can be calculated by [44]
FD = 6πην
(8)
Substituting Eqs. (5)–(7) into Eq. (8) and rearranging gives the critical velocity Vcr as
Asys R 6D
(7)
where ηb is the bulk liquid viscosity, v is the interface velocity, and D0 is the atomic diameter of liquid metal. When the SF reaches a critical distance Dcr, the force equilibrium is established as
and for the Al-TiCN system [43]
Asys ≈ ( AAl (solid) −
D η D − D0 b
(10)
where μ and n are constants, independent on the undercooling, and ΔT is the melt undercooling. The predicted critical velocities combined with the calculated SF velocities are presented in Fig. 5(b), and the parameters used are listed in Table 1. There are two curved surfaces in Fig. 5(b) – one representing the critical velocity Vcr versus the nanoparticle radius R and the other
(6)
Here η is given by [45] 7
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the Burgers vector, dNP is the mean NP size and VNP is the volume fraction of NPs. In this work, M = 3, G = 27 GPa, b = 0.286 nm, dNP = 80 nm and VNP = 0.02. The contribution from Orowan strengthening is estimated to be 98 MPa.
Table 1 Parameters used for the calculation of critical velocity and SF velocity. Parameter
Units
Value −2
ηb AAl(liquid) AAl(solid) ATiCN Dcr D0 μ n
NSm zJ zJ zJ nm nm – –
0.85 × 10 266 333 157 0.58 0.3 4 × 10−8 0.4
Reference −3
[47] [48] [49] [50] [20] [20] [51] [51]
4.2.3. Coefficient of thermal expansion (CTE) mismatch strengthening The mismatch between the thermal expansion coefficient of the matrix and nanoparticles can produce geometrically necessary dislocations around nanoparticles to accommodate the CTE difference, which in turn leads to an enhancement in yield strength of MMNCs. The CTE mismatch contribution can be determined by [55]
ΔσCTE =
the SF velocity Vt versus the undercooling ΔT, the intersecting line of which (the blue line) consists of all the critical points satisfying the critical criterion that for the given ΔT and R, Vcr = Vt. The projection onto the R-ΔT plane of the intersecting line is plotted in Fig. 5(c), which is divided into two regions by the projection line (the red line), i.e. Region I and II. For any given R and ΔT in Region I, Vcr > Vt, and NPs are pushed, similarly to those in Zone I of the wedge sample, where NPs exhibit intergranular distribution. On the contrary, for any given R and ΔT in Region II, Vcr < Vt, and NPs are captured, in which case NPs are expected to manifest intragranular distribution that is identical to the NP distribution in Zone III of the wedge sample. Accordingly, it is theorized that the NP size and cooling rate are the two prominent factors determining the NP distribution during solidification of MMNCs. In validating the accuracy of the theoretical model, it is pivotal to make a quantitative comparison between theoretical predictions and experimental results. As discussed in 3.2, the pattern of particle distribution varies with the cooling rate. In this work, the average radius of added NPs is 40 nm, and the corresponding critical undercooling is approximately 39 K. For NPs in Zone I, ΔT is estimated to be much less than 39 K, and thus NPs are in all probability pushed. On the other hand, for NPs in Zone III, ΔT may reach or even exceed 39 K, especially when the cooling rate is increased up to 111 K/s, meaning that NPs are highly likely to be captured. The model prediction agrees well with experimental observations.
ρCTE =
To predict the strength of Al-TiCN nanocomposites, in determining the NP contribution on strength improvement, a generalized model [40] was introduced by taking into consideration grain refinement strengthening (ΔσHP ), Orowan strengthening (ΔσOrowan ) and coefficient of thermal expansion (CTE) mismatch strengthening (ΔσCTE ).
(ΔσOrowan )2 + (ΔσCTE )2
(11)
4.2.1. Grain refinement strengthening A well-established Hall-Petch relationship [52] can be used to evaluate the increased yield strength due to grain refinement:
ΔσHP = kd−1/2
(12)
(14a)
The uniform dispersion of 2.0 vol.% TiCN nanoparticles has been achieved in CP aluminum through a combination of ultrasonic dispersion and fast cooling processing. The intragranular distribution of NPs obtained by tuning cooling rates can yield about 391% and 18% enhancement in tensile strength and ductility, respectively, compared to that of CP Al. The matrix structure over a large cooling rate range consists of fine equiaxed α-Al grains, whose size decreases with increasing cooling rate. The NP distribution in the matrix also varies with the cooling rate: an increase of the cooling rate from 10 to 111 K/s can result in the variation of NP distribution from intergranular to intragranular at micro scale and the transition of NP-matrix interface from incoherent to coherent at nano scale. A numerical model was
4.2.2. Orowan strengthening The strengthening contribution from the interactions between moving dislocations and NPs in the matrix can be described by the Orowan strengthening mechanism, which is given by [54]
MGb 6VNP 1/3 ⎛ ⎞ dNP ⎝ π ⎠
12VNP Δα ΔT (1 − VNP ) bdNP
5. Conclusions
where k is a constant and d is the average grain size. For the 2.0 vol.% Al-TiCN nanocomposite produced at 60 K/s, k is 0.326 MPa m1/2 [53] and d is 82 μm. Therefore, the ΔσHB has shown an increment of 36 MPa in yield strength.
ΔσOrowan =
(14)
where β is the dislocation strengthening coefficient, ρCTE is the dislocation density induced by the CTE mismatch, Δα is the CTE difference between the matrix and the nanoparticles and ΔT is the temperature change. Considering that β = 1.25, Δα = 15.6 × 10−6 K−1 and ΔT = 310 K, the ΔσCTE is calculated to be around 120 MPa, which is much larger than other strengthening contributions. This result highlights the predominant role in strengthening the matrix of the CTE mismatch strengthening. Substituting the predicted values obtained by Eqs. (12)–(14) into Eq. (11) approximates the yield strength of 191 MPa, showing good overall agreement (within 4.4%) with the experimental value of 183 MPa. By evaluating the contribution of individual strengthening mechanism, it is plausible that the full activation of grain refinement, Orowan mechanism and CTE mismatch strengthening mechanism is highly likely to occur in Al-TiCN nanocomposites, thus greatly enhancing the overall strength. Of them, the CTE mismatch strengthening is the most dominant contributor to the increase in yield strength, followed by the Orowan mechanism. Both outperform the grain refinement. A set of TEM images in Fig. 6 illustrate the interactions between dislocations and TiCN nanoparticles in the Al-TiCN nanocomposite that had previously been deformed by 0.2%. As shown in Fig. 6(a), the dislocations circumvent the nanoparticles and leave several Orowan loops surrounding them after crossing. The dislocation in Fig. 6(b) is bypassing a nanoparticle through the Orowan mechanism and an Orowan loop is formed incipiently around it. The bowing out of the dislocation can also be observed in the matrix (Fig. 6(c) and (d)). Driven by the applied stress, the dislocation bowing is caused by the resistance force exerted by the nanoparticles which in turn depends on the NPmatrix bonding and the hardness of nanoparticles [56]. From Fig. 6, it is salient that the rigid TiCN nanoparticles can not be sheared by the gliding dislocations. The unshearable nature of the TiCN nanoparticles combined with a strong coherent Al/TiCN interface results in the high resistance to the dislocation motion and thereby the great improvement in the yield strength of Al-TiCN nanocomposites.
4.2. Strengthening mechanisms
ΔσTotal = ΔσHP +
3 βG ρCTE
(13)
where M is the Taylor factor, G is the shear modulus of the matrix, b is 8
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Fig. 6. TEM images of the nanocomposite solidified at the average cooling rate of 60 K/s after tensile deformation (0.2% strained): (a) (b) Dislocations circumvent nanoparticles and leave Orowan loops around them. (c) (d) Dislocations bow out at the NP-matrix interface.
proposed to estimate the extent to which the cooling rate can influence the behavior of NPs at the solidification front. The theoretical analysis reveals that the NP size and cooling rate are the two prominent factors determining the NP distribution during solidification of nanocomposites. Experimental work and theoretical analysis substantiate that the CTE mismatch and Orowan strengthening are the predominant contributors to the great improvement in yield strength of Al-TiCN nanocomposites.
[2]
[3]
[4]
Acknowledgement [5]
The present study was sponsored by the National Natural Science Foundation of China, People’s Republic of China (NSFC) under Grant no. 51804197.
[6]
Appendix A. Supplementary data
[7]
Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ultsonch.2019.104626.
[8]
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