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Cite this: DOI: 10.1039/c4nr05739b

Received 30th September 2014,Accepted 18th October 2014

DOI: 10.1039/c4nr05739b

www.rsc.org/nanoscale

Cu–Ni nano-alloy: mixed, core–shell or Janusnano-particle?†

Grégory Guisbiers,* Subarna Khanal, Francisco Ruiz-Zepeda,Jorge Roque de la Puente and Miguel José-Yacaman

Bimetallic nanoparticles like Cu–Ni are particularly attractive due

to their magnetic and catalytic properties; however, their pro-

perties depend strongly on the structure of the alloy i.e. mixed,

core–shell or Janus. To predict the alloy structure, this paper

investigates the size and shape effects as well as the surface segre-

gation effect on the Cu–Ni phase diagram. Phase maps have been

plotted to determine the mixing/demixing behavior of this alloy

according the particle shape. Cu–Ni nanoalloy can form a mixed

particle or a Janus one depending on the synthesis temperature.

Surface segregation is also considered and reveals a nickel surface-

enrichment. Finally, this paper provides a useful roadmap for

experimentalists.

Cu–Ni is an important alloy in nanotechnology due to its newphysical and chemical properties appearing at the nanoscaleand coming from the high surface-to-volume ratio andquantum confinement.1 Bimetallic Cu–Ni nanoparticles areused as catalysts in important chemical reactions like methanedecomposition,2 ethanol steam reforming,3 oxidation ofmethanol,4 water–gas-shift reaction.5,6 Cu-Ni nanoparticles arealso used in magnetic applications as the Cu–Ni core shellstructure exhibits ferromagnetic properties.7

There are only a few reports discussing the properties ofCu–Ni at the nanoscale and they all focused on the liquidus/solidus curves and considered either spherical or cubicshapes. Huang and Balbuena8 applied molecular dynamicssimulations using the Sutton–Chen many-body potential tocalculate the melting behavior of cubic Cu–Ni clusters (343atoms and 1000 atoms) at two different compositions(Cu0.25Ni0.75 and Cu0.5Ni0.5). Shirinyan et al.9 used a thermo-dynamical approach to calculate the entire phase diagram of aspherical nanoparticle at 60 nm. Li et al.10 studied, via mole-cular dynamics simulations using the general embedded atommethod, the melting behavior of Cu–Ni clusters (2243 atoms)

at three different compositions (Cu0.8Ni0.2, Cu0.5Ni0.5,Cu0.2Ni0.8). Then, the same group of authors Li et al.11 studiedvia the same method the liquidus/solidus curves of two Cu–Niclusters (682 and 1048 atoms). Sopousek et al.12 used theCALPHAD method to calculate the liquidus/solidus curves ofspherical randomly mixed nanoparticles of 10 and 20 nm indiameter. In the present paper, we predict the entire phasediagram for various polyhedra often met at the nanoscale(tetrahedron, cube, octahedron, decahedron, dodecahedron,rhombic dodecahedron, truncated octahedron, cubocta-hedron, and icosahedron)13 at sizes equal to 4 nm and 10 nm.Furthermore, we also study the surface segregation effect asfunction of temperature.

A standard way to predict the solid solubility of two metalsis using the empirical Hume-Rothery rules.14,15 These rulessuggest that the alloy is formed if the crystal structure, atomicradii, valence and electronegativity of the elements are similar.The Cu–Ni alloy completely fulfills all the Hume-Rothery rulesand forms a substitutional solid solution. Indeed, both metalshave the same crystal structure (fcc), same valence (+1), similaratomic radii (size mismatch ∼2%), and similar electronegativ-ity (difference ∼2%). The complete miscibility and the absenceof maxima/minima in the liquidus/solidus curves (Fig. 1)suggest that the Cu–Ni alloy could be described as an idealsolution system. However, there exists a miscibility gap at lowtemperature (∼630 K)1,16 attributed to the positive values ofthe mixing enthalpies in the liquid and solid states.17,18 There-fore, to consider the chemical interactions between Cu and Niin both the liquid and the solid phases, we use the regularsolution model (i.e. a quasi-chemical model), where thesolidus-liquidus curves are given by:19

RT lnxsolidusxliquidus

� �¼ ΔHA

m 1� TTAm

� �þΩl 1� xliquidus

� �2�Ωs 1� xsolidusð Þ2

RT ln1� xsolidus1� xliquidus

� �¼ ΔHB

m 1� TTBm

� �þΩlxliquidus2 �Ωsxsolidus2

8>><>>:

ð1Þ

where R is the characteristic gas constant. xsolidus (xliquidus) isthe composition of the solid (liquid) phase at given tempera-

†Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr05739b

Department of Physics & Astronomy, University of Texas at San Antonio, One UTSA

Circle, San Antonio, Texas 78249, USA. E-mail: gregory.guisbiers@physics.org

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ture T. TAm and TBm are the size-dependent melting temperatureof nickel and copper respectively. ΔHA

m and ΔHBm are the size-

dependent melting enthalpy of nickel and copper respectively.Ωl and Ωs are the size-dependent interactions parameters inthe liquid and solid phases respectively. The interaction para-meters are related to the mixing enthalpies by the followingrelationship, ΔHmix,s(l) = xCuxNiΩs(l). If the interactions para-meters, Ωl and Ωs are set to zero, we retrieve the equationsdescribing the liquidus/solidus curves of an ideal solution.From Fig. 1, it is clear that the experimental data points20 ofCu–Ni alloy are well described by the regular solution model.Furthermore, the deviations from the ideality in the twophases are relatively small and of comparable magnitude.

To calculate the nano-phase diagram, the size-dependentproperties and parameters have to be first evaluated. The size-dependent melting temperature, melting enthalpy and inter-actions parameters are calculated by using the same relation-ship (eqn (2)),21 this is justified by quantum physicsconsiderations19,21–23 where all thermodynamic quantities areapproximately a linear function of 1/D (D denotes the lengthedge of the polyhedron) that corresponds to the surface-to-volume ratio of the nanoparticle.

Φ

Φ1¼ 1� α

Dð2Þ

Let us note the nano-scaled property/parameter as Φ andthe corresponding bulk property/parameter as Φ∞. The shape-dependent parameter, α, is defined as α = [Nsurf/(NtotX(hkl)a)]-(γs − γl)/ΔHm,∞ where X(hkl) is a numerical constant equal to1/2,

ffiffiffi2

p=4,

ffiffiffi3

p=3 for a 100, 110 and 111 face; Nsurf/Ntot is the

ratio between the surface atoms number to the total atomsnumber; γl and γs are the surface energies in the liquid and

solid state respectively; a is the bulk lattice parameter. In afirst approximation, the surface energies and the lattice par-ameter are considered size-independent. This is justified bythe fact that we restrict our discussion to size above 4 nmwhere these corrections are negligible. Explicitly, the latticeparameter is reduced by ∼1% for size around 4 nm22 andsurface energy is reduced by ∼10% for size around 4 nm.23

Generally, the solid surface energy is not well determined incontrast to the liquid surface energy which is quite accuratelyaccessible experimentally.24 Moreover, this is the differencebetween surface energies which is involved in the definition ofα, meaning that in the case of nickel (copper) if we consider a10% size effect on the surface energies, the difference, γs, (111)− γl, decreases by about ∼3% (∼6%) compared to the bulkcase, and can therefore be considered as a second order correc-tion (Table 1).

Introducing the size-dependent properties, TAm, TBm, ΔHAm,

ΔHBm, and parameters, Ωl, Ωs, calculated at a given size (4 nm

and 10 nm) by eqn (2), into the set of eqn (1), we can predictthe phase diagram of Cu–Ni at the nanoscale (Fig. 2). All thephase diagrams at 4 nm and 10 nm show that the liquidregion is enlarged and the solid solution area is narrowed.Above the liquidus curve, this is a one-phase field where thesolution is purely liquid. In the lens-shape region, this is a two-phase field where the liquid is at equilibrium with the solidphase. Below the solidus curve, this is a one-phase field wherethe solution is purely solid. Within the solid solution, the misci-bility gap is also reduced when size is decreased due to a lowervalue for the size-dependent interactions parameters. This is anillustration of the degradation of the regular solution into anideal solution when size decreases. This phenomenon hasalready been noticed by Jiang et al.19

From the miscibility gap, we define the miscibility tempera-ture as the critical temperature below which both constituentsare no more miscible. As can be seen from Fig. 2, the miscibil-ity temperature is size and shape dependent. Plotting the mis-cibility temperature for each polyhedron as a function of the

Fig. 1 Binary phase diagram (temperature versus composition) of bulkCu–Ni alloy. The diagram consists of two single-phase fields separatedby a two-phase field with a miscibility gap at low temperatures. Theexperimental points come from ref. 20.

Table 1 Material properties used to calculate the phase diagrams at thenanoscale

Material properties Ni Cu

Crystal structure33 fcc fccTm, ∞ (K)33 1728 1357ΔHm, ∞ (J mol−1)33 17 480 13 263γl (J m

−2)33 1.725 1.300γs, 111 (J m

−2)34 2.011 1.952γs, 100 (J m

−2)34 2.426 2.166γs, 101 (J m

−2)34 2.368 2.237Ωl (J mol−1)35 12 219Ωs (J mol−1)35 11 376Atomic radii (pm)33 115 117Electronic affinity (eV)33 1.16 1.241st ionization energy (eV)33 7.64 7.73χ, Mulliken electronegativitya (eV) 4.40 4.49ΔHv, ∞, molar heat of vaporization (J mol−1)33 369 240 300 700

a The Mulliken electronegativity is defined as the mean value betweenthe electronic affinity and the first ionization energy.

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number of faces gives access to a phase map indicatingthe mixing–demixing behavior of the Cu–Ni (Fig. 3). Above themiscibility temperature, the alloy is formed while below thistemperature the Janus particle is formed. These phase maps,

plotted at sizes equal to 4 nm and 10 nm, are very informativefor experimentalists who can adjust their synthesis tempera-ture or adjust the heating treatment after the synthesis, accord-ing the type of nanoparticle they want to produce. Cu–Ni

Fig. 3 Mixing–demixing phase map for nanoparticles having a side edge length equal to (a) 4 nm and (b) 10 nm. These phase maps represent themiscibility temperature versus the number of facets of each polyhedron considered in this study. The squares represent the experimental data i.e. thesynthesized nanoparticles shown in Fig. 5. The temperature used to synthesize these Cu–Ni nanoparticles was 250 K as indicated by the red arrow.

Fig. 2 Binary phase diagrams of Cu–Ni alloys for different shapes: (a) tetrahedron, (b) cube, (c) octahedron, (d) decahedron, (e) dodecahedron, (f )truncated octahedron, (g) cuboctahedron, (h) icosahedron, (i) rhombic dodecahedron.

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nanoalloy is very difficult to synthesize at room temperatureand generally requires a heat treatment.7,25–28 For the tetra-hedron having a side edge length ∼4 nm (Fig. 2), the miscibil-ity gap disappears completely meaning that there is no phaseseparation in the solid solution. In the case of a bimetallicalloy, it is interesting to consider the surface segregation.Indeed, due to a higher surface-to-volume ratio,29 diffusion isenhanced in nano-alloys compared to bulk alloys leading to apossible core–shell formation. Diffusion of atoms from thebulk to the surface is attributable to the gradient of the chemi-cal potential between the bulk and the surface.30 The solidusand liquidus compositions of the alloy can then be deter-mined at the surface by using the William–Nason’s model:31

xsurfacesolidus ¼xcoresolidus

1� xcoresoliduse�

ΔHsubz1vz1kT

1þ xcoresolidus

1� xcoresoliduse�

ΔHsubz1vz1kT

ð3Þ

xsurfaceliquidus ¼

xcoreliquidus

1� xcoreliquiduse�

ΔHvapz1vz1kT

1þ xcoreliquidus

1� xcoreliquiduse�

ΔHvapz1vz1kT

ð4Þ

where xcoresolidus and xcoreliquidus are the bulk solidus and liquiduscomposition given by the set of eqn (1) i.e. when segregation isnot considered. ΔHvap = |ΔHv, A − ΔHv, B| is the absolute differ-ence in the enthalpy of vaporization of the two pure elements.ΔHsub = |ΔHs, A − ΔHs, B| is the absolute difference in theenthalpy of sublimation of the two pure elements. z1v/zv isthe fraction of nearest neighbor atoms missing for atoms inthe first layer (for atoms belonging to a 111 face in a fcc struc-ture, z1v/zv = 0.25). Considering surface segregation on thesolidus/liquidus curves, it is clear from Fig. 4 that nickel is pre-ferentially found at the surface of the nanoalloy (Table 1).

Experimentally, we have synthesized Cu–Ni nanoparticlesusing wet chemistry methods at 250 °C (see ESI† for details)and characterized by transmission electron microscopy (TEM)in STEM mode. This has been carried out on a JEOL ARM200Fprobe aberration corrected electron microscope operating at200 kV. The samples for TEM observations were prepared bydropping the colloidal solution onto gold TEM grids anddrying in air. STEM images were recorded by High AngleAnnular Dark Field (HAADF) (Fig. 5a and b). The Z-contrastimages whose signal intensity depends on the atomicnumber,32 show that copper atoms appear brighter than nickelones, evidencing an alloyed and a Janus particle structure onFig. 5a and 5b, respectively. The elemental distribution of Cuand Ni inside the alloy was analyzed by Energy DispersiveX-ray Spectroscopy (EDX) with an EDAX Apollo XLT-2 Silicondrift detector. EDX line scan taken over the Cu–Ni nanoparti-cles is presented in Fig. 5c and d. The intensity of the copperand nickel peaks differ according the position in the particle,confirming the Janus structure of the particle. From Fig. 5, itis clear that the Cu–Ni nanoparticles synthesized at 250 °Cadopt the structure of Janus particles confirming the theore-tical predictions shown on Fig. 3. Furthermore, nickel surfacesegregation is also observed in Fig. 5b confirming then thetheoretical calculations.

Finally, using nano-thermodynamics theory, we confirmthat mixed Cu–Ni nanoparticles are difficult to synthesize atroom temperature and require a substantial heat treatment tobe produced. By adjusting the value of the synthesis tempera-ture, it is possible to control the structure of the alloy. By redu-cing the size of the nanoparticle, the miscibility gap narrowsand the mixing/demixing behavior of the Cu–Ni nanoparticlecan be predicted. It is also found that nickel preferentially seg-regates at the surface of the particle. To conclude, this papercontains the first phase map indicating the mixed or Janusstructure of Cu–Ni nanoalloy according the shape of the par-ticle. For sure, this will help the experimentalists by guiding

Fig. 4 (a) Binary phase diagram of a spherical Cu–Ni nanoparticle (diameter = 15 nm) without and with surface segregation. The solidus–liquiduscurves describing the segregated nanoparticle reveals the nickel surface enrichment. (b) STEM image of a “nearly” spherical Cu–Ni nanoparticlehaving a diameter around ∼15 nm. The red arrow indicates the scan direction. (c) EDX line scan across this particle revealing the nickel surfaceenrichment.

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them in their attempts to synthesize Cu–Ni nanoparticles withthe desired structure.

Acknowledgements

This project was supported by grants from the National Centerfor Research Resources (G12RR013646-12) and the NationalInstitute on Minority Health and Health Disparities(G12MD007591) from the National Institutes of Health. Theauthors would also like to acknowledge the NSF PREM#DMR0934218 and the Mexican Council for Science and Tech-nology, CONACYT (Mexico) through the project 207725.

References

1 R. Ferrando, J. Jellinek and R. L. Johnston, Chem. Rev.,2008, 108, 845–910.

2 T. V. Reshetenko, L. B. Avdeeva, Z. R. Ismagilov,A. L. Chuvilin and V. A. Ushakov, Appl. Catal., A, 2003, 247,51–63.

3 A. J. Vizcaíno, A. Carrero and J. A. Calles, Int. J. HydrogenEnergy, 2007, 32, 1450–1461.

4 M. Jafarian, R. B. Moghaddam, M. G. Mahjani andF. Gobal, J. Appl. Electrochem., 2006, 36, 913–918.

5 J.-H. Lin and V. V. Guliants, Appl. Catal., A, 2012, 445–446,187–194.

6 J.-H. Lin, P. Biswas, V. V. Guliants and S. Misture, Appl.Catal., A, 2010, 387, 87–94.

7 T. Yamauchi, Y. Tsukahara, T. Sakata, H. Mori, T. Yanagida,T. Kawai and Y. Wada, Nanoscale, 2010, 2, 515–523.

8 S.-P. Huang and P. B. Balbuena, J. Phys. Chem. B, 2002, 106,7225–7236.

9 A. Shirinyan, M. Wautelet and Y. Belogorodsky, J. Phys.:Condens. Matter, 2006, 18, 2537–2551.

10 G. Li, Q. Wang, D. Li, X. Lü and J. He, Mater. Chem. Phys.,2009, 114, 746–750.

11 G. Li, Q. Wang, T. Liu, K. Wang and J. He, J. Cluster Sci.,2010, 21, 45–55.

12 J. Sopousek, J. Vrestal, J. Pinkas, P. Broz, J. Bursik,A. Styskalik, D. Skoda, O. Zobac and J. Lee, CALPHAD:Comput. Coupling Phase Diagrams Thermochem., 2014, 45,33–39.

13 M. J. Yacaman, J. A. Ascencio, H. B. Liu and J. Gardea-Torresdey, J. Vac. Sci. Technol., B, 2001, 19, 1091–1103.

14 W. Hume-Rothery, G. W. Mabbott and K. M. ChannelEvans, Philos. Trans. R. Soc. London, Ser. A, 1934, 233, 1–97.

15 U. Mizutani, Hume-Rothery Rules for Structurally ComplexAlloy Phases, CRC Press, 2011.

16 K. P. Gupta, J. Phase Equilib. Diffus., 2009, 30, 651–656.

Fig. 5 STEM images of Cu–Ni nanoparticles: (a) HAADF image of three cubic nanoparticles, (b) HAADF image of a “nearly” decahedral nanoparticle.(c) EDX line scan on one of the cubic nanoparticles shown in (a), illustrating the alloy behavior of the nanoparticle. (d) EDX line scan on the “nearly”decahedral nanoparticle shown in (b), illustrating the Janus behavior of the nanoparticle. The red arrows in (a) and (b) indicate the scan direction.

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31/1

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17 J. Lee, J. Park and T. Tanaka, CALPHAD: Comput. CouplingPhase Diagrams Thermochem., 2009, 33, 377–381.

18 T. Tanaka and S. Hara, Z. Metallkd., 2001, 92, 1236–1241.

19 Q. Jiang and Z. Weng, Thermodynamics of Materials,Springer, 2011.

20 E. A. Feest and R. D. Doherty, J. Inst. Met., 1971, 99,102–103.

21 G. Guisbiers and G. Abudukelimu, J. Nanopart. Res., 2013,15, 1431.

22 W. H. Qi and M. P. Wang, J. Nanopart. Res., 2005, 7, 51–57.23 S. Y. Xiong, W. H. Qi, Y. J. Cheng, B. Y. Huang, M. P. Wang

and Y. J. Li, Phys. Chem. Chem. Phys., 2011, 13, 10648–10651.

24 G. Guisbiers, S. Arscott and R. Snyders, Appl. Phys. Lett.,2012, 101, 231606.

25 M. D. Cangiano, A. C. Carreras, M. W. Ojeda andM. D. Ruiz, J. Alloys Compd., 2008, 458, 405–409.

26 E. L. de Leon Quiroz, D. Vasquez Obregon, A. PoncePedraza, M. J. Yacaman and L. A. Garcia-Cerda, IEEE Trans.Magn., 2013, 49, 4522–4524.

27 M. D. Cangiano, M. W. Ojeda, A. C. Carreras, J. A. Gonzalezand M. D. Ruiz, Mater. Charact., 2010, 61, 1135–1146.

28 C. Damle and M. Sastry, J. Mater. Chem., 2002, 12, 1860–1864.

29 G. Guisbiers and L. Buchaillot, Nanotechnology, 2008, 19,435701.

30 H. Mehrer, Diffusion in Solids, Springer, 2007.31 F. L. Williams and D. Nason, Surf. Sci., 1974, 45, 377–408.32 S. J. Pennycook, Ultramicroscopy, 1989, 30, 58–69.33 W. Martienssen and H. Warlimont, Springer handbook of

condensed matter and materials data, Springer, 2005.34 L. Vitos, A. V. Ruban, H. L. Skriver and J. Kollar, Surf. Sci.,

1998, 411, 186–202.35 L. H. Liang, D. Liu and Q. Jiang, Nanotechnology, 2003, 14,

438–442.

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