Molecular Dynamics Simulation of the Melting Behavior of PtâAu

J. Phys. Chem. C 2008, 112, 4937-4947

4937

Molecular Dynamics Simulation of the Melting Behavior of Pt-Au Nanoparticles with Core-Shell Structure Zhen Yang, Xiaoning Yang,* and Zhijun Xu State Key Laboratory of Materials-Oriented Chemical Engineering, College of Chemistry and Chemical Engineering, Nanjing UniVersity of Technology, Nanjing 210009, China ReceiVed: December 13, 2007; In Final Form: January 20, 2008

Molecular dynamics (MD) simulations have been employed to investigate the melting behavior of coreshell Pt-Au nanoparticles with four different concentrations: Pt13Au548, Pt55Au506, Pt147Au414, and Pt309Au252. The icosahedral core-shell structures, with an icosahedral Pt core covered with an icosahedral Au shell, were taken as the initial configurations in this simulation. To compare with Pt-Au nanoparticles, the pure metals (Pt and Au) with the same particle size were also studied here. The results demonstrate that the coreshell bimetallic nanoparticles exhibit a two-stage melting, and their melting points rise as the concentration of Pt increases. A detailed analysis of the melting processes indicates that the premelting nature of the pure metal nanoparticles does not purely correspond to the surface premelting, but all atoms even including the center atom contribute to the premelting behavior through interlayer diffusion. For all the core-shell structures investigated, however, the premelting only occurs at the Au shells, and the Pt cores always keep a typical solid state before the homogeneous melting transition. Furthermore, the extent of the premelting of the Au shell is suppressed as the size of Pt core increases. The difference in the melting mechanism can be explained on the basis of the distribution of potential energy between the Pt and Au atoms in the pure metal and coreshell bimetallic nanoparticles.

1. Introduction Metal nanoparticles have extensive potential applications in catalysis, sensor, magnetic device, and optoelectronics fields.1-5 In particular, bimetallic nanoparticles exhibit superior properties in comparison with their monometallic counterparts.6-10 As for bimetallic nanoparticles, the physical and chemical properties depend largely on particle size, composition, and atomic distribution. Thus, the possible design, control, and fabrication of particle size, composition, and atomic distribution can produce various bimetallic nanoparticles with tailored properties.9-12 To exploit such an approach, the understanding of the structures and properties of bimetallic nanoparticles is very necessary. One of the most crucial properties is the melting behavior of metal nanoparticles, namely, a solid-liquid phase transition, which has a significant influence on the synthesis and processing of nanoparticles.13 On the nanometer scale, metal nanoparticles usually possess a much lower melting point than the corresponding bulk metals due to enormous surface-to-volume ratio. A common phenomenon obtained from experimental observation and theoretical calculation is that the melting point decreases with the decrease in particle size.14-17 However, the melting points of nanoparticles do not always vary monotonically with particle size. Haberland and co-workers18-21 have observed that the melting points of sodium nanoparticles show noticeable fluctuations in a size ranging from 55 to 200 atoms. Calvo and Spiegelmann22 also demonstrated that, below 75 atoms, the melting points of sodium nanoparticles exhibit strong non-monotonic variation with the particle size owing to the dominating premelting effects. Additionally, the melting point of metal nanoparticle does not * Corresponding author. E-mail: [email protected].

also remain lower than that of bulk counterpart at all times. Recent experiments have shown that the melting points of the tin23 and gallium24 nanoparticles of less than 40 atoms could be much higher than the bulk cases. At present, however, these experimental techniques, such as electron and X-ray diffraction and nanocalorimetry, are not applicable to free, mass-selected nanoparticles in vacuum, because there is no method for temperature measurement and it is also very difficult to collect a diffraction signal in such a small scale.25 Although various experimental techniques have been established to study the melting process of nanoparticles, the understanding of this problem has not been addressed satisfactorily because of the size and structure complication of nanoparticles. Computer simulation has been proven to be a convenient method to study the melting transition of metal nanoparticles, since it can not only provide adequate and accurate microscopic details, but also arbitrarily choose nanoparticles with desired sizes and structures. The study of the melting behavior of bimetallic nanoparticles has attracted increasing attention over the past decade. For example, earlier MD calculations regarding the Cu-Au bimetallic nanoparticles, consisting of 13 and 14 atoms, showed that their melting temperatures are close to that of pure copper nanoparticles with the same size.26 Huang and Balbuena27 found that the Cu-Ni particles display a two-stage melting, surface melting and homogeneous melting, both of which depend on composition and particle size. An analogous two-stage melting was also found in the event of Pd-Pt nanoparticles by a MD simulation with the quantum SuttonChen potential.28 More recently, Chen et al.29 revealed that the glass transitions dominate the thermal stability of gold-rich AuAg nanoalloys with 55 atoms. In terms of the definition of atomic distribution, the structures of bimetallic nanoparticle can be classified into the random alloy,

10.1021/jp711702y CCC: $40.75 © 2008 American Chemical Society Published on Web 02/21/2008

4938 J. Phys. Chem. C, Vol. 112, No. 13, 2008 core-shell structure, and others.6 The core-shell structures can be very important for application in catalysis due to their unusual electronic properties and favorable surface-volume ratio.30 More recently, the Pt-Au bimetallic nanoparticles, especially with the Pt-Au or the Au-Pt core-shell structures, have been preparedandcharacterizedforavarietyofcatalyticapplications.31-36 For example, the Au-Pt nanoparticle with the core-shell structure has demonstrated enhanced specific activity in methanol electrooxidation at room temperature as compared with the conventional platinum catalyst.36 Unlike bulk materials, nanoparticles can exhibit various structural motifs, which include hexagonal close-packed (hcp), cuboctahedral, icosahedral, truncated decahedral, and amorphous structures.37 For small nanoparticles, the icosahedral structure is more stable because it optimizes the surface energy.38,39 Nam et al.37 have explained why the icosahedral structure is dominantly formed in nanometer scale by using MD simulation. Koga and Sugawara40 have recently analyzed a large sample of free Au particles, with diameters of 3-18 nm, obtained in an inert-gas aggregation source and found that the icosahedral structure is the most frequent. In this work, we mainly focus on the melting transition of Pt-Au bimetallic nanoparticles with icosahedral structure and core-shell arrangement. The nanoaprticles investigated possess the magic sizes (561 atoms), which usually present special structural, electronic, and thermodynamic properties.41 In general, most of the simulated nanoparticles with core-shell structures and magic number sizes in the previous reports adopt the initial configuration obtained from the substitution of a single impurity atom in the pure metal nanoparticles. Aguado et al.42 found that doping of Na55 with a single Li atom at the center site can significantly decrease the melting point by using the orbital-free MD simulation. On the contrary, Mottet et al.39 have reported that the substitution of a single Ni or Cu atom in Ag icosahedral nanoparticles consisting of 55 atoms can lead to a considerable increase in the melting point. Furthermore, noticeable effects are still discovered even for lager icosahedral particles with magic numbers of 147, 309, and 561 atoms, respectively.39 Recent Monte Carlo simulations by Cheng et al.43 also revealed that the melting point of Cu1Au54 with core-shell structure is much higher than that of Au55. From the previous results, introducing a single impurity atom into the center of the nanoparticle can result in such an obvious effect on the melting properties. Naturally, it is very interesting to evaluate the effect of introducing more impurity atoms on the melting behavior of the nanoparticles. The primary objective of this work is to demonstrate, by using the canonical MD, how the melting properties of core-shell Pt-Au bimetallic nanoparticles change with the size of the Pt core. Four different concentrations are considered: Pt13Au548, Pt55Au506, Pt147Au414, and Pt309Au252. As shown in the following section, the Pt-Au nanoparticles with such compositions can form a stable icosahedral core-shell structure, with an icosahedral core consisting of only Pt atoms and an icosahedral shell consisting of only Au atoms. For comparison, the pure Pt and pure Au nanoparticles with the same sizes are also considered in this work. The paper is organized as follows: In section 2 we present the description of potential model, initial configurations setup and simulation details. The simulated results are then shown and discussed in section 3. Finally, a few general conclusions are summarized in section 4. 2. Simulation Methods 2.1. Potential Model. The many-body Sutton-Chen (SC) potential,44 based on the long-range Finnis-Sinclair (FS) type

Yang et al. TABLE 1: Parameters of the Sutton-Chen Potential for Au and Pt Au-Au Au-Pt Pt-Pt

(10-2 eV)

a (Å)

m

n

c

1.2794 1.5930 1.9835

4.08 4.00 3.92

8 8 8

10 10 10

34.428 34.428

potentials, is employed to describe interactions between metal atoms. The SC potential can be expressed as a pairwise repulsion term plus a many-body density-dependent cohesion term.44 The latter term is used for the short-range interactions so as to provide a good description of surface relaxation phenomena, and the former term gives a better description of long-range interactions with a van der Waals tail.45 In the SC model, the total energy of an N-atom system is written as44 N

U)

[ () 1

∑i 2 ∑ j*i

a

n

rij

]

- c xFi

(1)

where the local atomic density, Fi, is given by

Fi )

∑ j*i

() a

m

rij

(2)

where rij is the separation distance between atoms i and j, c is a positive dimensionless parameter, is a parameter with the dimensions of energy, a is the lattice constant, and m and n are positive integers (n > m). These parameters were obtained by fitting the experimental cohesive energy and lattice parameters. The SC potential reproduced well the bulk modulus and elastic constant44 and it was used to investigate thermal and mechanical properties of transition metals.46 The minimum-energy structure of transition metal nanoparticles using the SC potential have been determined by a Monte Carlo minimization method, which agrees with the experimental result.47 Rafii-Tabar and Sutton have extended the SC potential for binary metal alloys without changing pure elemental parameters.48 Generally, the geometric mean was used for the mixing energy parameter and length parameter a, and the arithmetic mean for the remaining parameters except for c,48 since the value of c depends only on the type of the atom at which the local energy density is evaluated. This mixing rule can give a reasonable description of the concentration dependencies of lattice parameters, elastic constants, and heats of formation of a set of binary alloys.48 Presently, the SC potential has been successfully applied to simulate different bimetallic nanoparticles, including Cu-Ni,27,49 Pb-Al,50 Au-Cu,51 Pt-Co,52 Au-Pd,53 and Au-Pt49 systems. In this work, the above mixing rule is used and all the SC parameters for Au-Pt bimetallic systems are listed in Table 1.48 2.2. Initial Configurations Setup. In this paper, we used a complete Mackay icosahedral structure with a magic number of atoms (N ) 561) as the initial simulated structure. For an icosahedral structure with K layers, the magic number of atoms needed to construct a perfectly symmetric icosahedron is54

N(K) )

11 10 3 K - 5K2 + K - 1 3 3

(3)

Therefore, the icosahedral nanoparticle with N ) 561 atoms consists of six layers. Four different concentrations are considered: Pt13Au548, Pt55Au506, Pt147Au414, and Pt309Au252. To compare with the core-shell structures, the pure gold Au561 and pure platinum Pt561 with the same size were also studied. The core-shell structures were generated by replacing the core

Melting Behavior of Pt-Au Nanoparticles

J. Phys. Chem. C, Vol. 112, No. 13, 2008 4939

Figure 1. Initial configurations of the core-shell Pt-Au nanoparticles, together with pure metal nanoparticles Au561 and Pt561. The Pt and Au atoms are represented by pink and yellow spheres, respectively. To better show the core-shell structures, half Au atoms were removed.

atoms with Pt atoms from the pure Au icosahedral nanoparticle. For instance, for the Pt13Au548 cluster, the two interior layers are composed of Pt atoms and other four layers consist of Au atoms. The local minimum-energy structures of core-shell PtAu nanoparticles interacting with the SC potential were determined by using a low storage BFGS (Broyden-FletcherGoldfarb-Shanno) nonlinear optimization.55 Note that we did not attempt to determine the global minimum-energy structure, but the structure obtained from the BFGS optimization method is at least reasonably close to the global minimum-energy structure. The xyz coordinates of the initial pure Au nanoparticles after optimization are given in Table S1 of the Supporting Information. After the energy optimization, the icosahedral core-shell structures are completely preserved and taken as the initial configurations in the following MD simulation. The obtained initial configurations of the simulated particles are shown in Figure 1. 2.3. Simulation Details. The MD simulations were carried out in the canonical ensemble (NVT) with the application of the Nose-Hoover thermostat for maintaining the constanttemperature condition, and no periodic boundary conditions were applied to ensure the simulation of isolated nanoparticles. Newton’s equations of motion were integrated using the velocity Verlet algorithm with a time step of 2 fs. Simulations were performed in a series of temperature conditions ranging from 100 to 1300 K in increments of 50 K. In consideration of the considerable temperature fluctuations in the vicinity of the melting point, the temperature increment was then reduced to 10 K. The initial configuration at each temperature was from the final configuration of the previous temperature point. At each run, the simulation time was typically from 400 to 600 ps for equilibration, and then the next 400 ps for the production stage.

Figure 2. Variation of the potential energy per atom as a function of temperature for the core-shell Pt-Au nanoparticles, together with pure metal nanoparticles Au561 and Pt561. To enhance visual clarity, the curves of Pt55Au506, Pt147Au414, Pt309Au252, and Pt561 are shifted upward by 0.11, 0.41, 0.97, and 1.74 eV/atom, respectively. The inset shows the nonshifted version of this figure.

3. Results and Discussion The Au-Pt bimetallic nanoparticles with various sizes can be obtained experimentally within the entire composition range.56 In this work, we did not make a detailed evaluation on the thermodynamic stability for the core-shell Pt-Au nanoparticles. However, according to the calculation from Xiao et al.,57 the formation heat of Au-Pt alloys with random structure, whose sizes do not exceed 7000 atoms, are negative within entire

4940 J. Phys. Chem. C, Vol. 112, No. 13, 2008

Figure 3. Variation of the bond order parameter as a function of temperature for the core-shell Pt-Au nanoparticles, together with pure metal nanoparticles Au561 and Pt561.

concentration range. Their calculation indicates that the AuPt nanoparticles within this size range possess better thermodynamics stability to some extent. Based on our MD simulation, the mean configuration energy of the Pt-Au nanoparticles with the core-shell structure is lower than those with random structure under the same size and composition. Thus, it may suggest that the core-shell structure could be a more stable formation for Au-Pt bimetallic nanoparticles. This supposition was also confirmed in the following MD simulations, where stable Pt-Au core-shell structures can be obtained before melting points. 3.1. Melting Point Characterization. In Figure 2, we present the caloric curves of the core-shell Pt-Au nanoparticles.

Yang et al. Meanwhile, the results of pure Au and pure Pt nanoparticles have also been given. As seen from this figure, at the beginning of heating, the average potential energy (averaging over all atoms) almost linearly increases with temperature. Near the melting transition points, however, the caloric curves display some fluctuations in deviation from a linear increase. The melting point locates at the position where there is a sharp jump in the caloric curve, and the dependence of the melting temperature on the size of Pt core can be clearly noted from the caloric curves; that is, the melting points of the nanoparticles increase with the concentration of Pt. Similar phenomena were observed for the Pd-Pt28 and Au-Pd53 nanoparticles, with the exception of the Au-Cu case,51 where no correlation between the melting point and the alloy composition has been examined. For the case of Au561, the average potential energy per atom is about -3.58 eV/atom at 300 K and the melting point is approximately 660 K. This result is consistent with the previous simulation report of Au nanoparticles53 using the same particle size and interaction potential, though the simulated structure of Au561 is cuboctahedron. It is worth mentioning that, for the Pt309Au252 nanoparticle, the magnitude of jumping step in the caloric curve is the highest, corresponding to the largest latent heat of fusion as compared with the other nanoparticles. Apart from the caloric curve, the bond order parameter58 was also applied to characterize the melting point in this work. The general idea of the bond order parameter is to capture the symmetry of bond orientations regardless of the bond length. A bond is defined as the vector joining a pair of neighboring atoms within a given cutoff radius. The local order parameter associated with a bond r is specified by the spherical harmonics functions58

Qlm(r) ) Ylm(θ(r),φ(r))

(4)

where θ(r) and φ(r) are the polar and azimuthal angles of the

Figure 4. Variation of the Lindemann index of each layer as a function of temperature for the core-shell Pt-Au nanoparticles with different concentrations: (a) Pt13Au548, (b) Pt55Au506, (c) Pt147Au414, and (d) Pt309Au252. In each panel, the red lines are for the Pt-core atoms and the blue lines for the Au-shell atoms.



bond r with respect to this reference system. Only even-l spherical harmonics Qlm(r) are considered here so that the bond parameters are invariant under inversion. The global bond order parameter can then be calculated by averaging Qlm(r) over all bonds in the system

Qlm )

1

∑ Qlm(r)

(5)

Nbbonds

where Nb is the number of bonds. To make the order parameters invariant with regard to rotations of the reference system, the second-order invariants are defined as

Ql )

(

4π

l

∑

2l + 1 m)-l

| |)

1/2

Qlm

2

(6)

Therefore, the bond order parameter is not only a sensitive indicator of the melting transition, but also a measure to identify the structure change of nanoparticles during heating process. Because of symmetry reason, the first nonzero value occurs at l ) 6 for the icosahedral structure, which is only used in this work. Moreover, the value of Q6 for icosahedral structure depends on particle size, since this structure is not periodic. For a perfect 561-atom icosahedral particle, the value of Q6 is 0.167. It should be emphasized that the surface bonds are included in the calculation of Q6, because the magnitude of Q6 can be affected by including the surface bonds in the average. The melting point can be clearly identified by a sharp drop toward zero in the curve of bond order parameter (see Figure 3). These resulting melting points here coincide with the results from the caloric curve. Identical results can be also obtained from the characterizations of heat capacity and Lindemann index, as shown in Figures S1 and S2 of the Supporting Information. At low temperatures, the values of all bond order parameters are found to be about 0.16, which is very close to the value of perfect icosahedron (0.167). It means that all particles keep a well-defined icosahedral structure at the beginning of the heating process. After the homogeneous melting occurs, the related values of the bond order parameter should decay to zero. However, in Figure 3, the resulting values are about 0.05 in the liquid state. This is caused by a finite size of the simulated nanoparticles.28,59,60 Just before the homogeneous melting transition, there exists a stage of nonlinear variation of the bond order parameters with temperature for each Q6 curve, which may imply that the nanoparticles exhibit a two-stage melting behavior: premelting and homogeneous melting. For example, the premelting range of the Au561 particle is about from 350 to 650 K. The melting behavior is very different from the bulk phases which only show the first-order melting transition. Similar temperature ranges of melting have been found in the silver and nitromethane nanoparticles.61,62 As shown in Figure 3, one can observe that the nanoparticle Pt561 has a longer premelting process than Au561. In contrast to pure metal nanoparticles (Pt561 and Au561), nevertheless, the temperature range of the premelting process of all core-shell structures becomes shorter as the concentration of Pt increases. Thus, this means that the premelting behavior is suppressed with the concentration of Pt. Especially, the particle Pt309Au252 undergoes homogeneous melting, almost without a separated premelting stage. The premelting behavior in this work is different from the result from Mejia-Rosales et al.,53 who found that the increasing concentration of Pd in the Au-Pd alloy nanoparticles leads to an extended premelting process. This difference could be attributed to the different

Figure 5. Same as in Figure 4 but for the pure metal nanoparticles: (a) Au561 and (b) Pt561.

melting mechanisms between the core-shell and alloy nanoparticles. It is interesting to explore the dependence of the thermal behavior of bimetallic nanoparticles on the atomic distribution. Accordingly, we have made a tentative comparison of the melting behavior of the Pt-Au nanoparticles between the core-shell and alloy structures. This initial examination shows that this melting feature observed in this work is mainly related to the specific core-shell structure rather than the particle size. Presently, the further thorough investigation is still in progress. 3.2. Melting Mechanism Analysis. In order to comprehensively analyze the melting mechanism of the core-shell bimetallic nanoparticles, we divided the whole particle into six layers based on the initial structure configuration in terms of eq 3. Accordingly, all 561 atoms were classified into six groups, that is, only the center atom [N(1)] in the first layer, the 12 atoms [N(2)-N(1)] in the second layer, the 42 atoms [N(3)N(2)] in the third layer, the 92 atoms [N(4)-N(3)] in the fourth layer, the 162 atoms [N(5)-N(4)] in the fifth layer, the 252 atoms [N(6)-N(5)] in the sixth layer, which is the initial surface layer. Then, the atoms in the six groups were denoted as layer(1), layer(2), layer(3), layer(4), layer(5), and layer(6), respectively. It should be noted that the atoms in the nanoparticles will not be situated at the initial positions during heating process because of thermal motion, thus, the sorting of atoms does not actually represent the atom layer in the nanoparticles with temperature increasing. However, we still used the classification of particle layer based on the initial structure in the following analysis instead of grouping the atoms at each temperature again. In this way, we could capture in detail the tracks of atom motion for a certain group during the whole simulation process, and it


Yang et al.

Figure 6. Variation of the deformation parameter of each layer as a function of the temperature for the core-shell Pt-Au nanoparticles with different concentrations: (a) Pt13Au548, (b) Pt55Au506, (c) Pt147Au414, and (d) Pt309Au252. In each panel, the red lines are for the Pt-core atoms and the blue lines for the Au-shell atoms.

is more sensitive and convenient to identify the surface isomerization and the interlayer diffusion during the heating process. The Lindemann index,63 i.e., the root-mean-square bondlength fluctuation, was used to characterize the melting transition of the metal nanoparticles. The Lindemann index of each layer δL(i) is expressed as

δL(i) )

2 NL(i)(NL(i) - 1)

∑ j 0.24), associated with the large motion freedom in the liquid state. The other core-shell Pt-Au nanoparticles display a similar behavior (see Figure 4b-d). In other words, prior to the homogeneous melting, the whole Pt core always behaves as a well-defined solid-state irrespective of the core size. Naturally, the increase of Pt concentration (Pt core size) leads to a reduction in the proportion of atoms participating in the premelting process. Thus, as shown in Figure 3, the premelting extent of the whole nanoparticle is reduced with the increase of the Pt concentration. For pure metal nanoparticles (see Figure 5), however, their premelting behavior is different from that in the core-shell nanoparticles. Up to a certain temperature, the Lindemann index of all layers shows obvious fluctuations and attains a higher value before the melting point. This observation indicates that all atom layers of the pure metal nanoparticles undergo the premelting stages to different extents before the melting transition. The deformation parameter is another effective method to explore the melting behavior of nanoparticles.27 The deformation parameter was also assigned to each layer, which is defined as NL(i)

L(i) )

|rL(i) - rcm| ∑ j j)1 NL(i)

(8)

where rL(i) is the position vector of the jth atom of the ith layer, j rcm is the position vector of the center of mass of the nanoparticle. Figure 6 gives the deformation parameter curves of each layer for the core-shell structures. It is demonstrated that the deformation parameters of the Pt layers remain


Figure 7. Same as in Figure 6 but for the pure metal nanoparticles: (a) Au561 and (b) Pt561.

unchanged before the homogeneous melting transition, indicating that the Pt atoms locate at the initial positions without interlayer diffusion. On the contrary, the interlayer diffusion

J. Phys. Chem. C, Vol. 112, No. 13, 2008 4943 behavior is observed for the Au atoms. In the case of Pt13Au548 (see Figure 6a), at about 600 K, the deformation parameter of the outermost layer(6) starts to decline, whereas that of the layer(5) starts to increase, which is an indicator of the inward diffusion of atoms in the sixth layer and the outward diffusion of atoms in the fifth layer. At higher temperatures of 650 and 670 K, the atoms on the fourth and the third layers begin with outward diffusion in turn. Note that, in Figure 4a, the premelting phenomenon of the outermost layer(6) starts at 500 K, which is lower than the beginning temperature of interdiffusion (see Figure 6a). Then, over the temperature range from 500 to 600 K, the premelting behavior may only result from the isomerization of the outermost layer(6) without interlayer diffusion. Therefore, the premelting ranges obtained from the deformation parameter curves are not consistent with those from the characterizations of bond order parameter and Lindemann index. This is reasonable since the deformation parameter can reflect the interlayer diffusion behavior during premelting process but fails to display the surface isomerization with sensitivity. For other core-shell structures, similar phenomena are shown in Figure 6b-d. According to the results in Figure 6, the diffusion among layers which belong to Au shell becomes weaker as the Pt-core size increases. This is consistent with the fact that the premelting behavior is restrained as the size of the Pt core becomes larger, as discussed in previous section (cf. Figure 3). In the liquid state, the deformation parameters of layers for Pt atoms are still lower than those for Au atoms. It is an indicator that the Au atoms tend to be segregated into the surface while the Pt atoms tend to be located at the core. This is because the surface energy of the Au atom is much lower than that of Pt,64 so the assembly of Au atoms into surface is favorable to reduce the surface energy. It should be mentioned that the parameter of layer(1) shows considerable fluctuations after the melting point due to poor statistics caused by just one atom. For pure metal particles (see Figure 7), the deformation parameters of all layers have shown a change before the melting point. This means that all atoms in the pure metal particle

Figure 8. Variation of the potential energy per atom in the Au and Pt subsystems as a function of the temperature for the core-shell Pt-Au nanoparticles with different concentrations: (a) Pt13Au548, (b) Pt55Au506, (c) Pt147Au414, and (d) Pt309Au252. The corresponding subsystems in pure Au and pure Pt nanoparticles are also given here.


Yang et al.

Figure 9. Atom distribution functions for the Pt13Au548 nanoparticle at several typical temperatures, together with the final snapshots (the upper is for the surface structure and the lower for the inner structure) of the nanoparticle at each temperature. The pink color is for the Pt core atoms and the yellow color for the Au shell atoms.

Figure 10. Same as in Figure 9 but for the Pt55Au506 nanoparticle.

participate in the diffusion among layers, which is consistent with the results in Figure 5. The above-mentioned behavior that the Pt cores can keep stable without premelting stage below the melting point may be related to the relative stability in the core-shell structures. The potential energy distribution of each layer in the coreshell particles is given in Figure S3. The average potential energy per atom for all Pt layers always keeps steady with a linear variation until at melting point. The remarkably stable energy evolution with temperature may lead to the absence of premelting behavior for the Pt cores. On the contrary, the potential energy variation of the Au shells evidently deviates from linearity before the melting point. The relevant potential energy distributions for Au561 and Pt561 have been shown in Figure S4. For the pure metal nanoparticles, however, all energy curves show evident fluctuations before the homogeneous melting transition, which is in good agreement with the previous results that the premelting behavior of various layers for pure metal nanoparticles almost occurs at the same time (see Figures 5 and 7).

The average potential energies per atom for the Pt-core subsystems and the Au-shell subsystems in the core-shell structures are illustrated in Figure 8. From Table 1, we can note clearly that the species Au has the larger lattice constant and lower energy parameter. Based on the SC potential, the calculated average potential energy of Pt cores is much lower than that of Au shells (see Figure 8). If the average bonding energy is defined as the positive quality of the average potential energy, the bonding energy of Pt core is much higher than that of Au shell for each core-shell nanoparticle, which denotes that the Pt core is more stable than the Au shell. Additionally, the average potential energy of the subsystem counterparts in the pure Au and pure Pt particles is also given in Figure 8. By comparison, the average potential energy of the Pt subsystem in the core-shell structures is clearly lower than that in the pure Pt particle, which indicates that the presence of the Au shell enhances the thermal stability of the Pt core. For the Au subsystem, however, this comparison is reversed. In the coreshell structures, the melting mechanism is determined by the stability of both core and shell parts. At equilibrium, the higher





configuration energy in the Au-shell subsystem is balanced by the lower energy in the Pt-core subsystem. Furthermore, the higher stability of the Pt core suppresses the premelting extent in the core-shell structures, as compared with the pure metal nanoparticles. With an increase in the Pt core size for the coreshell nanoparticles, the premelting temperature zone becomes shorter (see Figure 3) due to the enhancing influence of the Pt core. With respect to the average potential energy for the Pt and Au subsystems, the difference between the core-shell nanoparticles and pure metal nanoparticles may be mainly attributed to the mismatch between larger Au atom and smaller Pt atom in the core-shell structures. As revealed by Mottet et al.,39 the introduction of smaller Pt atoms (with smaller lattice constant) into the core region can lead to the internal strain release of the icosahedral nanoparticles and enhance the thermal stability. In this study, the core-shell structure leads to an enhanced Pt lattice relaxation and a reduced Au lattice distance in comparison with the corresponding pure metal particles. For example, the mean first neighbor distance between Pt atoms is 2.76 Å for Pt13Au548 and 2.78 Å for Pt147Au414, which are larger than that

in pure Pt561 (2.74 Å). A similar result has been reported for the Ag-Co core-shell nanoparticle.65 An interesting feature can be found by a careful inspection in Figure 8d for Pt309Au252. At the melting point, the potential energy of Pt subsystem shows a step increase, which is notably different from the other core-shell structures. This distinctive behavior is due to large portion of Pt atom in the Pt309Au252 particle and the Pt atom could relatively easily move to the surface at the melting point. This phenomenon agrees with the observation that the latent heat of fusion of Pt309Au252 shows a maximum value, as shown in Figure 2. 3.3. Atom Distribution in the Core-Shell Structures. Finally, the melting processes for the core-shell Pt-Au nanoparticles were further characterized by the atom distribution function N(r), where N(r) dr is the number of atoms within a shell of thickness dr at r from the center of mass of particle. Figures 9-12 present the atom distribution functions of four bimetallic nanoparticles with core-shell structure at several typical temperatures, together with the corresponding configuration snapshots. At a low-temperature of 300 K, the snapshots show that all nanoparticles still process a compact icosahedral

4946 J. Phys. Chem. C, Vol. 112, No. 13, 2008 structure and the core-shell arrangement is well preserved. Accordingly, the curves of atom distribution function display a series of well-defined peaks, corresponding to different site positions in the icosahedral structure. A clear separation of distribution between the Au and Pt atoms can be observed. Just before the melting transition (see Figures 9-12b), the peaks of the distribution curves merge and become broader. However, the distributions of the Pt core still keep a typical solid character and the atom distributions of both Au and Pt remain separated. This phenomenon agrees with the previous discussions and confirms that the Pt-Au core-shell structures can be preserved before melting transition. After the melting transitions occur (see Figures 9-12c), the distribution curves of Pt and Au atoms overlap obviously and all atoms are more uniformly distributed across the whole particle. Meanwhile, it can be clearly seen from this inset snapshot that the Pt-Au core-shell structures do not exist. Up to a higher temperature of 1300 K, the nanoparticles transform into a complete liquid state only with one broad and smooth peak in the atom distribution curves. In addition, as shown in Figure 9, the covering range of the atom distribution for the Pt13Au548 bimetallic particle has extended from 14 Å (300 K) to 18 Å (1300 K), mainly due to the distortion of particle shape from a solid state to a liquid state. Similar behavior can be observed in other core-shell particles (see Figures 9-12). We also present the atom distribution curves for both pure metal nanoparticles in the Figures S5 and S6 of the Supporting Information, which are different from those of core-shell structures. 4. Conclusions We have applied the classical MD simulation to investigate the thermal and structural properties of the core-shell Pt-Au 561-atom nanoparticles. The nanoparticles have the doubleicosahedral core-shell structures with different concentrations: Pt13Au548, Pt55Au506, Pt147Au414, and Pt309Au252. For comparison, the pure gold and pure platinum with the same particle size were also studied. The melting points of the coreshell Pt-Au nanoparticles are determined by the combining analysis of the caloric curve, heat capacity, bond order parameter and Lindemann index. The results demonstrated that the increasing concentration of Pt can lead to an increase of the melting temperature. Prior to the homogeneous melting transition, both the PtAu core-shell and pure metal nanoparticles display different extents of premelting process. The premelting process of pure platinum is longer than that of pure gold. However, it is interesting to note that the premelting extents of core-shell structures are suppressed with an increase in the concentration of platinum and the temperature zones of the premelting stage are smaller than those of both pure gold and pure platinum. Through detailed analysis of the Lindemann index and deformation parameter of each individual partitioned layer, the difference in the premelting behavior between pure metals and core-shell bimetallic nanoparticles is characterized. For the cases of the core-shell structure, regardless of the size of the Pt core, the premelting phenomenon only occurs within the Au shell, while the core always keeps a typical solid state until the homogeneous melting takes place. However, in the two pure metal nanoparticles, all atoms even including the center atom contribute to the premelting behavior. A comparison of the average potential energy of Au and Pt subsystems between the pure metals and the core-shell structures indicates that the average bonding energy of the Pt core is much higher than that of the Au shell. The presence of

Yang et al. the Au shell enhances the thermal stability of the Pt core due to a mismatch resulting from different characteristics of the Pt and Au atoms. Hence, the stable structures of the Pt cores in the core-shell nanoparticles can be preserved well before the homogeneous melting point. These results in this work may suggest that the chemical activity and thermal and structural stability of core-shell nanoparticles could be tuned up through adjusting the size of core, which is very promising for the preparation of core-shell bimetallic nanopartilces. Acknowledgment. This work was supported by the Natural Science Foundation of China under the Grant 20476044. Supporting Information Available: Figures S1 and S2: The variation of the heat capacity and Lindemann index as a function of temperature for all cases. Figures S3 and S4: The variation of the potential energy per atom in each layer as a function of the temperature for the core-shell Pt-Au and pure metal nanoparticles. Figures S5 and S6: Atom distribution functions for the Au561 and Pt561 nanoparticles together with the corresponding snapshots. Table S1: Coordinates of 561atom Au icosahedral nanoparticle after optimization. This information is available free of charge via the Internet at http:// pubs.acs.org. References and Notes (1) Corma, A.; Serna, P. Science 2006, 313, 332. (2) Favier, F.; Walter, E. C.; Zach, M. P.; Benter, T.; Penner, R. M. Science 2001, 293, 2227. (3) Maheshwari, V.; Saraf, R. F. Science 2006, 312, 1501. (4) Tang, Z. Y.; Kotov, N. A. AdV. Mater. 2005, 17, 951. (5) Xia, Y. N.; Yang, P. D.; Sun, Y. G.; Wu, Y. Y.; Mayers, B.; Gates, B.; Yin, Y. D.; Kim, F.; Yan, Y. Q. AdV. Mater. 2003, 15, 353. (6) Toshima, N.; Yonezawa, T. New J. Chem. 1998, 22, 1179. (7) Fernandez, J. L.; Walsh, D. A.; Bard, A. J. J. Am. Chem. Soc. 2005, 127, 357. (8) Liu, S. H.; Han, M. Y. AdV. Funct. Mater. 2005, 15, 961. (9) Graf, C.; van Blaaderen, A. Langmuir 2002, 18, 524. (10) Jeong, U.; Kim, J.-U.; Xia, Y. N. Nano. Lett. 2005, 5, 937. (11) Sanedrin, R. G.; Georganopoulou, D. G.; Park, S.; Mirkin, C. A. AdV. Mater. 2005, 17, 1027. (12) Yang, H.; Alonso-Vante, N.; Leger, J. M.; Lamy, C. J. Phys. Chem. B 2004, 108, 1938. (13) Johnston, R. L. Atomic and Molecular Clusters; Taylor and Francis: London, 2002. (14) Castro, T.; Reifenberger, R.; Choi, E.; Andres, R. P. Phys. ReV. B 1990, 42, 8548. (15) Ercolessi, F.; Andreoni, W.; Tosatti, E. Phys. ReV. Lett. 1991, 66, 911. (16) Lai, S. L.; Guo, J. Y.; Petrova, V.; Ramanath, G.; Allen, L. H. Phys. ReV. Lett. 1996, 77, 99. (17) Bottani, C. E.; Li Bassi, A.; Tanner, B. K.; Stella, A.; Tognini, P.; Cheyssac, P.; Kofman, R. Phys. ReV. B 1999, 59, R15601. (18) Schmidt, M.; Kusche, R.; Kronmuller, W.; von Issendorff, B.; Haberland, H. Phys. ReV. Lett. 1997, 79, 99. (19) Schmidt, M.; Kusche, R.; von Issendorff, B.; Haberland, H. Nature (London) 1998, 393, 238. (20) Kusche, R.; Hippler, T.; Schmidt, M.; von Issendorff, B.; Haberland, H. Eur. Phys. J. D. 1999, 9, 1. (21) Haberland, H.; Hippler, T.; Donges, J.; Kostko, O.; Schmidt, M.; von Issendorff, B. Phys. ReV. Lett. 2005, 94, 035701. (22) Calvo, F.; Spiegelmann, F. J. Chem. Phys. 2000, 112, 2888. (23) Shvartsburg, A. A.; Jarrold, M. F. Phys. ReV. Lett. 2000, 85, 2530. (24) Breaux, G. A.; Benirschke, R. C.; Sugai, T.; Kinnear, B. S.; Jarrold, M. F. Phys. ReV. Lett. 2003, 91, 215508. (25) Baletto, F.; Ferrando, R. ReV. Mod. Phys. 2005, 77, 371. (26) Lopez, M. J.; Marcos, P. A.; Alonso, J. A. J. Chem. Phys. 1996, 104, 1056. (27) Huang, S.-P.; Balbuena, P. B. J. Phys. Chem. B 2002, 106, 7225. (28) Sankaranarayanan, S. K. R. S.; Bhethanabotla, V. R.; Joseph, B. Phys. ReV. B 2005, 71, 195415. (29) Chen, F.; Curley, B. C.; Rossi, G.; Johnston, R. L. J. Phys. Chem. C 2007, 111, 9157. (30) Sastry, M.; Swami, A.; Mandal, S.; Selvakannan, P. R. J. Mater. Chem. 2005, 15, 3161.

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