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Applied Surface Science 422 (2017) 1139–1146

Contents lists available at ScienceDirect

Applied Surface Science

journa l homepage: www.e lsev ier .com/ locate /apsusc

ull Length Article

tomistic modeling of metallic thin films by modified embeddedtom method

uali Hao a, Denvid Lau a,b,∗

Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, ChinaDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

r t i c l e i n f o

rticle history:eceived 23 March 2017eceived in revised form 22 April 2017ccepted 2 May 2017vailable online 3 May 2017

eywords:luminum

nterfaceetallic thin film

a b s t r a c t

Molecular dynamics simulation is applied to investigate the deposition process of metallic thin films. Eightmetals, titanium, vanadium, iron, cobalt, nickel, copper, tungsten, and gold, are chosen to be depositedon the aluminum substrate. The second nearest-neighbor modified embedded atom method potential isadopted to predict their thermal and mechanical properties. When quantifying the screening parametersof the potential, the error for Young’s modulus and coefficient of thermal expansion between the simu-lated results and the experimental measurements is less than 15%, demonstrating the reliability of thepotential to predict metallic behaviors related to thermal and mechanical properties. A set of potentialparameters which governs the interactions between aluminum and other metals in a binary system isalso generated from ab initio calculation. The details of interfacial structures between the chosen films

odified embedded atom method potentialolecular dynamics simulation

and substrate are successfully simulated with the help of these parameters. Our results indicate thatthe preferred orientation of film growth depends on the film crystal structure, and the inter-diffusion atthe interface is correlated the cohesive energy parameter of potential for the binary system. Such find-ing provides an important basis to further understand the interfacial science, which contributes to theimprovement of the mechanical properties, reliability and durability of films.

© 2017 Elsevier B.V. All rights reserved.

. Introduction

Metallic thin films are widely deposited on Al for improvingts low load bearing capacity, electrical conductivity, photoelec-ric property and low corrosion resistance [1–5]. Residual stress,hich significantly affects the reliability and performance of metal-

ic films, cannot be avoided during fabrication. In general, therere two main reasons causing the residual stress in metallic films.irstly, due to the difference of thermal expansion coefficients�) between thin films and substrate, a thermal residual stressrises during the deposition process [5,6]. Secondly, the lattice mis-atch between thin film and substrate, and the defects within

lms (e.g. point defects, dislocations, grain boundaries) intro-uce intrinsic residual stress [7]. Some straightforward methodsuch as X-ray diffraction and neutron diffraction methods are

mployed to measure the residual stress in the thin film [8], and theigh-resolution transmission electron microscopy and scanningunneling microscopy are applied to characterize and investigate

∗ Corresponding author at: Department of Architecture and Civil Engineering, Cityniversity of Hong Kong, Hong Kong, China.

E-mail address: denvid@mit.edu (D. Lau).

ttp://dx.doi.org/10.1016/j.apsusc.2017.05.011169-4332/© 2017 Elsevier B.V. All rights reserved.

the microstructure evolution of films [9,10]. However, experimen-tal techniques are difficult to be adopted for measuring the residualstress in films with less than 100 nm thickness and displaying thedetails of interfacial microstructures, such as the inter-diffusion,defect, lattice mismatch, which are partial origins of the residualstress [11,12]. Even during the preparation of experimental speci-men, defects are unavoidably generated, resulting in the inaccuracyof characterizing and measuring residual stress. An approach toreveal microstructure and predict properties within several nano-size structures is necessary for a fundamental understanding of filmresidual stress, which contributes to the improvement of the dura-bility, reliability and properties of thin films. It is of technologicalsignificance, which paves a way for material selection of metallicthin films and optimization of manufactory techniques.

Molecular dynamics (MD) simulation provides a powerfulmeans for displaying atom configuration, predicting the materialsproperties, and quantifying the mechanisms of the structure-properties relationship [13–21]. A critical component of MDsimulation is the potential, which determines the accurately in

predicting properties of materials [22]. Selecting a good potentialenables us to precisely predict physical phenomenon and thermalproperties of film-substrate systems, such as defect formation, dis-locations, elastic modulus and �. Additionally, as the deposited film

1140 H. Hao, D. Lau / Applied Surface Science 422 (2017) 1139–1146

Table 1Parameters for 2NN MEAM potential of Al substrate material, and film materials Ni, Cu, Au, V, Fe, W, Ti and Co are represented. The units of the cohesive energy Ec, theequilibrium nearest-neighbor distance re and the bulk modulus K are eV, Å and × 1011 Pa, respectively.

Al [26] Ni [26] Cu [31] Au [26] V [27] Fe [27] W [27] Ti [14] Co [32]

Ec 3.36 4.45 3.54 4.08 5.30 4.29 8.66 4.87 4.41re 2.86 2.49 2.56 3.93 2.62 2.48 2.74 2.92 2.50K 0.79 1.88 1.38 1.80 1.57 1.67 3.14 0.91 1.95A 1.16 0.94 0.94 1.00 0.73 0.5 0.40 0.70 0.90�(0) 3.20 2.56 3.83 5.77 4.74 3.67 6.54 2.30 3.50�(1) 2.6 1.5 2.2 2.2 1.0 1.0 1.0 1.0 0.0�(2) 6.0 6.0 6.0 6.0 2.5 1.0 1.0 6.5 0.0�(3) 2.6 1.5 2.2 2.2 1.0 1.0 1.0 1.0 4.0t(1) 3.1 3.1 2.7 2.9 3.3 2.1 −0.6 3.5 3.0t(2) 0.5 1.8 3.0 1.6 3.2 1.0 0.3 0.1 5.0t(3) 7.8 4.4 2.0 2.0 −2.0 −8.5 −8.7 −10 −1.0

ofbdpFafiibpeSmfitioMtfwsin(pai

mgtdaStappmcpNEcoam

Cmin 0.49 0.81 0.80 1.53

Cmax 2.80 2.80 2.80 2.80

d 0.05 0.0 0.05 0.05

n the substrate results in the formation of an interface, the inter-ace structure can be forecast by the potential. Recently, there haveeen some literatures about applying MD simulation to model theeposition process of thin film with different potentials. For exam-le, the tight-binding potential has been employed to simulatee and Co atoms deposited on Cu substrate [23]. The embedded-tom method potential has been utilized to simulate the Al thinlm deposited on Cu substrate [24]. However, the details of the

nterfacial structure, such as the lattice mismatch at the interfaceetween thin film and substrate, cannot be clearly revealed by theseotentials. The modeled thin films cannot show the preferred ori-ntation growth mechanism and their natural crystal structures.uch modeled structures deviate from the experimental finding,aking them questionable for the analysis of residual stress in thin

lms. The modified embedded atom method (MEAM) potential ishe first semi-empirical potential that shows the possibility of hav-ng one single formulation which can be applied to a wide rangef elements by considering the nearest-neighbor interactions [25].EAM potential has been successfully applied to precisely estimate

he formation energy of defect, the stacking faults energy, the sur-ace energy, and the structural transformation energy for metals

ith various crystal structures except body-centered-cubic (bcc)tructure [26]. It is because the second nearest neighbor distancen bcc structure, which is just 15% larger than the first nearest-eighbor distance, is neglected [26]. The second nearest-neighbor2NN) MEAM potential has been developed based on the MEAMotential to consider both the first nearest-neighbor interactionnd the second nearest-neighbor interaction, successfully predict-ng many physical properties of bcc metals.

The objective of this work is to predict the mechanical and ther-al properties of different metals by 2NN MEAM potential, and to

enerate the 2NN MEAM parameters for binary systems from ab ini-io calculation that can predict the interfacial structure during theeposition process. Eight transition metals, Ti, V, Fe, Co, Ni, Cu, Wnd Au (sorted by atomic number) are deposited on the Al substrate.pecifically, Ni, Cu and Au have a face-centered-cubic (fcc) struc-ure, alike to the Al substrate; V, Fe, and W are of bcc structure; Tind Co have hexagonal close-packed (hcp) structure. The screeningarameters are firstly quantified based on the existing 2NN MEAMarameters for evaluating Young’s modulus (E) and � of depositedetals and substrate. Subsequently, the calculated properties are

ompared with the available experimental data. In addition, theotential parameters for interaction between Al and Ti, V, Fe, Co,i, Cu, W and Au are obtained by the first principles calculation.ventually, with the help of these parameters, the deposition pro-

ess of metallic films on substrate can be modeled and the detailsf interfacial structure can be illustrated. Our work provides a newpproach to characterize interfacial microstructures, such as latticeismatch, inter-diffusion, and reaction at interface, and to pre-

0.49 0.16 0.49 1.0 0.492.80 2.80 2.80 1.44 2.800.00 0.05 0.00 0.00 0.00

dict the properties of metallic thin film/substrate systems, such asintrinsic residual stress, interfacial adhesive toughness and interfa-cial fracture energy. All these benefit the analysis of the interfacialbehaviors, such as the crack prolongation and interfacial fracture,and help scientists an engineering improve the performance anddurability of thin films.

2. Simulation method

The full description on the 2NN MEAM formulation has beenpublished in details [27]. For pure elements, each pair interactionis characterized by a total of 14 independent parameters: the equi-librium nearest neighbor distance (re), the cohesive energy of atoms(Ec), the bulk modulus (K), an adjustable parameter (d) for the uni-versal equation of state, four exponential decay factors (�(0), �(1),�(2), �(3)) for the electron density, three weight factors (t(1), t(2), t(3))for the electron density, one parameter (A) for the embedding func-tion, and two parameters (Cmin, Cmax) for many-body screening. Fora binary system, in addition to unary potential parameters, another13 independent parameters are involved: Ec, re, K, d, �0 (electrondensity ration between individual elements), four Cmin and fourCmax [28,29]. As Cmin and Cmax determine the extent of screeningfor an atom from the interaction with two neighbor atoms, thereare four different types of interaction (i.e. A-B-A, B-A-B, A-A-B andA-B-B) in a binary system consisting of elements A and B [29]. Par-ticularly, the potential parameters Ec, re and K for binary systemsare determined either from experimental data or first principlecalculation based on a reference structure.

The MD simulation is carried out by using the parallel MDcode LAMMPS [30]. 2NN MEAM parameters for pure elements ofdeposited films and substrate are applied as the starting point,shown in Table 1 [14,26,27,31,32]. During the parameterization,the parameter Cmin for Cu is reduced from 1.21 originally to 0.8, andCmax for Co is increased from 2.0 originally to 2.8. This ensures theMEAM predictions of � not deviating noticeably from the experi-mental data. Such an adjustment has no effects on other properties.All ab initio calculations are performed in the Materials Studioby using generalized gradient approximation pseudopotential todevelop the potential parameters [33]. During the uniaxial ten-sile deformation, the tensile loading is implemented by subjectingthe simulation box of 10a × 10a × 20a (a = lattice constant) with aconstant strain rate 108 s−1 along the z-coordinate at 300 K. Thethermal expansion coefficient is calculated based on the averagethermal expansion in each direction and is given by the following

equation [34]:

˛(T) = 13

[1lx(T)

· dlx(T)dT

+ 1ly(T)

· dly(T)dT

+ 1lz(T)

· dlz(T)dT

] (1)

H. Hao, D. Lau / Applied Surface Science 422 (2017) 1139–1146 1141

F ; (b) pl he val

wadcpdeoem2i

otptiwptbmPodftfit

ig. 1. Stress-strain curves for different pure metals by MD simulation: (a) pure Alinear relationship between strain � and stress �. The slope of red line represents tegend, the reader is referred to the web version of this article.).

here lx, ly and lz are the size of the simulation box in the x, y,nd z directions at temperature of T. Specifically, the x, y and zirections are parallel to the [100], [010] and [001] directions ofrystal. To obtain this information, a model is developed in whicheriodic boundary conditions are applied to a unit cell in all threeirections. The simulation box (i.e. 10a × 10a × 10a) suffers fromlevating temperature from 300 K to 500 K. The three dimensionsf the simulation box are allowed to vary independently under zeroxternal pressure. By examining the root-mean-square displace-ent (RMSD) of atoms, which keeps at a constant level before the

00 ps NVT equilibrium run completes at different temperatures, itmplies that the equilibrated state has been obtained.

Metallic thin films, Ti, V, Fe, Co, Ni, Cu, W and Au are depositedn the Al substrate with a size of 24.3 Å × 24.3 Å × 16.2 Å, where theemperature of substrate is of small fluctuation during depositionrocess. The lowest two layers of the substrate are fixed to preventhe substrate from shifting due to the momentum transfer dur-ng collisions. The middle layers are called thermal control layers,

here the temperature is rescaled every ten steps according to therescribed substrate temperature (300 K). The atom velocities ofhe thermal control layers are given by Maxwell-Boltzmann distri-ution at the substrate temperature. The top three layers are free toove as to model the interactions of atoms during the deposition.

eriodic boundary conditions are imposed in the x and y directionsf the simulation box. A free boundary condition is used in the zirection, where the substrate atoms at surface are able to move

reely. It should be noted that the x, y and z directions are parallel to

he [100], [010] and [001] directions of Al crystal, respectively. Thelm atoms randomly deposit on the substrate surface from a posi-

ion of 121.5 Å above the Al surface. Deposition is performed with

ure Cu; (c) pure Fe; and (d) pure Co. When the strain � is less than 0.05, there is alue of Young’s modulus. (For interpretation of the references to color in this figure

a deposition rate of 1 atom per picosecond. Then, a relaxation pro-cess is conducted to enable the deposited system to equilibrate. Theroot-mean-square displacement of the atoms becomes stable afterrelaxation, indicating that the system has reached the equilibriumstate.

3. Simulation results and discussion

3.1. The mechanical and thermal properties of pure metals

Besides the Al substrate, the modeled property curves for threerepresentative film materials with different structures, namely, Cuwith fcc structure, Fe with bcc structure and Co with hcp structureare particularly demonstrated. The overall stress and strain rela-tions for the represented materials, Al, Cu, Fe, and Co are shown inFig. 1. The stress of these materials shows a linear response to theapplied strain at the early stage (elastic stage). For Al, Cu, and Cometals, when the strain is over a specific value (about 0.05), thesesamples have a non-linear relationship between strain and stresswith a uniform deformation, which indicates they suffer from plas-tic deformation. However, the strain-stress curve for Fe metal isdifferent with a non-uniform deformation. This is because differ-ent from other kinds of metals (i.e. fcc, hcp), the bcc metals typicallydo not obey Schmidt’s law during deformation, where slip occurson crystallographic planes, rather than the one with the maximumresolved shear stress [35–37]. The strain-stress curves from simu-

lation for these metals are in accordance with experimental tensiletests, where stress-strain curves for fcc and hcp metals have noyield phenomenon, while it yields with a non-homogenous defor-mation for bcc metals [38]. Based on the obtained stress-strain

1142 H. Hao, D. Lau / Applied Surface Science 422 (2017) 1139–1146

Fig. 2. The length deviation in x direction, plotted as a function of temperature: (a) pure Abox, the change of length along y and z directions is similar to that in x direction.).

Table 2Predicted Young’s modulus E and coefficient of thermal expansion � by 2NN MEAM,compared with the experimental results [41].

E (GPa) � ( × 10−6 K−1) (at room temperature)

MEAM Experiment Error MEAM Experiment ErrorAl 76.3 70.6 8.1% 21.2 23.1 8.2%Ni 201.4 199.5 1.0% 11.8 13.4 11.9%Cu 128.1 125.6 2.0% 15.9 16.5 2.2%Au 86.1 78.5 9.7% 12.1 14.2 14.8%V 142.8 127.6 11.9% 9.9 8.4 17.9%Fe 226.0 208 8.7% 12.6 11.8 6.8%W 432.8 411 5.3% 5.3 4.5 17.8%Ti 132.3 120.2 10.1% 7.4 8.6 14.0%Co 217.8 211 3.2% 11.8 13.6 13.2%

Nr

coArssasFr

iavomtv

ote: The error is the difference between the experimental data and the MEAMesults with respects to the experimental measurement.

urves, E is calculated by performing a linear regression analysisn the stress-strain data ranging at the elastic stage. The E of purel, Cu, Fe and Co are 76.3 GPa, 128.1 GPa, 226.0 GPa and 217.8 GPa,

espectively. Thermal expansion in the x, y, and z directions are theame for Al, Cu, Fe and Co, due to their periodical perfect crystallinetructures. The change of length in x directions at specific temper-ture is shown in Fig. 2. The length of the simulation box growsteadily with temperature. Based on Eq. (1), the typical � of Al, Cu,e, and Co metals at 300 K are 21.2, 15.9, 12.6 and 11.8 ( × 10−6 K−1),espectively.

The values of E and � for all modeled materials are summarizedn Table 2, compared with the experimental data. For all these met-ls, the simulation results of E are higher than the experimentalalues. This is because the strain rate in MD simulation is several

rders of magnitude higher, making less contribution of thermalotions to the mechanical response of the materials [39]. Addi-

ionally, the constructed model is free from structural defects andoids, which normally exist in the macroscopic samples. All these

l; (b) pure Cu; (c) pure Fe; and (d) pure Co. (As there is no defect in the simulation

result in the overestimation of E. The errors between the simulationresults and experimental values are less than 10%. Nevertheless,the predicted � is subtly lower than the experimental value. Thisunderestimation is possibly due to the imperfections in real mate-rials [40]. The errors of � for different metals are less than 15%.Such errors are much lower than the simulation results predictedby other potentials [42,43]. This indicates the reliability of MEAMpotential to predict the mechanical and thermal properties of filmmaterials, Ti, V, Fe, Co, Ni, Cu, W, Au and Al substrate material.

3.2. Interfacial structure between films and Al substrate withdeveloped 2NN MEAM potential

To describe the interfacial interaction in a bilayer system, themain task is to estimate the thirteen potential parameters for abinary system as mentioned above. According to phase diagrams,different intermetallic compounds between Al and elements of thinfilms are possible to form [41]. However, for films deposited on theAl substrate, the types of intermetallic compounds formed are notall available from experiments, or highly depend on the experi-mental conditions [44]. Furthermore, some formed compounds inexperiments are too complex to be modeled. For example, Al5Wwith hP12 structure is formed, when W film has been coated onAl [45]. Here, the intermetallic compounds with a high atom con-tent of Al are selected as a reference structure to determine theparameters Ec, re and K for binary systems. Generally, the substrateis thicker than the film, (i.e. a higher atom ratio of substrate tothin films), which results in a preferable formation of intermetalliccompounds with a high content of Al. The calculated 2NN MEAMparameters for Al-Cu, Al-Fe and Al-Co systems are presented in

Table 3. The first three parameters, which are computed basedon the first principle calculation or available data from literatures[32,38]; the other parameters are calculated through the corre-sponding equations in Table 3. Specifically, d is related to the atom

H. Hao, D. Lau / Applied Surface Science 422 (2017) 1139–1146 1143

Fig. 3. MD simulation snapshots of the deposition process at different times for Cu film deposited on Al (a) 50 ps; (b) 100 ps; (c) 200 ps; (d) 800 ps; (e) 1400 ps. The Cu atomsare located at the lattice points of the fcc structure during the deposition process. The growth mode of thin film is nearly layer-by-layer.

Table 32NN MEAM potential parameters set for the binary Al-M (M represents Cu, Fe, and Co) systems are garnered from ab initio calculation. The units of the cohesive energy Ec,the equilibrium nearest-neighbor distance re and the bulk modulus K are eV, Å and × 1011 Pa, respectively.

Reference state B1-AlCu L12-AlFe3 B1-AlCo

Ec 0.5EAlc + 0.5ECu

c − 0.19 [31] 0.25EAlc + 0.75EFe

c + 0.337 0.5EAlc + 0.5ECo

c + 0.565 [32]K 1.09 1.59 1.62re 2.53 [31] 2.51 2.48 [32]d 0.5 dAl + 0.5 dCu 0.75 dAl + 0.25 dFe 0.5 dAl + 0.5 dCo

�0 �Al/�Cu = 1 �Al/�Fe = 1 �Al/�Co = 1CAl−M−Al

minCAl

min= 0.49 CAl

min= 0.49 CAl

min= 0.49

CM−Al−Mmin

CCumin

= 0.80 CFemin

= 0.16 CComin

= 0.49

CAl−Al−Mmin

[(CAl

min)1/2+(CCu

min)1/2

2 ]

2

= 0.64 [(CAl

min)1/2+(CFe

min)1/2

2 ]

2

= 0.30 [(CAl

min)1/2+(CCo

min)1/2

2 ]

2

= 0.49

CM−AL−ALmin

[(CAl

min)1/2+(CCu

min)1/2

2 ]

2

= 0.64 [(CAl

min)1/2+(CFe

min)1/2

2 ]

2

= 0.30 [(CAl

min)1/2+(CCo

min)1/2

2 ]

2

= 0.49CM−AL−AL

minCAl

max = 2.8 CAlmax = 2.8 CAl

max = 2.8CAl−Al−M

minCCu

max = 2.8 CFemax = 2.8 CCo

max = 2.0

CAl−Al−Mmin

[(CAl

max )1/2+(CCu

max )1/2

2 ]2

= 2.8 [(CAl

max )1/2+(CFe

max )1/2

2 ]2

= 2.8 [(CAl

max )1/2+(CCo

max )1/2

2 ]2

= 2.4

CM−AL−ALmin

[(CAl

max )1/2+(CCu

max )1/2

2 ]2

= 2.8 [(CAl

max )1/2+(CFe

max )1/2

2 ]2

= 2.8 [(CAl

max )1/2+(CCo

max )1/2

2 ]2

= 2.4

1144 H. Hao, D. Lau / Applied Surface Science 422 (2017) 1139–1146

Fig. 4. MD simulation snapshots of the deposition process at different time for Fe film depatoms at the beginning stage of deposition process; (b) 200 ps; (c) 800 ps; (d) 1400 ps. ThThe inter-diffusion mainly occurs between the uppermost layer of Al substrate and the lo

Table 4Parameters Ec, re, and K set for binary Al-M (M represents Ni, Au, V, W and Ti) systemsare obtained by ab initio calculation. The units of the cohesive energy Ec, the equilib-rium nearest-neighbor distance re and the bulk modulus K are eV, Å and × 1011 Pa,respectively.

Referencestate

L12-Al3Ni L12-Al3Au L12-Al3V B1-AlW L12-Al3Ti

E 3.86 3.71 [45] 3.94 6.46 [46] 3.34 [47]

rBOfeswattw

MTsfifiopussttssrTeo

c

re 2.73 2.88 [45] 2.93 2.49 [46] 2.77 [47]K 1.15 1.59 0.83 1.97 1.18

atio in the reference structure; Cmin and Cmax for type A-B-A and-A-B are equivalent to those of pure B and pure A, respectively.ther Cmin and Cmax for type A-A-B and A-B-B directly are deduced

rom the equations shown in Table 3. The value of �0 normally isqual to 1. Table 4 shows the parameters Ec, re and K for binaryystems between Al and other elements (i.e. Ni, Au, W, V and Ti)hich are calculated by first principle approach and based on liter-

tures [46,47]. Such developed potential parameters are effectiveo explicitly display the interfacial structure, and it provides a basisowards the study of interfacial diffusion, reaction, lattice mismatchhich are difficult to be characterized by experiments [5].

The deposition process is modeled with the developed 2NNEAM potential parameters for Al and other metals in Table 3 and

able 4. The snapshots of deposited Cu and Fe films on the Al sub-trate at different times are shown in Figs. 3 and 4, respectively. Therst monolayer of the films is identical with the natural depositedlms’ lattice, and then the next monolayer grows. The growth modef films is nearly layer-by-layer. Eventually, this growth processrovides the lattice of the deposited films resembles to their nat-ral crystal structures. Moreover, the Fe atoms penetrate into theubstrate at the beginning of the deposition process as the circleshown in Fig. 4(a), while there are no deposited Cu atoms pene-rating into the substrate in Fig. 3(a). As the Co atoms, similar tohe case of Fe film, diffuse into the substrate at the beginning depo-ition process, the detailed snapshots of deposited Co film are nothown. Fig. 5 shows the final interfacial structures between the rep-

esentative metallic thin films (Cu, Fe and Co) and the Al substrate.he microstructures demonstrate the film growth of preferred ori-ntations, developing a coherent interface with the substrate. Therientation relationships between Cu and Al are Cu (100)//Al (100),

osited on Al: (a) 50 ps; partial Fe atoms penetrate into the substrate and replace Ale Fe atoms are located at the lattice point of bcc structure during deposit process.west two monolayers of Fe film.

Cu (010)//Al (010), the Cu film exhibiting a strong growth pref-erence on (001) plane in Fig. 5(a). Fig. 5 (b) shows the interfacialstructure between Fe and Al, where the preferred orientation of Fefilm is (001) plane. There are relationships of bcc Fe [110]//Al [100]

and Fe [110]//Al [010]. The Co film prefers to grow on (011) plane asshown in Fig. 5(c). The different preferred orientation of film growthhighly depends on the minimum surface energy of crystal struc-tures and the discrepancy of lattice mismatch between thin filmsand substrate. Comparing with the Cu film, the Fe and Co films havea higher lattice mismatch with Al, resulting in the films prefers togrow on the surface with minimize surface energy or rotation. Thedetails of inter-diffusion at the interface are also shown in Fig. 5.The Fe and Co films inter-mix with the Al substrate, as the circlesshown in Fig. 5(b) and (c), while there is no inter-diffusion betweenCu and Al. This is correlated to the cohesive energy of the referencestructure in binary systems, as represented in Table 3. The cohe-sive energy of Al-Fe and Al-Co is higher than pure Fe-Fe and Co-Co,resulting in diffusion, whereas the cohesive energy of Al-Cu is lowerthan pure Cu-Cu, leading to Cu atoms prone to aggregate on thesubstrate surface. Such a detailed and clear display of interfacialstructure provides an approach to study the interfacial properties,such as interfacial adhesive strength and residual stress at inter-face, and to analyze the effect of crystal structure on the interfacialbehavior, i.e. the interfacial cracking prolongation, interfacial frac-ture and detachment. It is envisioned that this research can helpto improve the performance and durability of films and provideguidelines for the film design.

4. Conclusion

In summary, the 2NN MEAM potential is employed to modelthe tensile and thermal behaviors of the Al substrate material andthe different film materials, Ti, V, Fe, Co, Ni, Cu, W and Au. Thediscrepancy for Young’s modulus and coefficient of thermal expan-sion between simulated results and measurement is less than 15%.The potential parameters, such as cohesive energy, lattice constant

and bulk modulus, for the binary systems between Al and otherelements are generated from ab initio calculation. The metallic thinfilms deposited on the Al substrate is successfully modeled. Metallicthin films with different crystal structures grow on their preferen-

H. Hao, D. Lau / Applied Surface Science 422 (2017) 1139–1146 1145

Fig. 5. The interfacial structure between films and the Al substrate modeled with 2NN MEAM potential: (a) the Cu film; (b) the Fe film; (c) the Co film. The growth of filmsshows a preferred orientation, with a coherent interface developed between the films and substrate. The Cu film grows on (001) plane with Cu (100)//Al (100) and Cu (010)//Al

( nd Fe

i e the cC

t(

tppTtiTba

A

dtC(

R

[

[

[

[

[

[

[

[

[

[

[

[

[

[

[

[

[

[

010). The preferred orientation of Fe film is (001) plane, with Fe [110]//Al [100] anter-diffusion is observed in the Fe and Co films deposited on Al substrate, becauso-Co, respectively.

ial planes. The Cu film grows on the (001) plane in both Cu (100)//Al100) and Cu (010)//Al (010). Although the preferred orientation of

he Fe film is also (001) plane, the Fe [110] and [110] directions arearallel to Al [100] and [010], respectively. The Co film has a strongreferred orientation on (011) plane with inter-mixing at interface.he successful prediction of interfacial structures contributes tohe further understanding on the interfacial behaviors, which arempossible to be in-situ observed by the experimental methods.his work provides a basis to investigate the interfacial science inilayer material system, with a focus to improve its performancend durability.

cknowledgments

The authors are grateful to the support from Croucher Foun-ation through the Start-up Allowance for Croucher Scholars withhe Grant No. 9500012, and the support from the Research Grantsouncil (RGC) in Hong Kong through the General Research FundGRF) with the Grant No. 11255616.

eferences

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