Surface segregation, structural features, and diffusion of NiCu bimetallic nanoparticles

Deng Yong-He; Zhang Yu-Wen; Tan Heng-Bo; Wen Da-Dong; Gao Ming; Wu An-Ru

doi:10.7498/aps.70.20210336

Abstract

Bimetallic core-shell nanoparticles such as NiCu are of great interest not only due to their excellent stability, selectivity, and magnetic and catalytic properties, but also because they are tunable by changing the morphology, surface element distribution, and particle size of the nanoparticles. The surface segregation and structural features of NiCu bimetallic nanoparticles, the deposition growth and the surface diffusion of Cu adsorbed atoms on the Ni substrate surface are studied by using molecular dynamics and the Montero method combined with embedded atomic potential. The results show that the Cu atom has a strong tendency of surface segregation. With the increase of concentration of Cu atoms, Cu atoms preferentially occupy the vertex, edge, (100), and (111) facet of nanoparticles due to the difference in configuration energy between Cu atoms and surface Ni atoms with different coordination numbers after the exchange, and finally form perfect Ni-core/Cu-shell nanoparticles. When growth temperature T = 400 K, the Ni-core/Cu-shell structure formed is the most stable. By observing the NiCu core-shell structure’s growth sequence, it is found that a few Ni atoms are replaced by Cu atoms on the step edge of the Ni substrate. The diffusion energy barrier of Cu atoms adsorbed on a Ni substrate surface is calculated by using the nudged elastic band method. The results show that Cu atoms adsorbed need to overcome a large ES barrier for both exchange and diffusion, making it difficult to diffuse between the facets of Ni substrate surface in a temperature range of 200–800 K. The lowest energy barrier for the diffusion of Cu atoms between facets of Ni substrate surface is 0.43 eV, and the diffusion path is from (111) facet to (100) facet. In contrast to Ni substrate, Ni atoms deposited on Cu substrate can easily migrate from the (111) facet to the (100) facet with a diffusion energy barrier of only about 0.12 eV, and at the present simulated temperature, Ni adsorbed atoms are unable to migrate on the (100) facet, resulting in a growth configuration toward an octahedral shape with its eight apex angles almost occupied by Ni atoms. In this paper, a new idea and method are provided for the preliminary design of NiCu nano-catalysts from atoms.

Keywords:

Authors and contacts

1.
School of Computational Science and Electronics, Hunan Institute of Engineering, Xiangtan 411104, China
2.
College of Physics, Mechanical and Electrical Engineering, Jishou University, Jishou 416000, China
3.
Hunan Provincial Key Laboratory of Vehicle Power and Transmission Systems, Hunan Institute of Engineering, Xiangtan 411104, China

Corresponding author: Deng Yong-He, dengyonghe1@163.com

Funds: Projects supported by the National Natural Science Foundation of China (Grant Nos. 51701071, 51871096) and the Natural Science Foundation of Hunan Province, China (Grant Nos. 2016JJ5028, 2018JJ3100)

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References

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[45]	Cleveland C L, Luedtke W D, Landman U 1999 Phys. Rev. B 60 5065 Google Scholar
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[52]	Wang Q, Wang X, Liu J, Yang Y 2017 J. Nanopart. Res 19 25 Google Scholar
[53]	Vitos L, Ruban A V, Skriver H L, Kollár J 1998 Surf. Sci. 411 186 Google Scholar
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Cited By

图 1 (a) TOC结构纳米粒子的总原子数与表面原子数比例随尺寸的关系; (b) TOC纳米粒子的表面催化位点比例随尺寸的关系

Figure 1. (a) The total atom number and surface atom percentage of TOC structure nanoparticles as a function of nanoparticle size; (b) the relationship between the surface catalytic sites density of TOC structure nanoparticles and the size of nanoparticles.

DownLoad: Full-Size Img PowerPoint

图 2 具有TOC结构的Ni和Cu纳米粒子的每原子势能和林德曼指数随温度的变化

Figure 2. Relations of the potential energy per atom and Lindemann index as a function of temperature for the Ni and Cu nanoparticles with TOC structures.

DownLoad: Full-Size Img PowerPoint

图 3 在200 K, 586原子的Ni_1–xCu_x双金属纳米粒子中Cu的分布随Cu浓度的变化

Figure 3. Variation of the fractional composition of Cu at different surface sites as a function of overall Cu composition for 586 atom nanoparticles at T = 200 K.

DownLoad: Full-Size Img PowerPoint

图 4 Ni, Cu纳米粒子的表面能随原子尺寸的关系

Figure 4. Variation of the surface energy of Ni and Cu nanoparticles as atomic number.

DownLoad: Full-Size Img PowerPoint

图 5 随机和偏析结构的Ni_1–xCu_x双金属纳米粒子的形成热与Cu原子浓度的变化关系. 实线为偏析结构, 虚线为随机结构

Figure 5. The formation energy of Ni_1–xCu_xbimetallic nanoparticles with random and segregation structure varies with the concentration of Cu atom. The solid line is a segregation structure, and the dotted line is a random structure.

DownLoad: Full-Size Img PowerPoint

图 6 在200 K, 586个原子TOC形貌的Ni_1–xCu_x双金属纳米粒子结构. 橘红色和海蓝色的球分别表示Cu原子和Ni原子

Figure 6. Configurations and cross-section snapshots of 586 atom TOC Ni_1–xCu_x nanoparticles at T = 200 K. The orange-red and sea-blue balls represent Cu atoms and Ni atoms, respectively.

DownLoad: Full-Size Img PowerPoint

图 7 在温度T = 200, 400, 600和800 K下, $N_{\rm{Ni}}^{{\rm{surf}}} $和$N_{\rm{Cu}}^{{\rm{bulk}}} $与沉积的Cu原子数的函数关系

Figure 7. The growth of Cu atoms on the TOC Ni substrate with 1289 atoms at T = 200, 400, 600, and 800 K, the $N_{\rm{Ni}}^{{\rm{surf}}} $ and $N_{\rm{Cu}}^{{\rm{bulk}}} $ as a function of the deposited Cu atoms (N_dep).

DownLoad: Full-Size Img PowerPoint

图 8 T = 400 K, Al原子在Ni TOC₁₂₈₉基底上的生长序列　(a) N_dep = 100; (b) N_dep = 200; (c) N_dep = 300; (d) N_dep = 400; (e) N_dep = 500; (f) N_dep = 600. 橘红色和海蓝色的球分别表示Cu原子和Ni原子

Figure 8. Growth sequence of NiCu clusters at T = 400 K. The snapshots of the growth simulation for various N_dep of 100, 200, 300, 400, 500, and 600. The orange-red and sea-blue ball show the Cu and the Ni atom, respectively.

DownLoad: Full-Size Img PowerPoint

图 9 Cu (Ni) 吸附原子在Ni TOC₁₂₈₉ (Cu TOC₁₂₈₉) 基底表面的扩散势垒　(a) Ni-基底 (111)→(100); (b) Ni基底 (111)→(111); (c) Cu基底 (111)→(100); (d) Cu基底 (111)→(111). 橘红色和海蓝色的球分别表示Cu原子和Ni原子

Figure 9. The diffusion energy barrier of Cu adatom on the surface of the Ni TOC1289: (a) Ni-base (111)→(100) facet; (b) Ni-base (111)→(111) facet; (c) Cu-base (111)→(100) facet; (d) Cu-base (111)→(111) facet. The orange-red and sea-blue balls represent Cu atoms and Ni atoms, respectively.

DownLoad: Full-Size Img PowerPoint

图 10 T = 400 K, Ni原子在Cu TOC₁₂₈₉基底上的生长序列　(a) N_dep = 100; (b) N_dep = 200; (c) N_dep = 300. 橘红色和海蓝色的球分别表示Cu原子和Ni原子

Figure 10. Growth sequence of NiCu clusters at T = 400 K: (a) N_dep = 100; (b) N_dep = 200; (c) N_dep = 300. The orange-red and sea-blue ball show the Cu and the Ni atom respectively.

DownLoad: Full-Size Img PowerPoint

表 1 对于586原子的TOC纳米粒子, 内部Cu原子与表面Ni原子交换后构型能差值 (∆E, 单位: eV/atom), 数字6, 7, 8, 9和12分别表示顶点、边缘、(100) 面、(111) 面和体内的位置

Table 1. Configuration energy difference values (∆E, unit: eV/ atom) for a bulk Cu atom exchanging with surface Ni atoms for the TOC nanoparticles of 586 atoms. The numbers 6, 7, 8, 9, and 12 are represent the sites at the vertex, edge, (100) facet, (111) facet, and bulk, respectively

Configuration ∆E/(eV·atom^–1)

12 → 6 –0.395
12 → 7 –0.303
12 → 8 –0.194
12 → 9 –0.149

DownLoad: CSV

map

[1]	Yang J Y, Hu W Y, Dai X Y 2018 Comput. Mater. Sci 154 371 Google Scholar
[2]	Riccardo F, Julius J, Johnston R L 2008 Chem. Rev. 108 845 Google Scholar
[3]	Nguyen N H, Hu A, Persic J, Wen J Z 2011 Chem. Phys. Lett. 503 112 Google Scholar
[4]	Huang R, Wen Y H, Shao G F, Sun S G 2013 J. Phys. Chem. C 117 4278 Google Scholar
[5]	Yang J Y, Hu W Y, Tang J F 2015 Thin Solid Films 593 137 Google Scholar
[6]	Huang R, Wen Y H, Zhu Z Z, Sun S G 2012 J. Phys. Chem. C 116 8664 Google Scholar
[7]	Mobedpour B, Rajabdoust S, Roumina R 2018 Comput. Mater. Sci 151 132 Google Scholar
[8]	Henz B J, Hawa T, Zachariah M 2009 Mol. Simul. 35 804 Google Scholar
[9]	Yang L Y, Gan X L, Xu C, Lang L, Jian Z Y, Xiao S F, Deng H Q, Li X F, Tian Z A, Hu W Y 2019 Comput. Mater. Sci. 156 47 Google Scholar
[10]	Jian L G, Qiang W, Tian L H, Kai W, Cheng H J 2008 Chin. Phys. B 17 3343 Google Scholar
[11]	Yang J Y, Hu W Y, Wu Y Q, Dai X Y 2012 Cryst. Growth Des. 12 2978 Google Scholar
[12]	Yang J Y, Hu W Y, Wu Y R, Dai X Y 2012 Surf. Sci. 606 971 Google Scholar
[13]	Tang J F, Yang J Y 2013 Thin Solid Films 536 318 Google Scholar
[14]	Dai X Y, Hu W Y, Yang J Y, Chen C P 2015 Physica B 458 144 Google Scholar
[15]	Yang J Y, Hu W Y, Tang J F, Dai X Y 2013 Comput. Mater. Sci. 74 160 Google Scholar
[16]	Baletto F, Mottet C, Ferrando R 2002 Phys. Rev. B 66 155420 Google Scholar
[17]	Baletto F, Mottet C, Ferrando R 2003 Phys. Rev. Lett. 90 135504 Google Scholar
[18]	Baletto F, Mottet C, Ferrando R 2003 Eur. Phys. J. D 24 233 Google Scholar
[19]	Baletto F, Mottet C, Rapallo A, Rossi G, Ferrando R 2004 Surf. Sci. 566-568 192
[20]	Deng L, Hu W Y, Deng H Q, Xiao S F 2010 J. Phys. Chem. C 114 11026 Google Scholar
[21]	Deng L, Hu W Y, Deng H Q, Xiao S F, Tang J F 2011 J. Phys. Chem. C 115 11355
[22]	Deng L, Deng H Q, Xiao S F, Tang J F, Hu W Y 2013 Faraday Discuss. 162 293 Google Scholar
[23]	Tang J, Deng L, Deng H, Xiao S, Zhang X, Hu W 2014 J. Phys. Chem. C 118 27850 Google Scholar
[24]	Tang J, Deng L, Xiao S, Deng H, Zhang X, Hu W 2015 J. Phys. Chem. C 119 21515 Google Scholar
[25]	Austin N, Butina B, Mpourmpakis G 2016 Prog. Nat. Sci. 26 487 Google Scholar
[26]	Tripathi A, Hareesh C, Sinthika S, Andersson G, Thapa R 2020 Appl. Surf. Sci. 528 146964 Google Scholar
[27]	Aslan M 2021 Mater. Today. Commun 26 101821 Google Scholar
[28]	Buendia F, Anzaldo A T, Vital C, Beltran M R 2020 J. Chem. Phys. 152 024303 Google Scholar
[29]	Yamauchi T, Tsukahara Y, Sakata T, Mori H, Yanagida T, Kawai T, Wada Y 2010 Nanoscale 2 515 Google Scholar
[30]	Bonet F, Grugeon S, Dupont L, Herrera U R, Guéry C, Tarascon J M 2003 J. Solid State Chem. 172 111 Google Scholar
[31]	Chatterjee J, Bettge M, Haik Y, Jen Chen C 2005 J. Magn. Magn. Mater. 293 303 Google Scholar
[32]	Hristova E, Dong Y, Grigoryan V G, Springborg M 2008 J. Phys. Chem. A 112 7905 Google Scholar
[33]	Xiao K, Qi X, Bao Z, Wang X, Zhong L, Fang K, Lin M, Sun Y 2013 Catal. Sci. Technol 3 1591 Google Scholar
[34]	Quaino P, Belletti G, Shermukhamedov S A, Glukhov D V, Santos E, Schmickler W, Nazmutdinov R 2017 Phys. Chem. Chem. Phys. 19 26812 Google Scholar
[35]	Guisbiers G, Khanal S, Ruiz-Zepeda F, Roque de la Puente J, Jose-Yacaman M 2014 Nanoscale 6 14630 Google Scholar
[36]	Panizon E, Olmos-Asar J A, Peressi M, Ferrando R 2015 Phys. Chem. Chem. Phys. 17 28068 Google Scholar
[37]	Mendes P C D, Justo S G, Mucelini J, Soares M D, Batista K E A, Quiles M G, Piotrowski M J, Da Silva J L F 2019 J. Phys. Chem. C 124 1158
[38]	Hardeveld R, Hartog F 1969 Surf. Sci. 15 189 Google Scholar
[39]	Wang G, Hove M A, Ross P, Baskes M I 2005 Prog. Surf. Sci. 79 28
[40]	Dzhurakhalov A, Marc H 2007 Phys. Rev. B 76 045429 Google Scholar
[41]	Martin T P 1996 Phys. Rep. 273 199 Google Scholar
[42]	Onat B, Durukanoglu S 2013 J. Phys. Condes. Matter 26 035404
[43]	Plimpton S 1995 J. Comput. Phys. 117 1 Google Scholar
[44]	Stukowski A 2010 Model. Simul. Mater. Sci. Eng 18 015012 Google Scholar
[45]	Cleveland C L, Luedtke W D, Landman U 1999 Phys. Rev. B 60 5065 Google Scholar
[46]	Zhi Z, Hu W Y, Xiao S F 2006 Phys. Rev. B 73 125443 Google Scholar
[47]	Huang R, Wen Y H, Zhu Z Z, Sun S G 2012 J. Phys. Chem. C 116 11837
[48]	Mottet C, Rossi G, Baletto F, Ferrando R 2005 Phys. Rev. Lett. 95 035501 Google Scholar
[49]	Feng D, Feng Y, Yuan S, Zhang X, Wang G 2017 Appl. Therm. Eng 111 1457 Google Scholar
[50]	Hamid I, Fang M, Duan H 2015 AIP Adv 5 047129 Google Scholar
[51]	Ding F, Rosén A, Bolton K 2004 Phys. Rev. B 70 075416 Google Scholar
[52]	Wang Q, Wang X, Liu J, Yang Y 2017 J. Nanopart. Res 19 25 Google Scholar
[53]	Vitos L, Ruban A V, Skriver H L, Kollár J 1998 Surf. Sci. 411 186 Google Scholar
[54]	Abbaspour M, Akbarzadeh H, Lotfi S 2018 J. Alloys. Compd. 764 323 Google Scholar
[55]	Wang H, Hu T, Qin J Y, Zhang T 2012 J. Appl. Phys. 112 073520 Google Scholar
[56]	Strohl J K, King T S 1989 J. Catal. 116 540 Google Scholar
[57]	Tang J F, Yang J Y 2013 J. Nanopart. Res 15 2050 Google Scholar
[58]	高明, 邓永和, 文大东, 田泽安, 赵鹤平, 彭平 2020 69 046401 Google Scholar Gao M, Deng Y H, Wen D D, Tian Z A, Zhao H P, Peng P 2020 Acta Phys Sin 69 046401 Google Scholar
[59]	Zhang Y W, Deng Y H, Zeng Q F, Wen D D, Zhao H P, Gao M, Dai X Y, Wu A R 2020 Chin. Phys. B 29 116601 Google Scholar
[60]	张宇文, 邓永和, 文大东, 赵鹤平, 高明 2020 69 136601 Google Scholar Zhang Y W, Dong Y H, Wen D D, Zhao H P, Gao M 2020 Acta Phys Sin 69 136601 Google Scholar

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Vol. 70, Issue 17 - 2021-09-05

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