Source: https://lettersonmaterials.com/en/Readers/Article.aspx?aid=1088
Timestamp: 2019-04-20 10:16:16+00:00

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The study of the surface free energy (SFE) of metal at nanoscale is far from consummation, and different approaches may lead to the different results. Despite the extensive investigations, there is still a need for a complete model for the surface energy of metallic nanoparticles which will be able to take into account effects of the particle size and shape. Most studies emphasize the size dependence of the melting characteristics, rather than considering the lattice deformation and the surface energy of nanoclusters. This research aimed at computation of SFE of copper nanoclusters depending on temperature over a wide range of sizes, containing 147 to 10179 atoms. We employed molecular dynamics simulation by using the embedded atom model and tight-binding Cleri-Rosato potential. Calculations were carried out on icosahedral Cu nanocluster with full-closed surface. This is the most stable shape in our range of sizes. Results of two series of computer experiments, made using the two interatomic potentials in LAMMPS program and our own software, have a notable agreement between themselfs. The results demonstrated that surface free energy decreases with increasing of cluster size, but rises with elevating of the temperature. Distribution of potential energy upon the inner and surface atoms of particles of various sizes is illustrated. In addition, it was revealed that for larger nanoclusters, SFE is more sensitive to variation of temperature than the small nanoparticles. These results seem to be of prime importance in understanding and manipulating of the desired properties of copper nanoparticles in industrial applications.
1. Shen Ping et al. J. Phys. Chem. C. 120 (16), 8900 - 8906 (2016).
2. A. V. Kalenskii, A. A. Zvekov, A. P. Nikitin, M. V. Anan’eva. Russian Physics Journal. 58 (8), 1098 (2015).
3. S. Chowdhury, V. R. Bhethanabotla, R. Sen. Appl. Phys. Lett. 95 (13), 131115 (2009).
4. W. Li, F. Chen. J. Nanopart. Res. 15 (7), 1809 (2013).
5. F. Bechstedt. Principles of surface physics. 4th ed. New York: Springer, (2003) 342 p.
6. K. Nanda, et al. Phys. Rev. Lett. 91 (10), 106102 (2003).
7. R. Dingreville, J. Qu, C. Mohammed. J. Mech. Phys. Solids. 53 (8), 1827 (2005).
8. A. I. Rusanov. Thermodynamics of surface phenomena [in Russian], Leningrad: Izd. LGU, (1960) 181 p.
9. A. I. Rusanov. Surf. Sci. Rep. 37 (25), 111 (2003).
10. L. M. Shcherbakov. General theory of capillary effects of the second type. in: Research in the Field of Surface Forces [in Russian], Moscow.: Izd. Akad. Nauk SSSR, (1961), pp. 28 - 37.
11. V. M. Samsonov, N. Yu. Sdobnyakov, A. N. Bazulev. Colloids and Surf. A. 239, 113 (2004).
12. J.-M. Zhang, F. Ma, K.-W. Xu. Appl. Surf. Sci. 229 (1), 34 (2004).
13. E. Aghemenloh, et al. Comput. Mater. Sci. 50 (12), 3290 (2011).
14. X. Wang, et al. Surface Science. 551 (3), 179 (2004).
15. R. Shuttleworth. Proc. Phys. Soc. A. 63 (5), 444 (1950).
16. G. Ouyang, X. Tan, G. Yang. Phys. Rev. B. 74 (19), 195408 (2006).
17. B. Medasani, Y. H. Park, I. Vasiliev. Phys. Rev. B. 75 (23), 235436 (2007).
18. M. Kabir, A. Mookerjee, A. Bhattacharya. Phys. Rev. A. 69 (4), 043203 (2004).
19. V. S. Myasnichenko, M. D. Starostenkov, Appl. Surf. Sci. 260, 51 (2012).
20. V. S. Myasnichenko, P. M. Ershov, N. Yu. Sdobnyakov, D. N. Sokolov. Physical and chemical aspects of the study of clusters, nanostructures and nanomaterials: Interuniver. coll. proceed. 7, 378 (2015) [in Russian].
21. M. S. Daw, M. I. Baskes. Phys. Rev. B. 29 (12), 6443 (1984).
22. S. Plimpton. J. Comp. Phys. 117 (1), 1 (1995).
23. Large-scale Atomic / Molecular Massively Parallel Simulator. Available online from: http://lammps.sandia.gov.
24. F. Cleri and V. Rosato. Phys. Rev. B: Condens. Matter Mater. Phys., 48 (1), 22 (1993).
25. V. S. Myasnichenko. ClusterEvolution. Certificate of Russian state registration of the computer program № 2011615692. July 20, 2011.
26. J.-M. Zhang, F. Ma, K.-W. Xu. Appl. Surf. Sci. 229 (1-4) 34 (2004).
27. F. Taherkhani, H. Akbarzadeh, H. Rezania. J. Alloys Compd. 617, 746 (2014).
28. S. Ali, V. S. Myasnichenko, E. C. Neyts. Phys. Chem. Chem. Phys. 18, 792 (2016).
29. I. Stich, R. Car, M. Parrinello and S. Baroni. Phys. Rev. B. 39 (8), 4997 (1989).
30. S. Nose. J. Chem. Phys. 81 (1), 511 (1984).
31. W. G. Hoover. Phys. Rev. A. 31 (3), 1695 (1985).
32. C. B. Barber, D. P. Dobkin and H. Huhdanpaa. ACM Trans. on Mathematical Software, 22 (4), 469 (1996).
33. Qhull: computational code for calculating surface area, volume etc. Available online from: http://www.qhull.org.
34. J. D. Honeycut, H. C. Andersen. J. Phys. Chem. 91, 4950 (1987).
35. A. Stukowski. Modell. Simul. Mater. Sci. Eng. 18, 015012 (2010).
36. E. H. Abdul-Hafidh, B. Aïssa. Appl. Surf. Sci. 379, 411 (2016).
37. L. Wang, Y. Zhang, X. Bian, Y. Chen. Phys. Lett. A. 310, 197 (2003).

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