29
Views
0
CrossRef citations to date
0
Altmetric
Part A: Materials Science

Generation of viable nanocrystalline structures using the melt-cool method: the influence of force field selection

ORCID Icon & ORCID Icon
Pages 205-238 | Received 29 Aug 2023, Accepted 29 Nov 2023, Published online: 14 Dec 2023

References

  • A. Rida, E. Rouhaud, A. Makke, M. Micoulaut, and B. Mantisi, Study of the effects of grain size on the mechanical properties of nanocrystalline copper using molecular dynamics simulation with initial realistic samples. Philos. Mag. 97(27) (2017), pp. 2387–2405.
  • Z.Y. Hou, K.J. Dong, Z.A. Tian, R.S. Liu, Z. Wang, and J.G. Wang, Cooling rate dependence of solidification for liquid aluminium: A large-scale molecular dynamics simulation study. Phys. Chem. Chem. Phys. 18(26) (2016), pp. 17461–17469.
  • A. Mahata, M.A. Zaeem, and M.I. Baskes, Understanding homogeneous nucleation in solidification of aluminum by molecular dynamics simulations. Model. Simul. Mater. Sci. Eng. 26(2) (2018), p. 025007.
  • C.A. Becker, F. Tavazza, Z.T. Trautt, and R.A. Buarque de Macedo, Considerations for choosing and using force fields and interatomic potentials in materials science and engineering. Front. Methods Mater. Simul. 17(6) (2013), pp. 277–283.
  • L.M. Hale, Z.T. Trautt, and C.A. Becker, Evaluating variability with atomistic simulations: The effect of potential and calculation methodology on the modeling of lattice and elastic constants. Model. Simul. Mater. Sci. Eng. 26(5) (2018), p. 055003.
  • S.M. Foiles, M.I. Baskes, and M.S. Daw, Embedded-Atom-Method functions for the Fcc metals Cu, Ag, Au, Ni, Pd, Pt, and their alloys. Phys. Rev. B 33(12) (1986), pp. 7983.
  • G.J. Ackland, G.J. Ackland, G. Tichy, V. Vitek, and M.W. Finnis, Simple N-body potentials for the noble metals and nickel. Philos. Mag. A Phys. Condens. Matter, Struct. Defects Mech. Prop. 56(6) (1987), pp. 735–756.
  • J.B. Adams, S.M. Foiles, and W.G. Wolfer, Self-diffusion and impurity diffusion of fee metals using the five-frequency model and the embedded atom method. J. Mater. Res. 4(1) (1989), pp. 102–112.
  • G.J. Ackland and V. Vitek, Many-body potentials and atomic-scale relaxations in noble-metal alloys. Phys. Rev. B. 41(15) (1990), pp. 10324–10333.
  • Y. Mishin, M.J. Mehl, D.A. Papaconstantopoulos, A.F. Voter, and J.D. Kress, Structural stability and lattice defects in copper: Ab initio, tight-binding, and embedded-atom calculations. Phys. Rev. B – Condens. Matter Mater. Phys. 63(22) (2001), pp. 2241061–22410616.
  • X.W. Zhou, R.A. Johnson, and H.N.G. Wadley, Misfit-energy-increasing dislocations in vapor-deposited CoFe/NiFe multilayers. Phys. Rev. B – Condens. Matter Mater. Phys. 69(14) (2004), p. 144113.
  • M.I. Mendelev, M.J. Kramer, C.A. Becker, and M. Asta, Analysis of semi-empirical interatomic potentials appropriate for simulation of crystalline and liquid Al and Cu. Philos. Mag. 88(12) (2008), pp. 1723–1750.
  • M.I. Mendelev and A.H. King, The interactions of self-interstitials with twin boundaries. Philos. Mag. 93(10–12) (2013), pp. 1268–1278.
  • E. Asadi, M.A. Zaeem, S. Nouranian, and M.I. Baskes, Two-phase solid-liquid coexistence of Ni, Cu, and Al by molecular dynamics simulations using the modified embedded-atom method. Acta Mater. 86 (2015), pp. 169–181.
  • S.A. Etesami and E. Asadi, Molecular dynamics for near melting temperatures simulations of metals using modified embedded-atom method. J. Phys. Chem. Solids 112 (2018), pp. 61–72.
  • S.J. Plimpton, Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117(1) (1995), pp. 1–19.
  • A.P. Thompson, H.M. Aktulga, R. Berger, D.S. Bolintineanu, W.M. Brown, P.S. Crozier, P.J. ‘t Veld, A. Kohlmeyer, S.G. Moore, T.D. Nguyen, et al., LAMMPS – a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comput. Phys. Commun. 271 (2022), p. 108171.
  • A.K. Subramaniyan and C.T. Sun, Continuum interpretation of virial stress in molecular simulations. Int. J. Solids Struct. 45(14) (2008), pp. 4340–4346.
  • A. Stukowski, Visualization and analysis of atomistic simulation data with OVITO–the open visualization tool. Model. Simul. Mater. Sci. Eng. 18(1) (2010), p. 015012.
  • L.S. Morrissey and S. Nakhla, Considerations when calculating the mechanical properties of single crystals and bulk polycrystals from molecular dynamics simulations. Mol. Simul. 46(18) (2020), pp. 1433–1442.
  • G. Simmons and H. Wang, Single Crystal Elastic Constants and Calculated Aggregate Properties: A Handbook. 2nd ed., MIT Press, Cambridge, MA, 1971.
  • D.H. Chung, Elastic moduli of single crystal and polycrystalline MgO. Philos. Mag. 8(89) (1963), pp. 833–841.
  • E. Schmid and B. Walter, Plasticity of Crystals : With Special Reference to Metals, Chapman and Hall, London, 1904-, 1968.
  • R. Hill, The elastic behaviour of a crystalline aggregate. Proc. Phys. Soc. Sect. A. 65(5) (1952), pp. 349–354.
  • C.M. Kube and M. de Jong, Elastic constants of polycrystals with generally anisotropic crystals. J. Appl. Phys. 120(16) (2016), p. 165105.
  • R. deWit, Elastic constants and thermal expansion averages of a polycrystal. J. Mech. Mater. Struct. 3(2) (2008), pp. 195–212.
  • H. Wern, N. Koch, and T. Maas, Self-Consistent calculation of the X-ray elastic constants of polycrystalline materials for arbitrary crystal symmetry. Mater. Sci. Forum. 404–407 (2002), pp. 127–132.
  • T. Gnäupel-Herold, A.A. Creuziger, and M. Iadicola, A model for calculating diffraction elastic constants. J. Appl. Crystallogr. 45(2) (2012), pp. 197–206.
  • V.A. Lubarda, New estimates of the third-order elastic constants for isotropic aggregates of cubic crystals. J. Mech. Phys. Solids 45(4) (1997), pp. 471–490.
  • M. Tane, K. Yamori, T. Sekino, and T. Mayama, Impact of grain shape on the micromechanics-based extraction of single-crystalline elastic constants from polycrystalline samples with crystallographic texture. Acta Mater. 122 (2017), pp. 236–251.
  • M.S. Daw and M.I. Baskes, Embedded-atom method: derivation and application to impurities, surfaces, and other defects in metals. Phys. Rev. B. 29(12) (1984), pp. 6443–6453.
  • B.J. Lee, M.I. Baskes, H. Kim, and Y. Koo Cho, Second nearest-neighbor modified embedded atom method potentials for Bcc transition metals. Phys. Rev. B. 64(18) (2001), p. 184102.
  • B.J. Lee, J.H. Shim, and I. Baskes, Semiempirical atomic potentials for the Fcc metals Cu, Ag, Au, Ni, Pd, Pt, Al, and Pb based on first and second nearest-neighbor modified embedded atom method. Phys. Rev. B – Condens. Matter Mater. Phys. 68(14) (2003), p. 144112.
  • I.E. Leksina and S.I. Novikova, Investigation of thermal Expn. of Cu, Ag and Au in a wide range of temperatures. Sov. Phys.-Solid State 5 (1963), pp. 798–780.
  • F.C. Nix and D. MacNair, The thermal expansion of pure metals: Copper, gold, aluminum, nickel, and iron. Phys. Rev. 60(8) (1941), pp. 597–605.
  • C. Lenihan, A Molecular Dynamics Exploration of the Properties of Bulk and Nanosized Single-Crystal Copper, University of Limerick, Limerick, 2011.
  • S. Bogatyrenko and A. Kryshtal, Thermal expansion coefficients of Ag, Cu and diamond nanoparticles: In situ TEM diffraction and EELS measurements. Mater. Charact. 178 (2021), p. 111296.
  • J.R. Morris, C.Z. Wang, K.M. Ho, and C.T. Chan, Melting line of aluminum from simulations of coexisting phases. Phys. Rev. B. 49(5) (1994), pp. 3109–3115.
  • J.R. Morris and X. Song, The melting lines of model systems calculated from coexistence simulations. J. Chem. Phys. 116(21) (2002), pp. 9352–9358.
  • N. Joshi, N. Mathur, T. Mane, and D. Sundaram, Size effect on melting temperatures of alumina nanocrystals: molecular dynamics simulations and thermodynamic modeling. Comput. Mater. Sci. 145 (2018), pp. 140–153.
  • D.G. Ellingsen, N. Horn, and J. Aaseth, Chapter 26 – Copper, in Handbook on the Toxicology of Metals, 3rd ed., G.F. Nordberg, B.A. Fowler, M. Nordberg, and L.T. Friberg, eds., Academic Press, Burlington, 2007. pp. 529–546.
  • S.M. Handrigan and S. Nakhla, Examination of critical grain size of isotropic nanocrystalline iron through molecular dynamics analysis. Mol. Simul. 48(11) (2022), pp. 976–990.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.