Melting of a polycrystalline material

Belonoshko, Anatoly B.; Lukinov, Timofei; Burakovsky, Leonid; Preston, Dean L.; Rosengren, Anders

doi:10.1140/epjst/e2013-01743-1

Cited by 12 publications

(5 citation statements)

References 12 publications

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“…The corresponding pressure-temperature relation follows approximately the shape of the letter Z, explaining the name of the method. Even though the Z method has been successfully applied to a few systems [22][23][24][25], its strong dependence on simulation size and length are still a matter of debate [27,[32][33][34]. Table I shows that in the last decade there was a strong focus on the coexistence approach and the Z method.…”

Section: Introductionmentioning

confidence: 99%

Efficient approach to compute melting properties fully from ab initio with application to Cu

2017

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Applying thermodynamic integration within an ab initio-based free-energy approach is a state-of-the-art method to calculate melting points of materials. However, the high computational cost and the reliance on a good reference system for calculating the liquid free energy have so far hindered a general application. To overcome these challenges, we propose the two-optimized references thermodynamic integration using Langevin dynamics (TOR-TILD) method in this work by extending the two-stage upsampled thermodynamic integration using Langevin dynamics (TU-TILD) method, which has been originally developed to obtain anharmonic free energies of solids, to the calculation of liquid free energies. The core idea of TOR-TILD is to fit two empirical potentials to the energies from density functional theory based molecular dynamics runs for the solid and the liquid phase and to use these potentials as reference systems for thermodynamic integration. Because the empirical potentials closely reproduce the ab initio system in the relevant part of the phase space the convergence of the thermodynamic integration is very rapid. Therefore, the proposed approach improves significantly the computational efficiency while preserving the required accuracy. As a test case, we apply TOR-TILD to fcc Cu computing not only the melting point but various other melting properties, such as the entropy and enthalpy of fusion and the volume change upon melting. The generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and the local-density approximation (LDA) are used. Using both functionals gives a reliable ab initio confidence interval for the melting point, the enthalpy of fusion, and entropy of fusion.

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Section: Introductionmentioning

confidence: 99%

Efficient approach to compute melting properties fully from ab initio with application to Cu

2017

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“…MD was successfully applied to examine the effects of size on the melting behavior of metallic nanoparticles [ [113]], nanowires [[114]- [117]] and thin films [ [118], [119]] also confined in between other materials [[120]- [122]]. Simulations were also performed for bulk nanocrystalline metals [ [123]].…”

Section: Multiscale Modelling Of Diffusion-controlled Phenomena In Co...mentioning

confidence: 99%

Modeling of Size Effects in Diffusion Driven Processes at Nanoscale - Large Atomic and Mesoscale Methods

Wejrzanowski

Kurzydłowski

2017

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The results of the studies presented here are devoted to understanding of microstructure effect on the processes and properties driven by diffusion. The role of various interfaces (intergranular, phase, free surface), as the high-energy defects, is underlined and investigated with special attention. The methodology relevant to analyses of the microstructural processes is first briefly presented. The capability and limitations of classical molecular dynamics, mesoscale Monte Carlo and cellular automaton techniques are described. Two examples of the diffusion driven processes analyzed at various length and time scale are shown: namely, grain growth in nanometallic materials and melting of thin embedded films. The modeling results are also accompanied with experimental studies. Thanks to application of numerical methods, models of relevant processes were proposed, which enabled to provide quantitative relationships between microstructure and the process kinetics. Such relationships can be later used for design of optimized materials for wide range of applications.

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“…(c) The fast-heating method (or so-called Z method) [26]: A solid is gradually heated until it melts, based 15 on N V E MD simulations. While this approach is applicable to a small system, recent studies suggest that long simulations and corrections for finite simulation time might be needed to achieve the required precision [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

A user guide for SLUSCHI: Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces

Hong

2016

Calphad

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Although various approaches for melting point calculations from first principles have been proposed and employed for years, their practical implementation has hitherto remained a complex and time-consuming process. The SLUSCHI code (Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces) drastically simplifies this procedure into an automated package, by implementing the recently-developed small-size coexistence method and putting together a series of steps that lead to final melting point evaluation. Based on density functional theory, SLUSCHI employs Born-Oppenheimer molecular dynamics techniques under the isobaric-isothermal (N P T) ensemble, with interface to the first-principles code VASP. In order to make this useful code available to a wide community of researchers who could benefit from it, this article outlines the procedure to perform melting point calculations, and presents a detailed user guide to the code.

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Melting of a polycrystalline material

Cited by 12 publications

References 12 publications

Efficient approach to compute melting properties fully from ab initio with application to Cu

Efficient approach to compute melting properties fully from ab initio with application to Cu

Modeling of Size Effects in Diffusion Driven Processes at Nanoscale - Large Atomic and Mesoscale Methods

A user guide for SLUSCHI: Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces

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