(500e) Enthalpy Landscape Analysis for Calculating the Melting Temperature of a Material | AIChE

(500e) Enthalpy Landscape Analysis for Calculating the Melting Temperature of a Material


Nieves, A. M. - Presenter, University of Pennsylvania
Vitek, V. - Presenter, University of Pennsylvania
Sinno, T. R. - Presenter, University of Pennsylvania

There is still an open debate on the mechanisms that drive melting in crystalline materials. Under most experimental conditions, melting originates from surfaces or grain boundaries, which have a lower melting temperature than the bulk defect-free material; this is also known as heterogeneous melting. On the other hand, in computer simulations and some experiments [1], a crystal can be superheated (i.e. it remains in the solid phase at temperatures higher than the heterogeneous melting temperature). Even though several studies have focused on measuring the maximum superheating temperature of a material, there is still no consensus in the literature on the actual mechanism that leads to homogeneous (bulk material) melting [2].

In previous computational investigations, stable structures in a super-cooled liquid [3], glass [4] and solid [5] material were obtained by sampling the energetic landscape using the inherent structure approach [6]. Here we use this approach to obtain the solid phase density of states of two materials, silicon (using the EDIP interaction potential [7]) and aluminum (using an EAM interaction potential [8]), by employing molecular dynamics simulations in the NPT ensemble. Within each simulation, atomic coordinates are stored at periodic intervals and used to calculate the formation enthalpy of the current structure by employing a conjugate gradient routine to minimize the enthalpy at a constant hydrostatic pressure. A probability distribution of states as a function of formation enthalpy is derived from these results and is used to generate the density of states of the material [5].

Our results demonstrate that the number of states in the material grows exponentially with increasing formation enthalpy of the defective structures in the crystal lattice. An effective temperature can be extracted from the slope of the density of states [5] and we show that for both, silicon and aluminum, this corresponds to the maximum superheating temperature of the material. The method developed here provides a simple and robust technique to measure the melting temperature of a material as a function of applied mechanical stress, impurity concentrations, and defect distributions including surfaces, dislocations, and grain boundaries.


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[4] P. G. Debenedetti and F. H. Stillinger, Nature 410, 259 (2001).

[5] S. S. Kapur, M. Prasad, J. C. Crocker, and T. Sinno, Phys. Rev. B 72, 014119 (2005).

[6] F. H. Stillinger and T. A. Weber, Phys. Rev. A 25, 978 (1982).

[7] J. F. Justo, M. Z. Bazant. E. Kaxiras, V. V. Bulatov, and S. Yip, Phys. Rev. B 58, 2539 (1998).

[8] M. I. Mendelev, M. J. Kramer, C. A. Becker, and M. Asta, Philosophical Magazine 88, 1723 (2008).