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Simple Method of Including Density Variation in Quantitative Continuum Phase-Change Models.
1Canadian Nuclear Laboratories, Chalk River, K0J 1J0 Ontario, Canada.
Physical Review Letters
|March 4, 2022
Summary
This study introduces a new method for modeling density and pressure changes in phase-change materials, enabling accurate predictions of material behavior based on composition and temperature. The approach enhances simulations of nanoparticle equilibrium and growth.
Area of Science:
- Computational materials science
- Thermodynamics
- Continuum mechanics
Background:
- Continuum phase-change models often simplify density and pressure variations.
- Accurately capturing these variations is crucial for simulating material behavior, especially at the nanoscale.
- Existing models may lack thermodynamic self-consistency in handling composition and phase changes.
Purpose of the Study:
- To develop a thermodynamically self-consistent method for incorporating density and pressure variations into continuum phase-change models.
- To generalize lattice constraints in thermodynamic potentials to allow for composition, temperature, and phase-dependent specific volumes.
- To validate the new formalism by comparing simulation results with established models.
Main Methods:
- Developed a quantitative method based on Eulerian formulation where local dilation is determined by species concentration.
- Introduced a hyperelastic contribution to the thermodynamic potential.
- Implemented the formalism in phase-change models and compared results against models with traditional lattice constraints.
Main Results:
- The proposed method successfully captures density and pressure variations in a thermodynamically consistent manner.
- The formalism allows for composition, temperature, and phase-dependent specific volumes, generalizing lattice constraints.
- Simulations of Ni-Cu nanoparticle equilibrium and dendritic growth showed differences compared to models with fixed lattice constraints, highlighting the impact of variable specific volumes.
Conclusions:
- The presented method offers a simple, quantitative, and thermodynamically robust approach for phase-change modeling.
- This formalism improves the accuracy of simulations involving composition and temperature-driven volume changes.
- The findings are significant for understanding and predicting the behavior of materials undergoing phase transitions, particularly nanoparticles.
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