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Model for the Solid-Liquid Interfacial Free Energy at High Pressures
Dane M Sterbentz1,2, Philip C Myint1, Jean-Pierre Delplanque2
1Lawrence Livermore National Laboratory, Livermore, California 94550, United States.
This study presents a new model for solid-liquid interfacial free energy applicable to extreme conditions. The model accurately predicts solidification kinetics in dynamic-compression experiments, improving classical nucleation theory (CNT) applications.
Area of Science:
- Materials Science
- Physical Chemistry
- Thermodynamics
Background:
- Interfacial free energy is crucial for modeling solidification kinetics via classical nucleation theory (CNT).
- Existing models often rely on equilibrium or near-ambient pressure assumptions, limiting their applicability.
- Non-equilibrium conditions, like high pressures in dynamic-compression experiments, necessitate advanced modeling approaches.
Purpose of the Study:
- To derive a robust solid-liquid interfacial free-energy model for high-pressure, non-equilibrium conditions.
- To incorporate atom-pair interaction enthalpies and interface roughness using the Temkin n-layer model.
- To validate the model's applicability to diverse materials, specifically water and gallium.
Main Methods:
- Developed a new interfacial free-energy model considering interaction enthalpies and multilayer interface disorder.
- Applied the Temkin n-layer model to account for interface roughness.
- Integrated the model into CNT-based simulations for solidification kinetics.
Main Results:
- The derived model successfully predicts solidification kinetics under high-pressure dynamic-compression conditions.
- Simulations for water solidifying to ice VII showed good agreement with experimental data.
- The model demonstrates applicability to various materials with minimal empirical fitting.
Conclusions:
- The new interfacial free-energy model overcomes limitations of equilibrium-based approaches.
- It provides accurate predictions for non-equilibrium solidification phenomena.
- This work enhances the predictive power of CNT for materials under extreme conditions.
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