Predicting solute segregation kinetics and properties in binary alloys from a dynamical variational gaussian model
The thermodynamics and kinetics of solute segregation in crystals is important for controlling microstructure and properties. Prime examples are the effects of solute drag on interface migration and of static strain aging on the yield stress. A fully quantitative prediction of solute segregation is difficult, however, due to the spatially varying solute-defect binding energies that are atomic in origin. Moreover, as solute segregation enhances (locally) the solute concentration, dilute approximations for the underlying thermodynamics and kinetics become questionable.
We present a dynamical version of the variational gaussian method for binary alloys [1] and illustrate its potential for select problems involving solute segregation including static strain aging in Al-Mg alloys [2]. Our model adapts the recently proposed Diffusive Molecular Dynamics (DMD) model for vacancy diffusion in crystals where a phonon- free description of solids is coupled with statistical averaging over various configurations to allow for the efficient calculation of free energies. In the alloy version of the model, the free energy is minimized by optimizing the atomic positions and vibrational amplitudes while relaxational dynamics are used to evolve the solute concentration field based on the local energy landscape. We show that this model successfully describes solute redistribution over diffusive timescales. In contrast to traditional continuum diffusion treatments, atomistic effects are automatically accounted for, and full kinetic pathways of the evolution of material properties are revealed in addition to the equilibrium properties.
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Dr. Chad W. Sinclair
Associate Professor
University of British Columbia
Department of Materials Engineering
Vancouver Campus
Frank Forward Building
309-6350 Stores Road
Vancouver, BC Canada V6T 1Z4
Phone | +1 604 822 3352 |
Prof. C. Sinclair | |
Http | UBC Materials Engineering |
Alloy Design : Sinclair Research Group |