J. Bouhattate

Contribution of the entropy on the thermodynamic equilibrium of vacancies in nickel.

The equilibrium vacancy concentration in nickel was determined from ab initio calculations performed with both generalized gradient approximation and local density approximation up to the melting point. We focus the study on the vacancy formation entropy expressed as a sum of a vibration and an electronic contribution, which were determined from the vibration modes and the electronic densities of states. Applying a method based on the quasi-harmonic approximation, the temperature dependence of the defect formation energy and entropy were calculated. We show that the vibrations of the first shell of atoms around the defect are predominant to the vibration formation entropy. On the other hand, the electronic formation entropy is very sensitive to the exchange-correlation potential used for the calculations. Finally, the vacancy concentration is computed at finite temperature with the calculated values for the defect formation energy and entropy. In order to reconcile point-defects concentration obtained with our calculations and experimental data, we conducted complementary calorimetric measurements of the vacancy concentration in the 1073-1273 K temperature range. Close agreement between theory and experiments at high temperature is achieved if the calculations are performed with the generalized gradient approximation and both vibration and electronic contributions to the formation entropy are taken into account.

Processing Path Model to Describe Texture Evolution during Mechanical Processing

Using a processing path model based on the conservation principle in the orientation space explicit solutions can be formed linking any final (desired) microstructure to a given initial state for polycrystalline materials. The model uses texture coefficients in spherical harmonics expansion to as materials descriptors to represent the texture state of polycrystalline materials. In this work, the effect of increasing the maximum number of texture coefficients used in the series expansion (represented by Lmax) on the prediction of texture and its accuracy is fully studied.