Third generation CALPHAD databases by automated statistical regression analysis
Irina Roslyakova, Ruhr-Universität Bochum, Bochum, Germany
The aim of the third generation of CALPHAD databases is to develop an accurate physically-based description of Gibbs energies of pure elements from 0K up to high temperatures that can guarantee a robust prediction of thermodynamic properties of binary, ternary and high-order systems within a wide composition range. Recently, a novel thermodynamic modeling strategy of stable, metastable and liquid phases has been established based on segmented regression approach and it considers several physical effects, which could be activated in low and high temperatures depending on the properties of the studied elements and systems. The segmented regression model has been applied for 18 pure elements, five compounds, two binary and one ternary phase from 0K and demonstrated a good agreement with available experimental data in low and high temperatures. Moreover, a significant improvement of thermodynamic description and predictive capability of the CALPHAD method has been achieved.
Session M3: Moday, 25 June 2018
End: 06:00 p.m.