Literature DB >> 33071299

The need for reliable data in computational thermodynamics.

Ursula R Kattner1.   

Abstract

Computational methods have become indispensable tools for efficient development and processing of new materials and have led to the new discipline of integrated computational materials engineering (ICME). The CALPHAD (calculation of phase diagrams) method has been identified as one of the pillars of ICME. The CALPHAD method, originally developed to model thermodynamic properties and phase diagrams, uses extrapolation methods for the functions of binary and ternary systems that enable the calculation of the properties of higher order systems. The CALPHAD functions are built to a large extent on available experimental data for these binary and ternary systems. To ensure reliability of the results from CALPHAD calculations, it is necessary to critically evaluate the experimental data that are being used for developing the CALPHAD functions. This review presents a brief overview of the CALPHAD method and its models, summarizes the data that are needed and the criteria that need to be applied for the evaluation of these data.

Entities:  

Keywords:  CALPHAD; computational data; computational thermodynamics; experimental data; phase equilibria data; thermochemical data; thermophysical data

Year:  2020        PMID: 33071299      PMCID: PMC7558216     

Source DB:  PubMed          Journal:  High Temp High Press        ISSN: 0018-1544            Impact factor:   0.571


  2 in total

1.  Potential of mass spectrometry for the analysis of inorganic high-temperature vapors.

Authors:  K Hilpert
Journal:  Fresenius J Anal Chem       Date:  2001-07

2.  ThermoData Engine (TDE): software implementation of the dynamic data evaluation concept. 9. Extensible thermodynamic constraints for pure compounds and new model developments.

Authors:  Vladimir Diky; Robert D Chirico; Chris D Muzny; Andrei F Kazakov; Kenneth Kroenlein; Joseph W Magee; Ilmutdin Abdulagatov; Michael Frenkel
Journal:  J Chem Inf Model       Date:  2013-11-27       Impact factor: 4.956

  2 in total

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