Scientific visualization of an extremely large simulation of a Rayleigh–Taylor instability problem.
Computational thermodynamics is the use of computers to simulatethermodynamic problems specific tomaterials science, particularly used in the construction of phase diagrams.[1][2]
Several open and commercial programs exist to perform these operations. The concept of the technique is minimization ofGibbs free energy of the system; the success of this method is due not only to properly measuring thermodynamic properties, such as those in thelist of thermodynamic properties, but also due to the extrapolation of the properties of metastableallotropes of thechemical elements.
The computational modeling of metal-based phase diagrams, which dates back to the beginning of the previous century mainly byJohannes van Laar and to the modeling ofregular solutions, has evolved in more recent years to theCALPHAD (CALculation of PHAse Diagrams).[3] This has been pioneered by Americanmetallurgist Larry Kaufman since the 1970s.[4][5][6]
Computational thermodynamics may be considered a part ofmaterials informatics and is a cornerstone of the concepts behind thematerials genome project. While crystallographic databases are used mainly as a reference source, thermodynamic databases represent one of the earliest examples of informatics, as these databases were integrated intothermochemical computations to map phase stability in binary and ternaryalloys.[7] Many concepts and software used in computational thermodynamics are credited to the SGTE Group, aconsortium devoted to the development of thermodynamic databases; the open elements database is freely available[8] based on the paper by Dinsdale.[9] This so-called "unary" system proves to be a common basis for the development of binary and multiple systems and is used by both commercial and open software in this field.
However, as stated in recent[when?] CALPHAD papers and meetings, such a Dinsdale/SGTE database will likely need to be corrected over time despite the utility in keeping a common base. In this case, most published assessments will likely have to be revised, similarly to rebuilding a house due to a severely broken foundation. This concept has also been depicted as an "inverted pyramid."[10] Merely extending the current approach (limited to temperatures above room temperature) is a complex task.[11] PyCalphad, aPython library, was designed to facilitate simple computational thermodynamics calculation usingopen source code.[12] In complex systems, computational methods such as CALPHAD are employed to model thermodynamic properties for each phase and simulate multicomponent phase behavior.[13] The application of CALPHAD to high pressures in some important applications, which are not restricted to one side of materials science like theFe-C system,[14] confirms experimental results by using computational thermodynamic calculations of phase relations in the Fe–C system at high pressures. Other scientists even consideredviscosity and other physical parameters, which are beyond the domain of thermodynamics.[15]
There is still a gap between ab initio methods[16] and operative computational thermodynamics databases. In the past, a simplified approach introduced by the early works of Larry Kaufman, based onMiedema's Model, was employed to check the correctness of even the simplestbinary systems. However, relating the two communities toSolid State Physics andMaterials Science remains a challenge,[17] as it has been for many years.[18] Promising results from ab initioquantum mechanics molecular simulation packages likeVASP are readily integrated in thermodynamic databases with approaches like Zentool.[19]
A relatively easy way to collect data for intermetallic compounds is now possible by using Open Quantum Materials Database. A series of papers focused on the concept of Zentropy has been proposed by prof. Z.K. Liu and his research group has been recently proposed.[20]
^Fabrichnaya, Olga B.; Saxena, Surendra K.; Richet, Pascal; Westrum, Edgar F. (2004).Thermodynamic Data, Models, and Phase Diagrams in Multicomponent Oxide Systems. Data and Knowledge in a Changing World.doi:10.1007/978-3-662-10504-7.ISBN978-3-642-05730-4.[page needed]
^L Kaufman and H Bernstein, Computer Calculation of Phase Diagrams, Academic Press N Y (1970)ISBN0-12-402050-X[page needed]
^N Saunders and P Miodownik, Calphad, Pergamon Materials Series, Vol 1 Ed. R W Cahn (1998)ISBN0-08-042129-6[page needed]
^H L Lukas, S G Fries and B Sundman, Computational Thermodynamics, the Calphad Method, Cambridge University Press (2007)ISBN0-521-86811-4[page needed]
^L., Lukas, H. (2007).Computational thermodynamics : the CALPHAD method. Fries, Suzana G., Sundman, Bo. Cambridge: Cambridge University Press.ISBN978-0521868112.OCLC663969016.{{cite book}}: CS1 maint: multiple names: authors list (link)
^Fei, Yingwei; Brosh, Eli (2014). "Experimental study and thermodynamic calculations of phase relations in the Fe–C system at high pressure".Earth and Planetary Science Letters.408:155–62.Bibcode:2014E&PSL.408..155F.doi:10.1016/j.epsl.2014.09.044.
^Zhang, Fan; Du, Yong; Liu, Shuhong; Jie, Wanqi (2015). "Modeling of the viscosity in the AL–Cu–Mg–Si system: Database construction".Calphad.49:79–86.doi:10.1016/j.calphad.2015.04.001.
^Turchi, P. A. (14 April 2004). AB INITIO AND CALPHAD THERMODYNAMICS OF MATERIALS (Report).OSTI15014097.
^Miedema, A. R.; Rathenau, G. W., eds. (2016).Proceedings of the International Symposium on Thermodynamics of Alloys: Delft, The Netherlands, June 12-13, 1980. Elsevier.ISBN978-1-4832-7801-8.[page needed]
^Liu, Zi-Kui (September 2023). "Thermodynamics and its prediction and CALPHAD modeling: Review, state of the art, and perspectives".Calphad.82 102580.doi:10.1016/j.calphad.2023.102580.OSTI1987742.
Miodownik, Peter (2012). "Working with Larry Kaufman: Some thoughts on his 80th birthday".Calphad.36:iii–iv.doi:10.1016/j.calphad.2011.08.008.
Kaufman, Larry; Ågren, John (2014). "CALPHAD, first and second generation – Birth of the materials genome".Scripta Materialia.70:3–6.doi:10.1016/j.scriptamat.2012.12.003.
