Welcome to Computational Thermodynamics
Why Computer Simulations and CALPHAD Method?
In order to fulfill all the requirements under service conditions, modern alloys have to be based on very complex multi-component systems, where simplifying assumptions can no longer be made. The thermodynamic properties — which control driving forces, boundary conditions, and kinetic parameters — are complex functions of temperature and chemical composition. Computational approach has emerged and established itself as the most efficient way of designing and studying complex, modern alloys.
Most alloys undergo one or more phase transformations (during processing and/or during use) which are best understood through the use of phase diagrams. Experimentally determined phase diagrams, however, are usually available for binary systems only (e.g., Co-Cr, Fe-C, Fe-Co, Fe-Cr, Fe-Mn, Fe-Mo, Fe-Ni, Fe-Ti, Fe-V, Ni-Cr, Ti-Al, Ti-B, Ti-N, etc), to some extent for ternary systems (e.g., Fe-Cr-C, W-Co-C, W-Fe-C, W-Ni-C, etc), and very rarely for higher-order systems. This is where the CALPHAD (CALculation of PHAse Diagrams) method comes in.
The CALPHAD method is based of the fact that a phase diagram is a representation of the thermodynamic properties of a system. Thus, if the thermodynamic properties are known, it would be possible to calculate the multi-component phase diagrams. Thermodynamic descriptions of lower order systems (e.g., the Gibbs energy of each phase) are combined to extrapolate higher order systems.
Finally, the expense of conducting experiments in materials science or metallurgical engineering is often prohibitively high. In many cases, using the experimental route to solve complex metallurgical problems can be more time-consuming and costly for a particular company than they are worth. The cost-benefit picture, however, changes if such problems could be solved numerically (sometimes in just a couple of hours) using computational tools such as Thermo-Calc, DICTRA, JMatPro, FactSage, Pandat, MTDATA, etc.
The Value Proposition
The greatest value of computational thermodynamics is its ability to enable users to model and numerically solve a vast number of different materials-related engineering problems. The problems that can be solved successfully can be extremely complex. For example, attempting to analyze all the possible interactions that can take place in a problem involving up to, say, ten or fifteen alloying elements at a given temperature (or as a function of a temperature) can be a huge engineering undertaking. These and similar types of problems can usually be solved experimentally, but the time required to do so can be significantly longer (sometimes even several orders of magnitude longer) than if solved using computer simulations.
The computational approach has become more reliable and vastly more rapid and efficient than the old-fashion approach that is based solely upon experimental trial-and-error methods, as the application of tools such as Thermo-Calc, DICTRA, JMatPro, FactSage, Pandat, and MTDATA reduces the need for new costly experiments. The results of an experiment can now be predicted, thus limiting the number of experiments that eventually have to be made. In some instances the computational approach alone may produce results reliable enough to be used directly.
Share Your Experience and Knowledge
We invite both the developers and the end-uses of Thermo-Calc, DICTRA, JMatPro, FactSage, Pandat, and MTDATA to submit articles and/or examples that are preferably focused on how to calculate and use sophisticated multi-component phase diagrams to solve various practical problems related to metallic materials such as carbon steels, stainless steels, tool steels, high-speed steels, nickel-base alloys, titanium-base alloys, titanium-aluminides, aluminum-base alloys, as well as exotic alloys.
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