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proach of experiments, first-principles calculations and CALPHAD
modelling have been used to obtain thermodynamic descriptions
of the constituent binary and ternary systems. In total, 147 of the
binary systems in this 26-element framework have been assessed to
their full range of composition. TCAL1 also contains assessments of
58 ternaries in the Al-Cu-Fe-Mg-Mn-Ni-Si-Zn system. In addition,
twelve quaternaries and one quinary system have been assessed.
MOBAL2 is a kinetic database containing mobility data for the
liquid and fcc phases in Al-based alloys within a 23-element framework
[Al, Cu, Fe, Mg, Mn, Ni, Si, Zn, Cr, Ge, Sn, Sr, Ti, V, Zr, Ag,
Ca, Hf, K, La, Li, Na, Sc]. For the FCC phase, the database contains
assessed impurity diffusion data in Al for all included elements. It
also includes complete and critical assessments in some important
binary systems. As for liquid, there are also assessed data for diffusion
in liquid Al for Al, Cr, Cu, Fe, Ge, Mg, Mn, Ni, Si, Ti, V, and
Zn.
The TCAL1 and MOBAL2 databases are the result of a longterm
collaboration with academia that has involved extensive experimental
work, as well as critical assessments of the published
literature. Both databases have also been validated where possible
against higher order systems, such as data published for industrial
alloys. Such validation highlights the key systems which are the
basis of many of the commercial aluminium alloys to which care of
special practical importance. Take for example, the AA-7000 series
alloys, which are high strength, high toughness alloys often used in
high performance applications such as aircraft, aerospace and competitive
sporting equipment: these alloys are based around the Al-
Cu-Mg-Zn system. In spite of the addition of other minor elements
like Mn and Si etc., the main hardening elements Zn, Mg and Cu
play a dominant role in the formation of the main precipitate phases
such as C14 (MgZn 2 , the η phase), S (Al 2 CuMg) and T (which is
stable in the Al-Cu-Mg, Al-Mg-Zn and Al-Cu-Mg-Zn ternary systems).
In some cases, the formation of the Al 7 Cu 2 Fe phase may also
be important. These phases dominate the balance of the properties,
and their amounts are closely related to the composition and to the
heat treatment conditions. In TCAL1, the thermodynamic description
of the Al-Zn-Mg-Cu-Fe core system has been systematically
refined and validated in order to give more accurate predictions
for these commercial Al-based alloys. More specifically, crucial corrections
or modifications have been made for the following related
ternary systems: Al-Cu-Fe, Al-Cu-Mg, Al-Cu-Zn, and Al-Mg-Zn.
tion during solidification. For example Onda et al [5] investigated the
solidification of alloy AC2A. The authors noted: “Prediction of the
solidification model by thermodynamic calculations is useful from a
practical point of view.”
However, equilibrium thermodynamic calculations, while useful, do
not consider the dynamic effects of time. DICTRA is a software tool
used for detailed simulations of diffusion-controlled phase transformations
for multi-component alloys where time diffusion is a parameter.
Example applications include the simulation of microsegregation during
solidification, heat treatment, growth and dissolution of precipitates,
and coarsening. Senaneuch et al [6], for example, used DICTRA to
look at diffusion modelling in brazed aluminium alloy components;
and Samaras et al [7] simulated the evolution of the as-cast microstructure
during the homogenisation heat treatment of alloy AA6061.
In the latter paper, the alloy microsegregation, which results after casting,
was calculated with the Scheil module using Thermo-Calc, and
the microstructure evolution during homogenisation was then simulated
with DICTRA. The composition profiles of the alloying elements,
and the volume fraction of the secondary phases, were calculated as
a function of homogenisation time. Comparison with experimental
work concluded: “The model reproduces the homogenisation kinetics
reasonably, and it is capable for the prediction of the homogenisation
heat treatment completion times.”
Two examples in the areas of casting and heat treatment using
Thermo-Calc in conjunction with TCAL1 are illustrated below.
Molten Metal Level Control
Thermodynamic and kinetic simulations
Predictions for multicomponent systems are useful, since they show
what phases could form at different temperatures during processing
and operation, for different alloy compositions, both under equilibrium
and under non-equilibrium conditions. Phase diagrams make
it possible to see how an element is influencing the phase stabilities
and solubilities of different elements at varying temperatures. For
example, Thermo-Calc can be used to predict second phase particles
that are formed during casting, homogenisation, downstream rolling
and annealing. Gupta et al [4] performed such a study to validate
calculations of phase stability made using Thermo-Calc against
experimental observations for automotive alloy AA6111, which is
a commercial body sheet alloy. The paper concluded: “The type of
particles, and the temperature regime in which they are formed,
are consistent with the predictions made by the Thermo-Calc software.”
The Scheil model in Thermo-Calc can also be used to predict
non-equilibrium solidification behaviour and micro-segrega-
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