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This article is
mainly to introduce the principles and applications of alloy design based on
thermodynamics. This report will include three parts, high-entropy alloy
design, genetic alloy design and alloy design of
high-temperature solder. The introductions, principles and applications also will be
included in each part.

 

In the
part of high-entropy alloy(HEA) design, the thermodynamics criteria for mixing
elements to get HEA is introduced.

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In the
second part, a theoretical guidance for the design of alloy design is presented.
The aim of the approach based on the guidance is to optimize the desired performance,
microstructure and the alloy compositions.

 

The
third part will introduce how thermodynamics help decide several specific
compositions and how the compositions are examined in terms of melting
behavior, electrical resistivity, wetting angle and hardness. These materials
were used in high-temperature solders.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Part1.
Application in high-entropy design

 

High entropy alloys (HEA) represents a
new concept of alloy design, a revolution for traditional alloy design method. The
traditional design method of the alloy is usually based on one or at most two
key elements. Instead, HEAs has many elements. HEA usually forms a simple solid
solution structure, such as face-centered cubic (fcc), body-centered cubic
(bcc) or a mixture of both. This is because of the high entropy of mixing in
the solution phase. In thermodynamics, when the gibbs free energy of the system
achieves its global minimum under constant temperature and pressure, the system
will be at equilibrium. The solution phase of the mixing Gibbs can be described
as follows1:

 

?Hmix
means the enthalpy of mixing. ?Smix
means the entropy of mixing. For a random mixing of

components, the configurational entropy
of mixing is calculated by:

              

                      

T is the temperature in Kelvin and R is
the gas constant. For the n-element solution phase, ?Smix
reaches its maximum Rln (n) when using the equivalent mole fraction of each
element (xi). The higher entropy of mixing leads to lower Gibbs energy at
constant temperature, which stabilizes the solution1.

 

Recently, HEA becomes more and more
popular for the reason that it has many outstanding properties, such as high
strength, high thermal ability, high abrasion resistance and high antioxidant properties.

 

Even though the HEA consists of many
elements, it does not mean that HEAs can be produced by simply mixing a series
of elements together with an equal atomic ratio. Here are some criteria1:

 

a. High entropy of mixing (?Smix
> 1.61R), which requires at least five principal components in the system
with equal atomic ratio.

b. Small enthalpy of mixing (-15< ?mix< 5 kJ/mol), which is due to the fact that a large positive enthalpy of mixing results in the segregation of different elements, and a large negative enthalpy of mixing leads to the formation of compounds. c. Small atomic size difference (?< 4.6), which favors the formation of solid-solution phase.         ` Part 2. Genetic alloy design based on thermodynamics and kinetics   This essay is mainly about a novel computational approach to alloy design. The method is based on the expected microstructure, and the aim is to combine strength maximization with corrosion resistance. The required alloys are searched based on thermodynamic calculations. So, I will primarily introduce this part.   It defines multiple targets, microstructure and strict parameters that reflect different aspects. The composition of alloy is the corresponding design. There are 13 elements are considered: C, Cr, Ni, Ti, Mo, Al, Cu, Co, Nb, N, V, Mn and Si. Table 1 lists the concentration ranges of each element in the optimization process. They explain industrial and technical constraints related to the manufacture of alloys. For each alloy element, the composition range is divided into 32 equal intervals. It is also important to note that multiple alloy elements may have conflicting interactions due to multiple targets. Therefore, the number of different alloying elements must be balanced while Optimization the alloy composition2.   Genetic algorithm is chosen as the optimal solution in order to scan the wide range of solution space for 32 candidate alloys and find the best compromise solution among different goals. A major FORTRAN program was developed, mainly through genetic optimization algorithm from program execution thermodynamics calculation and evaluation of evolution standard (figure 1). For each candidate solution, use the following algorithm to evaluate the above criteria2.   a. Define the system in ThermoCalc and enter calculation conditions (composition and temperature).   b. The Ms temperature is calculated from Equation (1) and a go/no-go criterion of Ms?200Co was imposed to ensure the formation of lath martensite. Ms temperature is estimated by considering the energy variation of both the chemical and mechanical contributions of the alloying elements.   c. Thermodynamic equilibrium calculation; Obtain the volume fraction and composition of the equilibrium phase. The total integral number of the phase that not desired is added, and the Cr concentration recorded in the matrix is retained.   d. Set Fe-rich BCC phase as matrix, and calculate the precipitation driving force at the fixed precipitation temperature of 500 ? as well as the critical nucleation radius .   e. The strengthening factor  is calculated.

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