APPLICATIONS OF THERMO-CALC

Iron and Steels

Thermo-Calc can be used to predict thermophysical and phase-based properties as well as to simulate material behavior throughout the materials life cycle for Fe-based alloys and a wide range of steels.

Applications to Steels

Fe-based alloys and steels cover a broad range of materials, which can be subdivided into stainless steels, high-speed steels, tool steels, high-strength low alloy (HSLA) steels, cast irons, corrosion-resistant high strength steels, low-density steels and also cemented carbides. 

Handbook data typically covers only the most common alloys, and additionally does not always take into account variations in chemistry or processing conditions. Where this data is missing, Thermo-Calc can be used to fill the gaps in material property data and make predictions of material behavior throughout the materials life cycle.

Calculate the following based on your actual alloy chemistry:

  • Thermophysical properties, such as:
    • Specific heat, enthalpy, latent heat, viscosity, density as a function of temperature, coefficients of thermal expansion, and more
    • Phase-based properties, such as:
      • Critical transformation temperatures such as A1 and A3, amounts and compositions of phases, solubility limits, activities, phase diagrams, and more
        • Solvus temperatures and volume fractions of phases such as σ, α’, and carbides as well as nitrides and carbonitrides
        • Equilibrium and non-equilibrium solidification, such as:
          • Liquidus, solidus, incipient melt temperatures, freezing range, fraction solid curves, solidification path, fraction eutectic, microsegregation, partition coefficients, latent heat, shrinkage, and more
          • Homogenization, such as:
            • Optimal homogenization temperatures, time needed to homogenize any chemical segregation arising from solidification, and/or dissolve precipitates
            • Precipitation hardening, such as:
              • Concurrent nucleation, growth/dissolution, coarsening of precipitate phases, volume fraction, and size distribution as a function of time
              • Surface hardening:
                • Case depth profiles and precipitate formation during carburization, nitridation, and carbonitriding
                • Transformation kinetics, such as:
                  • Austenite to ferrite, carbide dissolution, and more
                  • Steelmaking, slag-metal, and slag-crucible reactions. Learn more at the Process Metallurgy Module page.
                  • Martensite and pearlite transformations. Learn more at the Steel Model Library page.

Application Examples

Thermo-Calc has many applications to steels and Fe-based alloys. Below are three such examples.

Critical Temperatures and Phase Fractions in P91 Steels

P91 steels rely on a quench and temper microstructure to obtain good creep strength and toughness. If the A1 temperature is exceeded during tempering, then untempered martensite will remain after heat treatment, leading to poor toughness. Phase transformation temperatures can vary with chemistry and this can be calculated using Thermo-Calc.

This figure shows the equilibrium phases as a function of temperature for a nominal composition of P91, with A1, A3, liquidus, and solidus listed on the diagram.

A plot showing the volume fraction of phases vs. temperature for a nominal composition of P91.

A1 Temperature Distribution for P91 Base Metal and Weld Filler Metals

In the above example, the A1 temperature was calculated based on a nominal composition of P91. This temperature can vary with composition and can be different between the weld metal and base metal, but this is hard to capture for every possible heat of material without performing many experiments. With Thermo-Calc, you can calculate this across the entire composition space. 

The histogram here shows the A1 temperature calculated for 200 compositions each that fall within the P91 base metal and two weld filler metal matching composition specifications. As can be seen, if the post weld heat treat temperature is selected according to the base metal compositions, the A1 temperature could be exceeded in the weld metal resulting in fresh martensite formation.

A plot showing a comparison of A1 temperature for 9Cr-1Mo creep strength enhanced ferritic steel base metal (ASTM A335 Gr. P91) and two weld “matching” filler metals (AWS A5.28 ER90S-B9).

Martensite Content for 4130 Low Alloy Steel

Many low alloy steels, such as 4130, rely on a quench and temper microstructure to obtain desired mechanical properties. The martensite transformation start and finish temperatures can vary as a function of chemical composition. The Ms temperature can be easy to measure, but it is difficult to determine the martensite fractions as a function of temperature. This is important to determine if any retained austenite may be present. With Thermo-Calc, the martensite fraction can be calculated as a function of temperature for different compositions.

The diagram here shows the martensite fractions as a function of temperature for a 4130 steel with nominal chemistry and agrees well with the literature value of 380 °C (ASM Handbook Volume 1: Properties and Selection: Irons, Steels, and High-Performance Alloys, ASM Handbook Committee).

A plot showing the martensite content as a function of temperature for 4130 steel.

Learn more about Applications to Steels

Read several in-depth examples showing how Thermo-Calc can be used to improve steels and steel processing

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Steel Making and Steel Refining using Thermo-Calc and the TCOX9 Database

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Thermo-Calc used to Estimate Critical Temperatures in Type 410 Steels

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The importance of steel chemistry and thermal history on the sensitization behavior in austenitic stainless steels: Experimental and modeling assessment

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Challenges and opportunities in thermodynamic and kinetic modeling microalloyed HSLA steels using computational thermodynamics

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Retention of Delta Ferrite in the Heat-Affected Zone of Grade 91 Steel Dissimilar Metal Welds

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Continuous Casting of High Carbon Steel: How Does Hard Cooling Influence Solidification, Micro – and Macro Segregation?

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