APPLICATIONS OF THERMO-CALC

Alloy Development

Thermo-Calc accelerates alloy design by predicting material properties and behavior with composition and temperature dependence to down-select potential candidate alloys for further testing.

Applications to Alloy Development

Designing new alloys to meet specific property requirements requires intimate knowledge of the composition, processing, and microstructure relationships. Traditional ways of developing new alloys are founded on experimental trial and error approaches that only give incremental improvements. Recent initiatives such as ICME (Integrated Computational Materials Engineering) and MGI (the Materials Genome Initiative) provide a more systematic approach for materials design.

Thermo-Calc offers a solid foundation for an ICME framework by providing material data with composition and temperature dependence to input into other codes, and simulating chemistry and processing effects on material behavior to down-select potential candidate alloys for further testing.

Accelerate the materials design process by:

  • Predicting phase stability as a function of chemistry and temperature
  • Pre-screening large numbers of potential candidate compositions to reduce the number of experiments
  • Using high throughput calculations to discover chemistries that meet a target property
  • Exploring trade-offs between material properties as a function of chemistry
  • Augmenting machine learning and AI models with calculated material property data as training sets
  • Understanding material processability issues that may arise moving from benchtop to industrial scale

Application Examples

Thermo-Calc has many applications to alloy development. Below are two such examples.

Designing Martensitic Stainless Steels for Carburization Treatments

During alloy design, phase diagrams can provide useful information to predict the stable phase fields as a function of composition and temperature. For example, Turpin et al. (Met. Trans. A, 2005) used Thermo-Calc and the Diffusion Module (DICTRA) to understand the influence of the chemical composition to find the optimal carbon profile in an alloy in order to develop a carburized martensitic stainless steel for applications in the aerospace industry. As a first step, the phase diagram of the steel was calculated using Thermo-Calc.

This recalculated figure shows an isopleth for a Fe-13Cr-5Co-3Ni-2Mo-0.07C martensitic stainless steel. The figure shows that, as the overall carbon content increases, first M23C6 carbides precipitate, then M7C3 carbides appear in the austenitic matrix; if the mass percent of carbon exceeds 3.8, M3C carbides (a structure similar to cementite) will preferentially precipitate at the grain boundaries, which could weaken the microstructure and should thus be avoided.

A phase diagram for a Fe-13Cr-5Co-3Ni-2Mo-0.07C martensitic stainless steel.

Optimizing Pitting Resistance in Duplex Stainless Steels

Duplex stainless steels consist of a nearly balanced microstructure of ferrite (BCC) and austenite (FCC) phases. They are designed to offer a combination of high strength, toughness, and corrosion resistance and require stringent control on composition and thermal processing. Thermo-Calc can be used to study the influence of composition on the corrosion resistance of each phase.

In this figure, the PRE (pitting resistance equivalent) is calculated for the ferrite and austenite in a 2507 alloy. When the alloy has 0.33wt% N, the PRE is equal in both phases, which helps avoid preferential corrosion. The homogenization temperature required to get a balanced 50/50 microstructure is also shown to be 990 °C – 1280 °C with 1172 °C providing the optimal equivalent PRE.

A plot showing a Pitting Resistance Calculation for Super Duplex 2507 as a function of Nitrogen content.

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