Thermo-Calc 2025a Available Now
Webinar on Thermo-Calc 2025a Release
Sign up for our upcoming release webinar to explore the exciting new features and databases included in Thermo-Calc 2025a. Hear directly from six of the developers who contributed to this release as they share insights into these significant advancements.
New Licensing System
Thermo-Calc Software is excited to announce that we are migrating to a new License Entitlement System. The new system uses login credentials, which greatly simplifies the licensing process and brings many advantages to our customers.
Benefits include:
Redesigned Online Help
The online help receives a new look and feel in the 2025a release as well as a reorganization of the content for easier navigation.
Improvements include:
Thermal Gradients and Solidification Rates Added to AM Module and Can Be Overlayed Over CET Plots
First, the AM Module adds the ability to plot thermal gradients and solidification rates for both steady-state and transient simulations. These can be plotted in 2D as a scatter plot or in 3D.
The 2D plot can then be overlaid over CET (Columnar to Equiaxed transition) plots from the General Model Library, allowing users to evaluate whether the solidified microstructure corresponds to columnar or equiaxed, given the solidification conditions in the melt pool, as shown in the image below.
The plot shows thermal gradient vs solidification for IN718. The lines show the equiaxed fraction from the CET Model and the points show the solidification conditions at the melt pool calculated with the AM Module. As can be seen, nearly all the points (those below the purple line) exist in a fully columnar region.
Two new examples are available demonstrating these new features, one in Thermo-Calc and one in TC-Python:
Improved Modelling of AM in the Precipitation Module (TC-PRISMA)
Work has also been done to better simulate additive manufacturing in the Precipitation Module (TC-PRISMA) and to speed up these types of simulations.
Since the release of the AM Module, users have been able to send probe temperature data from the AM Module to the Precipitation Module (TC-PRISMA) in order to model microstructure. However, these types of simulations often took a long time or failed to complete.
Work has been done to address these issues and has resulted in two new checkboxes in the Precipitation Module (TC-PRISMA) for non-isothermal simulations:
These checkboxes pre-process the required thermodynamic and kinetic data coming from the AM Module in order to save time during the precipitation simulations and ensure the calculations complete successfully.
One new example is available demonstrating these new simulation options:
Simulated incipient melting of the large precipitates in the powder and reprecipitation after a single pass of an electron beam. Note the sudden drop in volume fraction resulting from incipient melting. The volume fraction increases upon reprecipitation once the material has resolidified, and the sufficient undercooling has been reached.
Model Absorptivity of the Liquid in the AM Module
It is now possible to predict the absorptivity of the liquid in the AM Module. Previously, users had to provide the absorptivity as a constant value, but you can now choose between providing a constant value or selecting Calculated, which models the absorptivity as a function of composition, temperature, wave length, and angle of incidence.
Screenshot of the software showing the calculated absorptivity as a function of angle of incidence for the alloy IN738LC. The red curve shows the absorptivity at the liquidus temperature and the blue curve the corresponding absorptivity at the evaporation temperature.
Improved Stability and Predictability for Al-alloys
Simulations for aluminum alloys have been improved in the Additive Manufacturing Module. Aluminum alloys have several challenges that make accurate simulations especially challenging, particularly in the three areas listed:
Due to these challenges, AM simulations for aluminum alloys often failed or provided inaccurate results in previous versions of the software. Therefore, work has been done to address these issues and make Al simulations more stable and accurate, namely three additions in the software. First, the absorptivity modeling that was discussed in the previous section.
Left: Al10SiMg – abs. 20% simulated in 2024b showing disagreement between experimental and simulated results; right: from Example AM_11_Batch_Al10SiMg in 2025a showing good agreement after the improvements.
Second, in the AM Calculator, the Smagorinsky constant can now be set by the user, whereas it was hardcoded before. This allows the simulation to better account for turbulent flows.
Smagorinsky constant setting added to the AM Calculator Options tab. This is used with the fluid flow model.
And finally, a new setting has been added to the Scheil calculator that allows for interface scattering to be applied after Scheil. This improves the predictability of as-cast and as-printed conductivity for all alloys with large amounts of secondary phases, not just aluminum alloys.
This new setting has been added to the main Scheil calculator as well, not just the one related to the AM Module.
A new example is available demonstrating these improvements:
New Functionality Added to the Plot Renderer
Several improvements have been made to the plot renderer in the Additive Manufacturing Module to make it easier to work with and expand the functionality.
When working in the AM Calculator there are now new options available to work with various tasks. You can save an image of the geometry or a 3D plot, set probe positions, or delete markers. These options are available either as tooltips or from menus when you right-click in the Visualizations window.
Example of the submenu on an AM Plot Renderer 3D Plot. You can right-click in the plot area to either save a snapshot of the plot at the given zoom level (select Save As), or when working with markers you can right-click to Delete marker when you are using the Show Manual Ruler button to measure between two points.
New Noble Metal Alloys Model Library
A new Property Model Library for Noble Metal Alloys is available as of this release. The library includes one model that was designed for predicting the optical properties and apparent color of noble metal alloys as a function of incident light. The model is intended to assist users in achieving an attractive color when developing noble metal alloys for the purpose of cosmetic applications.
Color prediction for Ag-Au-Cu alloy using the new Optical Properties Model in the Noble Metal Alloys Model Library.
One example is available, which demonstrates three use cases for simulating color in the silver-gold-copper (Ag-Au-Cu) alloy system:
Import 1D and 2D PSD and Convert to 3D
The Precipitation Module (TC-PRISMA) adds the ability to convert two-dimension (2D) or one-dimensional (1D) particle size distribution information to a three-dimensional (3D) distribution for use in modeling. This allows users to upload experimental 2D or 1D particle size distribution data into the program, convert it to 3D distribution data, and compare the approximation with the experimental data.
The improvement includes a new setting available on the Preexisting Particle Size Distribution window, Input type. Choose Generate 3D PSD from distribution function, From File, or Approximate the 3D PSD from experimental data. When Approximate the 3D PSD from experimental data is chosen, there is an additional option (Dimensionality of exp. data) to choose the dimension (1D, 2D, or 3D) and then import experimental data.
The converse ability, to convert 3D distribution to 2D distribution, was added to the software in Thermo-Calc 2024a.
Graphical mode example P_10_Precipitation_Initial_PSD_FeCrC.tcu has been updated to demonstrate both conversion options.
From the updated example P_10, M7C3 phase which uses 1D dimensionality and imports experimental data.
New Method for Splitting Multi-modal Distributions
A new method is implemented in the Precipitation Module (TC-PRISMA) to split precipitate size distributions in order to identify statistics of individual populations.
You can both section and split several post processing quantities.
Results from running Example P_06 in 2024b (left plot) and 2025a (right plot). The results showcase how the particle population detection has been improved in Thermo-Calc 2025a.
Example P_06 is updated to demonstrate this improvement, which simplifies the process and makes it more robust to identify individual populations:
TC-Python also updates one example and adds one example showing this:
Databases and Properties
New Databases
Updated Databases
Thermo-Calc 2025a also includes four updated databases. Read the Release Notes for more details.