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June 1, 2026Advanced Engineering Materials0 citationsOpen Access

Precipitation Simulations of the O‐Phase in Ti 2 AlNb Alloys Processed by Laser Powder Bed Fusion

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STSilvana TumminelloJGJoachim GussoneSFSuzana G. Fries

Key Points

  • This research seeks to simulate the O‐phase volume fraction evolution during postprocessing of a Ti‐21Al‐25Nb alloy.
  • Used computational models for phase precipitation and thermodynamic simulations.
  • Performed sensitivity analysis to evaluate input parameter effects on phase fraction evolution.
  • Conducted experimental analysis to validate simulation results.
  • Identified interfacial energy as the key parameter influencing the aging process volume fraction.
  • Simulations accurately predict O-phase precipitation behavior under various conditions.
  • Showed computational methods can predict material behavior effectively when combined with experimental data.

Abstract

In this work, computational models for phase precipitation were used to simulate the evolution of the O‐phase volume fraction during postprocessing of a Ti‐21Al‐25Nb (at.%) alloy processed by laser powder bed fusion and to study the phase transformations during subsequent heat treatments. The combination of computational simulations, thermodynamic models, and own experimental analysis allowed us to understand the sluggishness of the O‐phase isothermal precipitation in this alloy. To arrive at these conclusions and ensure that the simulations provided meaningful results, a thorough analysis of the input parameters was required to set up the calculations. A sensitivity analysis allowed quantification of the influence of these parameters on the phase fraction evolution. The interfacial energy of the matrix and precipitate phases was identified as the most relevant input parameter for the simulation of the volume fraction evolution during the aging process. This case study illustrates that computational thermodynamic and precipitation analysis provides a strong complementarity with experimental studies, enabling to tackle specific questions that are difficult to answer by designed experiments and even predict materials’ behavior.

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Cite This Study

Tumminello et al. (2026) studied this question.

synapsesocial.com/papers/6a1d22f702fbce9130638986https://doi.org/10.1002/adem.70963
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