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<p>Topologically close-packed (TCP) phases such as sigma (σ) and mu (μ) are known to degrade the mechanical properties of Ni-based superalloys due to their inherent brittleness. Accurate thermodynamic modeling of these phases is essential for computational alloy design and process optimization. In this work, the Effective Bond Energy Formalism (EBEF) is implemented in the TCNI13 database to reassess the σ and μ phases using crystallographically consistent five-sublattice (5-SL) thermodynamic models supported by Density Functional Theory (DFT) calculations. The EBEF approach enables a significant reduction in the number of required formation energies while improving predictive accuracy across binary, ternary, and multicomponent systems. Results show enhanced agreement with experimental phase equilibria, particularly in complex alloys such as Hastelloy variants and other advanced Ni-based superalloys. TCNI13 demonstrates improved extrapolation capabilities and reduced reliance on adjustable parameters, marking a substantial advancement in the CALPHAD modeling of TCP phases.</p>

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Implementing the Effective Bond Energy Formalism to Improve the Description of the Sigma (σ) and Mu (μ) Phases in the TCNI Database

  • 期刊论文

  • 发表日期：

    2026年4月15日

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  • Júlio César Pereira dos Santos,
  • Weiwei Zhang,
  • Huahai Mao,
  • Giancarlo Trimarchi,
  • Reza Naraghi

摘要

Topologically close-packed (TCP) phases such as sigma (σ) and mu (μ) are known to degrade the mechanical properties of Ni-based superalloys due to their inherent brittleness. Accurate thermodynamic modeling of these phases is essential for computational alloy design and process optimization. In this work, the Effective Bond Energy Formalism (EBEF) is implemented in the TCNI13 database to reassess the σ and μ phases using crystallographically consistent five-sublattice (5-SL) thermodynamic models supported by Density Functional Theory (DFT) calculations. The EBEF approach enables a significant reduction in the number of required formation energies while improving predictive accuracy across binary, ternary, and multicomponent systems. Results show enhanced agreement with experimental phase equilibria, particularly in complex alloys such as Hastelloy variants and other advanced Ni-based superalloys. TCNI13 demonstrates improved extrapolation capabilities and reduced reliance on adjustable parameters, marking a substantial advancement in the CALPHAD modeling of TCP phases.