MTRL-SCIAICOMP-PHJun 21, 2025

Clarifying the Ti-V Phase Diagram Using First-Principles Calculations and Bayesian Learning

arXiv:2506.17719v21 citationsh-index: 4Comput mater sci
Originality Incremental advance
AI Analysis

This clarifies a long-standing disagreement in materials science, providing a definitive phase diagram for Ti-V alloys, which is incremental but important for alloy design and understanding.

The researchers resolved conflicting experimental data on the titanium-vanadium (Ti-V) binary alloy by constructing a phase diagram using an ab initio and machine-learning workflow, confirming a body-centred cubic miscibility gap terminating at T = 980 K and c = 0.67 and ruling out oxygen contamination as the cause.

Conflicting experiments disagree on whether the titanium-vanadium (Ti-V) binary alloy exhibits a body-centred cubic (BCC) miscibility gap or remains completely soluble. A leading hypothesis attributes the miscibility gap to oxygen contamination during alloy preparation. To resolve this disagreement, we use an ab initio + machine-learning workflow that couples an actively-trained Moment Tensor Potential with Bayesian inference of free energy surface. This workflow enables construction of the Ti-V phase diagram across the full composition range with systematically reduced statistical and finite-size errors. The resulting diagram reproduces all experimental features, demonstrating the robustness of our approach, and clearly favors the variant with a BCC miscibility gap terminating at T = 980 K and c = 0.67. Because our simulations model a perfectly oxygen-free Ti-V system, the observed gap cannot originate from impurity effects, in contrast to recent CALPHAD reassessments.

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