用第一性原理与贝叶斯学习澄清钛钒相图争议
Clarifying the Ti-V Phase Diagram Using First-Principles Calculations and Bayesian Learning
- 结合第一性原理与主动学习势函数，构建全成分相图
- 发现体心立方共存区在980K、组分比0.67处终止
- 证明相分离非杂质导致，支持存在真实共存区
关于钛-钒（Ti-V）二元合金是否存在体心立方（BCC）混溶间隙，实验结果相互矛盾。主流假说认为该现象源于制备过程中的氧污染。为解决这一争议，我们采用第一性原理结合机器学习的流程，通过主动训练的矩张量势与贝叶斯自由能表面推断，系统构建了全成分范围的Ti-V相图，显著降低统计与有限尺寸误差。结果准确再现所有实验特征，明确支持存在一个在980 K、组分比c=0.67处终止的BCC混溶间隙。由于模拟系统完全无氧，该共存区不可能由杂质引起，与近期CALPHAD再评估结论相反。
原文摘要 · Abstract (English)
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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