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<p>Titanium and its alloys are technologically important materials that display a rich phase behaviour. In order to enable large-scale, realistic modelling of Ti and its alloys on the atomistic scale, MLIPs are crucial, but rely on databases of atomic configurations. We report databases of such configurations that represent the <i>α</i>, <i>β</i>, <i>ω</i> and liquid phases of Ti and the Ti-6Al-4V alloy, where we provide total energy, force and stress values evaluated by DFT using the PBE functional. We have also utilised a data reduction strategy, via non-diagonal supercells, for the vibrational properties of Ti and sampling of atomic species for Ti-6Al-4V. These configurations may be used to fit models that can accurately model the phase behaviour of Ti and Ti-6Al-4V across a broad range of thermodynamic conditions. To validate models, we assembled a set of benchmark protocols, which can be used to rapidly develop and evaluate MLIP models. We demonstrated the utility of our databases and validation tools by fitting models using the GAP and ACE frameworks.</p>

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Multi-phase dataset for bulk Ti and the Ti-6Al-4V alloy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月5日

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  • Connor S. Allen,
  • Albert P. Bartók

摘要

Titanium and its alloys are technologically important materials that display a rich phase behaviour. In order to enable large-scale, realistic modelling of Ti and its alloys on the atomistic scale, MLIPs are crucial, but rely on databases of atomic configurations. We report databases of such configurations that represent the α, β, ω and liquid phases of Ti and the Ti-6Al-4V alloy, where we provide total energy, force and stress values evaluated by DFT using the PBE functional. We have also utilised a data reduction strategy, via non-diagonal supercells, for the vibrational properties of Ti and sampling of atomic species for Ti-6Al-4V. These configurations may be used to fit models that can accurately model the phase behaviour of Ti and Ti-6Al-4V across a broad range of thermodynamic conditions. To validate models, we assembled a set of benchmark protocols, which can be used to rapidly develop and evaluate MLIP models. We demonstrated the utility of our databases and validation tools by fitting models using the GAP and ACE frameworks.