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Novel inorganic crystal structures predicted using autonomous simulation agents.

ABSTRACT: We report a dataset of 96640 crystal structures discovered and computed using our previously published autonomous, density functional theory (DFT) based, active-learning workflow named CAMD (Computational Autonomy for Materials Discovery). Of these, 894 are within 1 meV/atom of the convex hull and 26826 are within 200 meV/atom of the convex hull. The dataset contains DFT-optimized pymatgen crystal structure objects, DFT-computed formation energies and phase stability calculations from the convex hull. It contains a variety of spacegroups and symmetries derived from crystal prototypes derived from known experimental compounds, and was generated from active learning campaigns of various chemical systems. This dataset can be used to benchmark future active-learning or generative efforts for structure prediction, to seed new efforts of experimental crystal structure discovery, or to construct new models of structure-property relationships.

SUBMITTER: Ye W

PROVIDER: S-EPMC9197834 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Novel inorganic crystal structures predicted using autonomous simulation agents.

Ye Weike W Lei Xiangyun X Aykol Muratahan M Montoya Joseph H JH

Scientific data 20220614 1

We report a dataset of 96640 crystal structures discovered and computed using our previously published autonomous, density functional theory (DFT) based, active-learning workflow named CAMD (Computational Autonomy for Materials Discovery). Of these, 894 are within 1 meV/atom of the convex hull and 26826 are within 200 meV/atom of the convex hull. The dataset contains DFT-optimized pymatgen crystal structure objects, DFT-computed formation energies and phase stability calculations from the convex ...[more]

PMID: 35701432

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Project description:We tested a battery of density functional theory (DFT) methods ranging from generalized gradient approximation (GGA) via meta-GGA to hybrid meta-GGA schemes as well as Møller-Plesset perturbation theory of the second order and a single and double excitation coupled-cluster (CCSD) theory for their ability to reproduce accurate gas-phase structures of di- and triatomic molecules derived from microwave spectroscopy. We obtained the most accurate molecular structures using the hybrid and hybrid meta-GGA approximations with B3PW91, APF, TPSSh, mPW1PW91, PBE0, mPW1PBE, B972, and B98 functionals, resulting in lowest errors. We recommend using these methods to predict accurate three-dimensional structures of inorganic molecules when intramolecular dispersion interactions play an insignificant role. The structures that the CCSD method predicts are of similar quality although at considerably larger computational cost. The structures that GGA and meta-GGA schemes predict are less accurate with the largest absolute errors detected with BLYP and M11-L, suggesting that these methods should not be used if accurate three-dimensional molecular structures are required. Because of numerical problems related to the integration of the exchange-correlation part of the functional and large scattering of errors, most of the Minnesota models tested, particularly MN12-L, M11, M06-L, SOGGA11, and VSXC, are also not recommended for geometry optimization. When maintaining a low computational budget is essential, the nonseparable gradient functional N12 might work within an acceptable range of error. As expected, the DFT-D3 dispersion correction had a negligible effect on the internuclear distances when combined with the functionals tested on nonweakly bonded di- and triatomic inorganic molecules. By contrast, the dispersion correction for the APF-D functional has been found to shorten the bonds significantly, up to 0.064 Å (AgI), in Ag halides, BaO, BaS, BaF, BaCl, Cu halides, and Li and Na halides and hydrides. These results do not agree well with very accurate structures derived from microwave spectroscopy; we therefore believe that the dispersion correction in the APF-D method should be reconsidered. Finally, we found that inaccurate structures can easily lead to errors of few kcal/mol in single-point energies.

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Novel inorganic crystal structures predicted using autonomous simulation agents.

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Novel inorganic crystal structures predicted using autonomous simulation agents.

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