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1,831 claims from 1,127 papers are on the record. 46 have been checked so far; the other 1,785 have no check with a result yet.

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2 claims from 1 paper

1. Materials Science › Machine Learning in Materials Science

   Predicting density functional theory total energies and enthalpies of formation of metal-nonmetal compounds by linear regression

   Deml, O’Hayre, Wolverton and Stevanović · Physical review. B./Physical review. B · 2016

   The authors fit a linear regression model to a large set of DFT-based calculated energies of metal-nonmetal compounds, linking them to elemental properties and testing it on compounds outside the fitting set.

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   1. UncheckedA linear model fitted by stepwise regression reproduces calculated FERE total energies and formation enthalpies to within about 80 meV per atom on average.“From a stepwise linear regression, we develop a linear model for ${E}_{\mathrm{tot}}$, and consequently $\mathrm{\ensuremath{\Delta}}{H}_{f}$, that reproduces calculated FERE values with a mean absolute error of \ensuremath{\sim}80 meV/atom.”
   2. UncheckedThe authors' linear model of total energy and enthalpy of formation can be extended to predict these values for compounds outside its development set.“We also demonstrate that our ${E}_{\mathrm{tot}}/\mathrm{\ensuremath{\Delta}}{H}_{f}$ model can be directly extended to predict the ${E}_{\mathrm{tot}}$ and $\mathrm{\ensuremath{\Delta}}{H}_{f}$ of compounds outside the set used to develop the model.”