Ontology highlight
ABSTRACT:
SUBMITTER: Ye W
PROVIDER: S-EPMC6143552 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
Ye Weike W Chen Chi C Wang Zhenbin Z Chu Iek-Heng IH Ong Shyue Ping SP
Nature communications 20180918 1
Predicting the stability of crystals is one of the central problems in materials science. Today, density functional theory (DFT) calculations remain comparatively expensive and scale poorly with system size. Here we show that deep neural networks utilizing just two descriptors-the Pauling electronegativity and ionic radii-can predict the DFT formation energies of C<sub>3</sub>A<sub>2</sub>D<sub>3</sub>O<sub>12</sub> garnets and ABO<sub>3</sub> perovskites with low mean absolute errors (MAEs) of ...[more]