Using Data Mining To Search for Perovskite Materials with Higher Specific Surface Area.

Journal: Journal of chemical information and modeling
Published Date: Dec 24, 2018

Abstract

The specific surface area (SSA) of ABO-type perovskite is one of the important properties associated with photocatalytic ability. In this work, data mining methods were used to explore the relationship between the SSA (in the range of 1-60 m g) of perovskite and its features, including chemical compositions and technical parameters. The genetic algorithm-support vector regression method was used to screen the main features for modeling. The correlation coefficient ( R) between the predicted and experimental SSAs reached as high as 0.986 for the training data set and 0.935 for leave-one-out cross-validation. ABO-type perovskites with higher SSA can be screened out using the Online Computation Platform for Materials Data Mining (OCPMDM) developed in our laboratory. Further, an online web server has been developed to share the model for the prediction of SSA of ABO-type perovskite, which is accessible at http://118.25.4.79/material_api/csk856q0fulhhhwv .

Authors

  • Li Shi
    Department of Integrated Chinese and Western Medicine, Second Xiangya Hospital, Central South University, Changsha 410011, China.
  • Dongping Chang
    Materials Genome Institute , Shanghai University , Shanghai 200444 , China.
  • Xiaobo Ji
    Department of Chemistry, College of Sciences , Shanghai University , Shanghai 200444 , China.
  • Wencong Lu
    Department of Chemistry, College of Sciences, Shanghai University, Shanghai 200444, China.

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