Classification of AB O3 perovskite solids: a machine learning study

Pilania, G.; Balachandran, P. V.; Gubernatis, J. E.; Lookman, T.

doi:10.1107/S2052520615013979

Title: Classification of AB O₃ perovskite solids: a machine learning study

Journal Article · Thu Jul 23 00:00:00 EDT 2015 · Acta Crystallographica. Section B, Structural Science, Crystal Engineering and Materials (Online)

DOI:https://doi.org/10.1107/S2052520615013979· OSTI ID:1257974

Pilania, G. ^[1]; Balachandran, P. V. ^[1]; Gubernatis, J. E. ^[1]; Lookman, T. ^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Here we explored the use of machine learning methods for classifying whether a particular ABO₃chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, the A and B ionic radii relative to the radius of O, and the bond valence distances between the A and B ions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2–3 percentage points over using any one pair. We also included the Mendeleev numbers of the A and B atoms to this set of feature pairs. Moreover, doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.

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Research Organization:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1257974

Report Number(s):: LA-UR-15-22854; ACSBDA; PII: S2052520615013979

Journal Information:: Acta Crystallographica. Section B, Structural Science, Crystal Engineering and Materials (Online), Vol. 71, Issue 5; ISSN 2052-5206

Publisher:: International Union of CrystallographyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 43 works

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