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Machine learning lattice constants for spinel compounds

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Abstract Spinels can house a large variety of elements into the crystal structure. As a crystallographic parameter, the lattice constant, a, is highly sought in further investigations into materials properties.… Click to show full abstract

Abstract Spinels can house a large variety of elements into the crystal structure. As a crystallographic parameter, the lattice constant, a, is highly sought in further investigations into materials properties. Experimental approaches to obtain the lattice constant are resource-intensive, and limit the exploration into non-synthesized spinels. Here, we develop the Gaussian process regression model to shed light on the relationship among ionic radii, electronegativities, and lattice constants. 167 samples with lattice constants between 8.044 A and 11.660 A are investigated. The model provides more accurate predictions than previous studies based on linear regressions, and statistical relationships between descriptors and the target.

Keywords: constants spinel; lattice constants; learning lattice; machine learning; spinel compounds

Journal Title: Chemical Physics Letters
Year Published: 2020

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