Machine learning the lattice constant of cubic pyrochlore compounds

Abstract

Pyrochlores, with a general formula A 2 B 2 X 7 , are promising candidates in many potential applications due to their wide varieties of physical properties. Different combinations of cations and anions in the crystal structure enable the tailoring of their properties and functionalities. For cubic pyrochlores, the lattice constant, a, is an integrated result of stoichiometry, ionic radii, and electronegativities of alloying elements.It also has significant impacts on stabilities, electronic structures, ionic conductivities, and thus performance of materials. Here, we develop the Gaussian process regression model to shed light on the relationship among ionic radii, electronegativities, and lattice constants for cubic pyrochlores. The dataset includes ternary pyrochlores and mixed pyrochlores with co-doping and multi-doping situations. One hundred and thirty-nine samples with lattice constants between 9.287 and 11.150 Å are examined.The model is highly stable and accurate that contributes to efficient and low-cost lattice constant estimations.

Machine learning the peak emission wavelength of Mn4+-activated inorganic phosphors

“…Brgoch et al 30 developed a support vector regression algorithm based on 134 experimentally measured temperature-dependent Eu 3+ emission data points to rapidly predict the thermal quenching temperature. The lattice constants of pyrochlores were successfully predicted by Zhang et al 31 using a Gaussian process regression (GPR) model with electronegativities and ionic radii as descriptors. The aforementioned researchers have achieved certain milestones; however, KNN provides better results when dealing with sparse and scattered data.…”

Atomic Insights into the Structural Properties and Displacement Cascades in Ytterbium Titanate Pyrochlore (Yb2Ti2O7) and High-Entropy Pyrochlores

“…Brendan et al have investigated the relationship between the structural and bonding energy in lanthanide pyrochlore oxides (Sn 2 O 7 ) and found that the position parameter of the oxygen vacancies is inversely proportional to the lattice parameter. Recently, Zhang et al have reported on the machine learning (ML) methods to determine lattice constants of different multi-substitutional pyrochlores in the range of 9-11 Å [17]. Moreover, the pyrochlore stannate (Ce 2 Sn 2 O 7 ) demonstrated a temperature-dependent anisotropic nature [18].…”

A novel Sn2Nb2O7/defective carbon nitride heterojunction photocatalyst: preparation and application for photocatalytic oxytetracycline removal

“…8–10 Pyrochlore-based oxides with the general formula A 2 B 2 O 7 have been considered good candidates for highly sought application areas such as superconductors, multiferroic materials, catalysts, and photoelectronic devices due to their high ionic conductivity and low electronic conductivity. 11,12 Among them, Nb-based pyrochlore semiconductors have been applied in various photocatalysts because of their excellent ability to transfer photogenerated electron–hole pairs. Importantly, Nb-based photocatalysts have more negative conduction band (CB) levels, which consist of a Nb 4d orbital as opposed to a Ti 3d orbital, giving the photogenerated electrons strong reducing capability.…”