AB₂X₆ Compounds and the Stabilization of Trirutile Oxides

Abstract

The properties of crystalline materials tend to be strongly correlated with their structures, and the prediction of crystal structure from only the composition is a coveted goal in the field of inorganic materials. However, even for the simplest compositions, such prediction relies on a complex network of interactions, including atomic or ionic radii, ionicity, electronegativity, position in the periodic table, and magnetism, to name only a few important parameters. We focus here on the AB 2 X 6 (AB 2 O 6 and AB 2 F 6 ) composition space with the specific goal of finding new oxide compounds in the trirutile family, which is known for unusual 1D antiferromagnetic behavior.Through machine learning methods, we develop an understanding of how geometric and bonding constraints determine the crystallization of compounds in the trirutile structure as opposed to other other ternary structures in this space. In combination with density functional theory (DFT) calculations, we predict 18 candidate, previously unreported trirutile oxides. We successfully prepare one of these and show it forms in the disordered rutile structure, under the preparation conditions adopted here.

Modeling ionic conductivity and activation energy in garnet-structured solid electrolytes: the role of composition, grain boundaries and processing

“…In recent decades, machine learning methods demonstrated the permanent success in materials science as in one of the most actively growing areas of their application and formalized the materials informatics as assertive direction that, however, should be awared of the actual experince gained in the allied fields [20]. Recent materials informatics studies include (i) information retrieval and text mining [21,22], (ii) the direct rational screening of materials with tailored characteristics [23,24,25,26,27,28,29,30,31], (iii) the post-processing and analysis of the results of the materials characterization techniques [32,33,34,35,36], (iv) the modeling of the processes at the interfaces [37], (v) the crystal structure prediction [38,39,40], (vi) design of experiment [41,42] and many other applications. The computer-aided screening of fast Li solid state electrolytes or the modeling of Li transport characteristics have been performed in a number of studies [43,44,45,46,47,48,49,50,51].…”