Computational discovery of stable and metastable ternary oxynitrides

Abstract

Materials design from first principles enables exploration of uncharted chemical spaces. Extensive computational searches have been performed for mixed-cation ternary compounds, but mixed-anion systems are gaining increased interest as well. Central to computational discovery is the crystal structure prediction, where the trade-off between reliance on prototype structures and size limitations of unconstrained sampling has to be navigated. We approach this challenge by letting two complementary structure sampling approaches compete. We use the kinetically limited minimization approach for high-throughput unconstrained crystal structure prediction in smaller cells up to 21 atoms. On the other hand, ternary—and, more generally, multinary—systems often assume structures formed by atomic ordering on a lattice derived from a binary parent structure. Thus, we additionally sample atomic configurations on prototype lattices with cells up to 56 atoms. Using this approach, we searched 65 different charge-balanced oxide–nitride stoichiometries, including six known systems as the control sample. The convex hull analysis is performed both for the thermodynamic limit and for the case of synthesis with activated nitrogen sources. We identified 34 phases that are either on the convex hull or within a viable energy window for potentially metastable phases. We further performed structure sampling for “missing” binary nitrides whose energies are needed for the convex hull analysis. Among these, we discovered metastable Ce3N4 as a nitride analog of the tetravalent cerium oxide, which becomes stable under slightly activated nitrogen condition ΔμN > +0.07 eV. Given the outsize role of CeO2 in research and application, Ce3N4 is a potentially important discovery.

Experimental Synthesis of Theoretically Predicted Multivalent Ternary Nitride Materials

“…46 Despite these several examples, it remains difficult to make nitrogen-rich transition metal nitrides due to the relatively weak oxidizing power of nitrogen, but the technological interest has led to new compound predictions awaiting novel synthesis strategies. For example, a nitrogen rich cerium nitride Ce 3 N 4 has been predicted as a slightly metastable nitride based on a computational search 51 and remains to be synthesized.…”

Computational Discovery of Two-Dimensional Rare-Earth Iodides: Promising Ferrovalley Materials for Valleytronics

“…The Kinetically Limited Minimization (KLM), an unconstrained crystal structure prediction algorithm, which combines unbiased random sampling and sequential atomic perturbations based on ground-state energy derived from the first principle calculations, is employed to predict the crystal structure of RI 2 materials. The KLM method has successfully been employed for the discovery of novel ternary nitrides [26,27], ternary oxynitrides [28], and recently 2-D materials [15,29]. The crystal structure search is performed over 100-150 independent seed structures with varying formula units from 1 to 4.…”

Intrinsic Valley Polarization in Computationally Discovered Two‐Dimensional Ferrovalley Materials: LaI2 and PrI2 Monolayers

“…[ 40 ] The crystal structures of bulk LaI 2 and PrI 2 were computed using unconstrained crystal structure search, kinetically limited minimization (KLM) algorithm. [ 41,42 ] The structure search was performed over several formula units of LaI 2 and PrI 2 , each with more than 100 independent seed structures. The detailed description of the KLM method has been discussed in ref.…”

“…The detailed description of the KLM method has been discussed in ref. [41]. The layered structure of LaI 2 and PrI 2 was determined using the KLM algorithm without any bias or constraints to a layered or a 3D structure.…”