Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

Abstract

Structure-property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packedlike environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for elementspecific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2 -spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

Identifying promising metal–organic frameworks for heterogeneous catalysis via high‐throughput periodic density functional theory

“…Identify or construct a dataset of MOF crystal structures to study. Tools such as Pymatgen and Zeo++ can be used to select MOFs with specific metals, coordination environments, and pore sizes relevant to the given reaction of interest. Using DFT, optimize the unit cell volume, unit cell shape, and internal degrees of freedom (i.e., atomic positions) for each MOF. Starting from the optimized MOF structures, initialize the positions of atomic and molecular adsorbates required to predict catalytic activity via (1). Using DFT, relax the atomic positions of the structures generated via (4). Compute the catalytic descriptors of interest to rank MOF candidates. For promising MOF candidates, generate the potential energy diagram for the proposed mechanism and perform detailed electronic structure analyses to better understand the reaction kinetics.…”

PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators

“…PyCDT uses an effective and easily extendable approach for interstitial site finding (Interstitial Finding Tool: In-FiT) that has been recently introduced by Zimmermann et al [36]. The procedure systematically searches for tentative interstitial sites by employing coordination pattern-recognition capabilities [67,68] implemented in pymatgen [3].…”

First-Principles Investigation of Native Interstitial Diffusion in Cr2O3

“…In addition to PyCDT and pymatgen, we utilized phonopy [36], and VESTA [37] for generating inputs to DFT calculations, post-processing, and plotting the DFT calculations results. The order-parameter based interstitial finding algorithm introduced by Zimmerman et al [28] identified five potential interstitial sites and their positions are shown in Figure 1. Among the potential interstitial sites, three are tetrahedral sites and the remaining two are octahedral sites, which are defined by their coordination numbers as well as the coordinating elements.…”