Robocrystallographer: automated crystal structure text descriptions and analysis
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Artificial Intelligence Research Letter
Robocrystallographer: automated crystal structure text descriptions and analysis Alex M. Ganose
and Anubhav Jain, Lawrence Berkeley National Laboratory, Energy Technologies Area, 1 Cyclotron Road, Berkeley, CA 94720, USA
Address all correspondence to Anubhav Jain at [email protected] (Received 14 January 2019; accepted 1 July 2019)
Abstract Our ability to describe crystal structure features is of crucial importance when attempting to understand structure–property relationships in the solid state. In this paper, the authors introduce robocrystallographer, an open-source toolkit for analyzing crystal structures. This package combines new and existing open-source analysis tools to provide structural information, including the local coordination and polyhedral type, polyhedral connectivity, octahedral tilt angles, component-dimensionality, and molecule-within-crystal and fuzzy prototype identification. Using this information, robocrystallographer can generate text-based descriptions of crystal structures that resemble descriptions written by human crystallographers. The authors use robocrystallographer to investigate the dimensionalities of all compounds in the Materials Project database and highlight its potential in machine learning studies.
Introduction The crystal structure of a material plays a fundamental role in determining its properties.[1,2] This is best exemplified by carbon allotropes[3]—diamond is extremely hard and electrically insulating, whereas graphite is soft and semi-metallic. Even minor structural modifications can have a profound effect on a broad array of properties, ranging from ferroelectricity and piezoelectricity (e.g., phase-dependent ferroelectricity in BaTiO3)[4] to conductivity (e.g., metal to insulator Peierls distortions)[5] and photocatalytic activity (e.g., observed only in Rutile rather than Anatase TiO2).[6] Accordingly, our ability to describe and understand such structural features is of crucial importance when characterizing new and existing materials.[7] There now exists an increasing number of packages for programmatically analyzing crystal structures. These mainly fall into two categories. The first provides information on the global structure, such as the dimensionality,[8–11] the symmetry information,[12] and whether the structure matches a known mineral prototype.[13] The second analyzes local coordination environments and site geometries (e.g., the recent ChemEnv[14] and LocalEnv[15] packages). Currently, however, there are not yet tools for describing semi-local structure, i.e., how the local geometry connects throughout space to form the overall structure (Fig. 1). Furthermore, to our knowledge, no package provides human-readable descriptions of crystal structure resembling that found in a journal article. In this paper, we introduce robocrystallographer, an opensource toolkit for analyzing crystal structures. We illustrate how robocrystallographer can extract local, semi-local, and
global structure features, and use these to generate
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