9 Early Career Investigators in Mineralogy and Crystallography

This session provides a platform for early-career mineralogists and crystallographers to share their research. Early-career, postdoctoral, and student researchers are encouraged to submit abstracts and provide fresh perspectives, new ideas, and creative answers to mineralogical problems.

Sunday, 19 October 2025
8:00 AM - 12:00 PM
HBGCC, 214D

AI for Crystallography: Introducing “Crystract”, an R package to Read and Analyze CIF Files

Paper number: 9-8
Program: Technical Sessions
Time: 9:55 AM – 10:10 AM

Authors

Abstract

Solid matter consists of three-dimensional arrangements of individual atoms predominantly organized in repeating patterns (motifs). We can directly relate properties of materials, both of natural and synthetic origin to their structural arrangement, regardless if they belong to the classes of organics, polymers, or inorganics. For example, the arrangement of carbon atoms leads to the stark difference between diamond and graphite. The large-scale analysis of crystal structures is fundamental not just to the understanding of minerals and their evolution through time, but also can be employed towards the design of new materials. As crystallographic databases continue to expand, the need for powerful computation tools to harness their information has become critical. 

The Crystallographic Information File (CIF) is the standard for disseminating this data, yet researchers face a significant bottleneck in its programmatic use. Manual data extraction is tedious, and syntactic inconsistencies in CIF files complicate high-throughput analysis, forcing researchers into fragmented workflows between different software environments. To improve reproducibility and hasten the speed of discovery, we have developed “Crystract”, an open-source R package designed to overcome these challenges by providing an efficient solution for the batch processing and statistical analysis of CIF data. The package streamlines the extraction of essential information including unit cell parameters, atomic coordinates, and symmetry operations. A key feature of “Crystract” is its ability to propagate experimental uncertainties from the CIFs through derived quantities, such as interatomic distances and bond angles, facilitating a more rigorous statistical treatment.

We also implement established algorithms to generate full unit cells and determine atomic bonding environments. By integrating these tools directly within the R statistical environment, “Crystract” provides a seamless workflow for crystallographic analysis. As a fully open-source package to be made available on the Comprehensive R Archive Network (CRAN), “Crystract” promotes reproducible, data-driven research in the Crystallographic research across Earth and Space Science.

Geological Society of America Abstracts with Programs. Vol. 57, No. 6

doi: 10.1130/abs/2025AM-414267

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