# Structure-mining: screening structure models by automated fitting to the atomic pair distribution function over large numbers of models

## TL;DR

This paper introduces an automated method for screening candidate atomic structures from PDF data by fetching and refining models from databases, significantly streamlining structure determination for various materials.

## Contribution

The authors present a fully automated approach that integrates database fetching and structure refinement to identify crystal structures from PDF data without human intervention.

## Key findings

- Effective in identifying correct structures across diverse materials
- Works with both x-ray and neutron PDF data
- Applicable to crystalline, nanocrystalline, and complex materials

## Abstract

A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenter's search criteria and performs structure refinements on them without human intervention. It supports both x-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowires, low-symmetry and locally distorted structures, and complicated doped and magnetic materials. This approach could greatly reduce the traditional structure searching work and enable the possibility of high-throughput real-time auto analysis PDF experiments in the future.