From minutes to seconds: Capillary auto-alignment with python and opencv

Samples used for diffraction experiments at the Australian Synchrotron, a research facility in Melbourne, are typically presented as finely ground powders confined inside very thin (1mm or less) glass capillaries. These samples are irradiated with X-rays in order to uncover their atomic crystal structures. Amongst our research areas, we study applications in mining, solar cells, perovskites, hydrogen storage, and geology, where understanding material properties at the atomic level can lead to advancements such as enhancing mineral extraction processes, improving solar cell efficiency, developing better hydrogen storage solutions, and analysing the composition of meteorites.

To ensure good data quality, the capillary needs to rotate precisely around its centre of rotation in front of the X-ray beam. Alignment of the centre of rotation is usually a manual operation that relies on the human eye and expertise to discern that the capillary is straight and stationary while it rotates around its axis; this process can be lengthy, error-prone, and difficult to achieve, especially for non-experts.

In this talk, I will demonstrate how we have united Python, OpenCV, and motion control systems to automate the capillary alignment procedure at the Australian Synchrotron, reducing the time to align a sample from several minutes to just 10 seconds.