A picture is worth a thousand diffraction spots: using photometry and computer vision to perform rapid high-throughput sample-versatile serial crystallography

Coulson, Ben A., Lewis, Sam G., Orr, Christian, Hatcher, Lauren E. ORCID: https://orcid.org/0000-0002-1549-9727, Allan, David R. and Warren, Mark 2026. A picture is worth a thousand diffraction spots: using photometry and computer vision to perform rapid high-throughput sample-versatile serial crystallography. IUCrJ 13 (4) 10.1107/s2052252526003568

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Abstract

The `photometric selection' approach as a high throughput, sample tolerant, low cost and highly automatable method of carrying out serial crystallography is presented. Crystalline samples are loaded and distributed onto a simple transparent substrate and an in-line camera identifies crystals using image recognition algorithms from the computer vision project OpenCV. In contrast to established serial techniques, which generally require that crystal samples be refined with narrow size distributions and defined habits, the sample requirements when using photometric selection are shown to be minimal. We demonstrate how broadly effective photometric selection can be by collecting high-quality datasets from three exemplar systems: a small-mol­ecule organometallic, a small-mol­ecule organic and a metal–organic framework system. In contrast to previously established grid-scanning techniques, data collection using photometric selection can be up to six times faster.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Chemistry
Publisher:	International Union of Crystallography
ISSN:	2052-2525
Date of First Compliant Deposit:	26 May 2026
Date of Acceptance:	7 April 2026
Last Modified:	25 Aug 2026 22:11
URI:	https://orca.cardiff.ac.uk/id/eprint/187209

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