AIXtal is an accessible refinement platform designed to simplify structural analysis in crystallography, particularly for first-time users. It features an intuitive interface, tutorials, tooltips, and modular plugin support for functionalities such as AI assistance, helping users refine X-ray and neutron diffraction data. Ongoing developments are making AIXtal increasingly attractive not only to newcomers but also to experienced researchers. The successful student testing conducted in April 2025 has validated the platform's capabilities. This update introduces new minimal-sized Dockerfiles for AIXtal components and includes a sample docker-compose.yaml for full-stack deployment. Production-ready versioned images are now used instead of operating within a developer environment; these images are currently hosted on RWTH GitLab and will move to DAPHNE GitLab after further testing. During Noah Nachtigall's successful PhD defense, the collaboration between X-ray and neutron diffraction techniques, the university's resources, and DAPHNE use cases was highlighted, showcasing AIXtal's role in integrating these components. The preliminary implementation of multidimensional (2D) Rietveld refinement has been completed, along with various quality-of-life improvements that enhance overall performance. Improvements in responsiveness have been achieved through "triggered" database events, enabling cooperative refinements among users. A significant focus has been placed on enhancing both user documentation and developer experience. Extensive documentation has been developed to support users effectively, while additional resources for developers include comprehensive unit tests, UI integration tests, and database integration tests to ensure robustness.
Nachtigall et al. (Mon,) studied this question.
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