CATS, a new theme at LINXS, aims to make advanced computational tools for interpreting X-ray and neutron scattering data more accessible. By making the tools available through standardised software, and providing training and tutorials, the long-term goal is to support more informative interpretations and generate new scientific knowledge.

Mikael Lund. Photo. — Mikael Lund highlights how computational tools give researchers more information about their sample in comparison to the standard tools in use today. This information can generate new scientific knowledge and data analysis,

“Many of us who work in computational chemistry sit on modelling tools that we have developed for scattering data in the last ten years. But these tools are currently not readily available, require a lot of prior knowledge to use, and take a long time to analyse data,” says theme leader Mikael Lund, Professor in Computational Chemistry at Lund University.

Mikael Lund was one of the first LINXS fellows when the institute launched in 2017. It was through LINXS that he started developing computational tools to interpret X-ray and neutron scattering data from soft matter and biological systems. Since then, he has been a member of two other themes but has never led one himself. Until now.

“Now is the right time for such a theme. We have the contacts, the know-how, and the right people to bring these tools to X-ray and neutron users.”

Making the tools more accessible is a major focus within the theme. This entails both including them in standard workflows and small-angle scattering analysis software packages, and organising workshops, hackathons and tutorials for the user community on how to use the tools in practice.

“The most important thing is to ensure that the tools are available to users, and to make people interested in testing them out. Researchers tend to choose the tools that are easy to use, so even the most advanced methods need to be accessible to make a difference.”

Advanced tools give more information about samples

Mikael Lund highlights how computational tools give researchers more information about their sample in comparison to the standard tools in use today. One reason is that simpler tools tend to rely on rough approximation to make calculations easier. Proteins are e.g. treated as spheres, even though they are highly complex macromolecules whose functions depend entirely on their specific shapes and dynamic movements.

“With standard tools you miss out on interpretation, and often cannot infer why a protein behaves in a certain way. It also makes it harder to understand how changes to your protein will change the results of the experiment.”

“In contrast, our tools get closer to reality because you can see the real shape of the protein and use that information to predict its behaviour.”

Supporting synergy between modelling and experimental research

The use of computational tools can not only aid data interpretation but also support more targeted, and even entirely new types of experiments, which in turn creates more refined and accurate modelling tools, Mikael Lund emphasises.

“The ideal synergy between modelling and experimental research is that they inform and build on each other in an iterative process. You feed your data into the model, which predicts a certain process or behaviour, that you can then test in your next experiment. The data from that experiment feeds into the model again, in a loop.”

Ultimately this workflow can help maximise the output from experiments at facilities like MAX IV or ESS – that are expensive to perform. However, one challenge to using computational tools more widely is that their high resolution makes them slower to run than most standard tools currently in use. The theme members will therefore focus on how to reduce the time it takes for certain models to render results.

“Experimental users don’t want to wait for two weeks to see results. If we can speed up our existing models, we will be able to put them in the hands of many more people.”

An opportunity to bring people from different backgrounds together

Mikael Lund is excited to run the theme at LINXS – because it is quite rare to get support for initiatives such as CATS which centres around knowledge exchange, education and networking. The theme will gather researchers, X-ray and neutron users, and instrument scientists.

“It is great to have a platform to connect people who are working on very similar things but have never met before. I think this can generate lots of new ideas in terms of developing the tools we already use and making them more accessible.”

About the theme CATS: Accessible Computational Scattering Tools

The theme will start in early 2027 and work across five working groups: Working Group 1: Simulation-Based Structure Factors; Working Group 2: Numerical Theory for Structure Factors; Working Group 3: Hydration, Solvation, and Coarse-Grained Scattering Models; Working Group 4: Intrinsically Disordered Proteins and Flexible Systems; and Working Group 5: End-User Integration and Training.