AI-SAXS:Decoding Structural Complexity with Intelligent Scat. Analysis

The research project AI-SAXS: intelligent analysis at the nano level aims to use artificial intelligence to interpret complex data from advanced X-ray analysis of materials at the nano and micro level in a faster and more accurate way. The project develops methods that will simplify and improve the understanding of the internal structures of materials, which in turn enables better control and optimization in manufacturing processes. The AI-based analysis is intended to be a powerful tool for many industries where material properties at the microscopic level are of great importance.

Complex dissemination data

In the project, RISE is collaborating with the MAX IV national research laboratory, AstraZeneca and Tetra Pak. By combining MAX IV's advanced X-ray technology, such as Small-Angle X-ray Scattering (SAXS), with AI methods such as machine learning, large amounts of data can be analyzed more efficiently than before. The SAXS method involves sending extremely bright X-rays towards the material, where they scatter in different ways depending on the material's internal structure. The scattering data collected is complex and extensive, making interpretation time-consuming and challenging for researchers. By training AI models on both synthetic and experimental data, the project can create algorithms that learn to recognize and interpret patterns in the scattering curves. This contributes to faster, more accurate analysis and reduces the need for manual estimation and model testing. At the same time, the project aims to develop general solutions that can be adapted to different materials and needs, increasing the potential for wider use in industry.

More efficient processes and more sustainable products

For companies such as AstraZeneca and Tetra Pak, this means improved understanding of how the nanostructures of materials affect product properties - for example, drug carriers or the behavior of packaging materials under different environmental conditions. This in turn provides better control over production and quality, which can lead to more efficient processes and more sustainable products. RISE contributes to the project with cutting-edge expertise in chemical analysis, materials science and AI, and leads the collaboration between industry and research environments. A postdoc from RISE is stationed at MAX IV to work closely with the partners and ensure a smooth transfer of knowledge and technology between research and industrial applications.

AI-SAXS is funded through Vinnova's Advanced Digitization program and runs from November 2023 to November 2026. The project is an example of how new technologies and interdisciplinary collaboration can pave the way for innovations that strengthen Swedish industry and research in materials science.