On the trail of the missing hydrogen atoms Villigen, 11.06.2026 — To simulate the properties of materials, researchers use crystal structures of materials stored in databases. Often, however, these lack the positions of the hydrogen atoms. Researchers at the Paul Scherrer Institute PSI have now trained an artificial intelligence system to reconstruct these positions very quickly and efficiently. Their new method, called XtalPaint, will make it possible to simulate materials more accurately for a variety of applications: from efficient hydrogen storage to new batteries. Artificial intelligence is often used to generate images. In research, specialised AI models are used for scientific applications – for example, to predict the positions of atoms in materials. The MatterGen model developed by Microsoft can generate complex crystal structures from just a few pieces of information – which atoms should be present and in what proportions – and researchers can then use these structures for computer simulations of new materials. Now a scientific team led by Giovanni Pizzi from the PSI Center for Scientific Computing, Theory and Data, together with researchers from the universities of Parma and Modena in Italy, has found a way to use AI to solve a practical problem in materials science: locating missing atomic positions in otherwise known structures. As they report in the journal npj Computational Materials, the materials scientists used an approach normally employed in image processing or computer vision, that is, recognition and interpretation of visual information by means of AI. This allows materials that are experimentally known but have been theoretically inaccessible to be simulated for the first time or significantly better than before. Thus the researchers are contributing to the exploration of new materials with special properties, for hydrogen storage for example, or potentially for the development of new superconductors. “Invisible” hydrogen atoms “For our simulations