Researchers at the Nanoscience Center and Faculty of Information Technology in the University of Jyväskylä, Finland, have achieved a significant step forward in predicting atomic structures of hybrid nanoparticles. A research article published in Nature Communications on 3 September 2019, demonstrates a new algorithm that learns to predict binding sites of molecules at the metal-molecule interface of hybrid nanoparticles by using already published experimental structural information on nanoparticle reference systems. The algorithm can in principle be applied to any nanometer-size structure consisting of metals and molecules provided that some structural information already exists on the corresponding systems. The research was funded by the AIPSE research program of the Academy of Finland (Novel Applications of Artificial Intelligence in Physical Sciences and Engineering Research). Nanometre-sized hybrid metal nanoparticles have many applications in different processes, including catalysis, nanoelectronics, nanomedicine and biological imaging. Often, it is important to know the detailed atomic structure of the particle in order to understand its functionality.