The paper, "Stability of Some Ternary 13-Atom Icosahedral Clusters Assessed with Geometric, Electronic, and Thermodynamic Criteria," investigates the stability of small metal nanoclusters using a combination of geometric, electronic, and thermodynamic criteria, drawing on both atomistic simulation and machine learning approaches. The work reflects Dr. Krishnadas' broader research at ZIB into atomic cluster behavior, where machine-learned interatomic potentials are used to model nanocluster properties at scales beyond what traditional DFT methods can reach.
