Mapping the local stoichiometry in Cu nanoparticles during controlled oxidation by STEM-EELS spectral imaging.

Copper nanoparticles (NPs) can be coupled with cuprous oxide, combining photoelectrocatalytic properties with a broad-range optical absorption. In the present study, we aimed to correlate changes in morphology, electronic structure and plasmonic properties of Cu NPs at different stages of oxidation. We demonstrated the ability to monitor the oxidation of NPs at the nanometric level using STEM-EELS spectral maps, which were analyzed with machine learning algorithms. The oxidation process was explored by exposing Cu NPs to air plasma, revealing systematic changes in their morphology and composition. Initial plasma exposure created a CuO shell, while prolonged exposure resulted in hollow structures with a CuO shell. This study identified procedures to obtain a material with CuO surface stoichiometry and absorption extended into the near-infrared range. Moreover, this study introduced a novel application of machine learning clustering techniques to analyze the morphological and chemical evolution of a nanostructured sample.