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

Area of Science:

• Materials Science
• Nanotechnology
• Surface Chemistry

Background:

• Copper nanoparticles (NPs) exhibit promising photoelectrocatalytic properties and broad optical absorption.
• Controlling the oxidation state of copper NPs is crucial for tuning their electronic and plasmonic characteristics.
• Understanding nanoscale oxidation is key for developing advanced nanomaterials.

Purpose of the Study:

• To correlate morphological, electronic, and plasmonic property changes in copper NPs during oxidation.
• To investigate the oxidation process of copper NPs induced by air plasma exposure.
• To apply machine learning for analyzing nanoscale material evolution.

Main Methods:

• Utilized scanning transmission electron microscopy with electron energy loss spectroscopy (STEM-EELS) for nanoscale analysis.
• Employed machine learning clustering algorithms to interpret spectral maps and track compositional changes.
• Controlled oxidation of copper NPs via controlled exposure to air plasma.

Main Results:

• Demonstrated real-time monitoring of NP oxidation at the nanometric level.
• Observed the formation of a cuprous oxide (Cu2O) shell followed by hollow structures with a cupric oxide (CuO) shell upon prolonged plasma exposure.
• Achieved a Cu2O surface stoichiometry with optical absorption extending into the near-infrared (NIR) range.

Conclusions:

• Established a method to precisely control copper NP oxidation states and morphology.
• Highlighted the efficacy of machine learning in analyzing complex nanostructure evolution.
• Identified procedures for creating copper-based nanomaterials with tailored NIR absorption properties for potential applications.