In-situ characterization of metal nanoparticles and their organic coatings using laser-vaporization aerosol mass spectrometry

The development of methods to produce nanoparticles with unique properties via the aerosol route is progressing rapidly. Typical characterization techniques extract particles from the synthesis process for subsequent offline analysis, which may alter the particle characteristics. In this work, we use laser-vaporization aerosol mass spectrometry (LV-AMS) with 70-eV electron ionization for real-time, in-situ nanoparticle characterization. The particle characteristics are examined for various aerosol synthesis methods, degrees of sintering, and for controlled condensation of organic material to simulate surface coating/functionalization. The LV-AMS is used to characterize several types of metal nanoparticles (Ag, Au, Pd, PdAg, Fe, Ni, and Cu). The degree of oxidation of the Fe and Ni nanoparticles is found to increase with increased sintering temperature, while the surface organic-impurity content of the metal particles decreases with increased sintering temperature. For aggregate metal particles, the organic-impurity content is found to be similar to that of a monolayer. By comparing different equivalent-diameter measurements, we demonstrate that the LV-AMS can be used in tandem with a differential mobility analyzer to determine the compactness of synthesized metal particles, both during sintering and during material addition for surface functionalization. Further, materials supplied to the particle production line downstream of the particle generators are found to reach the generators as contaminants. The capacity for such in-situ observations is important, as it facilitates rapid response to undesired behavior within the particle production process. This study demonstrates the utility of real-time, in-situ aerosol mass spectrometric measurements to characterize metal nanoparticles obtained directly from the synthesis process line, including their chemical composition, shape, and contamination, providing the potential for effective optimization of process operating parameters.