On-line compositional measurements of AuAg aerosol nanoparticles using optical emission from spark ablation

Summary, in English

Spark ablation is an established method for generating aerosol nanoparticles. By changing the electrodes, synthesis of monometallic, multimetallic and semiconducting nanoparticles has been demonstrated. Apart from using electrodes of specific composition, compositional tuning of bimetallic nanoparticles during synthesis has recently been demonstrated (Kohut, et al., 2021). In many applications, it is desirable to have a specific stoichiometry and monitoring the composition on-line provides important feedback during the process and for the samples generated. Common methods to determine aerosol composition involves lengthy sampling and off-line characterization. Most on-line
tools are complex and expensive to operate. In both cases, the characterization is destructive. There is a need for fast and low-cost methods that can give rapid compositional feedback during synthesis.

Optical diagnostics is a promising approach for aerosol monitoring due to the on-line and non-destructive capabilities (Samuelsson, et al., 2021). Analysing the optical emission during the spark discharges can provide valuable information related to the nanoparticle properties, including their composition. In this work, we demonstrate a simple setup to monitor the composition of AuAg aerosol nanoparticles generated by spark ablation using optical emission from the discharges on-line. The optical setup
cost was low by using an untriggered spectrometer with long integration time. The complex optical spectra were related to the AuAg nanoparticle composition, measured by an aerosol X-ray fluorescence (XRF) setup, by calibration models using the least absolute shrinkage and selection operator (LASSO).

Models trained for varying discharge energies demonstrated good predictability of nanoparticle stoichiometry with mean absolute errors < 10 at. % and root mean square errors comparable to other machine learning techniques. While the models utilized different wavelengths in the predictions, a combined model using spectra from all discharge energies made accurate predictions of the AuAg nanoparticle composition, showing the method’s robustness under variable synthesis conditions. We suggest future improvements to the methodology with respect to hardware and pre-processing to improve the signal-to-background and calibration models.

Kohut, A., Villy, L. P., Kéri, A., Bélteki, Á., Megyeri, D., Hopp, B., . . . Geretovszky, Z. (2021). Full range tuning of the composition of Au/Ag binary nanoparticles by spark discharge generation. Scientific reports, 11, 1–10.

Samuelsson, P., Snellman, M., Magnusson, M. H., Deppert, K., Aldén, M., & Li, Z. (2021). Airborne Gold Nanoparticle Detection Using Photoluminescence Excited with a
Continuous Wave Laser. Applied Spectroscopy, 75, 1402–1409.