Atomization of gold nanoparticles in graphite furnace AAS: Modelling and simulative exploration of experimental results

This study expands the recent experimental investigations, which have shown the possibility to differentiate between nanoparticles (NPs) and metal ions in graphite furnace atomic absorption spectroscopy (GFAAS). Lately, the simultaneous sizing and quantification of Gold NPs was shown experimentally. In this contribution, the experimental results are transferred to a computational model, which enables the possibility to simulate the obtained experimental results. Overfitting is avoided by a minimal number of parameters. With this model, the experimental absorbance signals are extrapolated from one fitting point for changing particle sizes, different analyte concentrations and heating rates. Analyte concentration is predictable over the whole range (5 ppb - 45 ppb) of experimental datapoints. Limits are observed for very small particles (dP < 40 nm) due to the nano effect and for changing heating rates (100 - 750 K s-1) due to model simplicity. For a given temperature program, the precision of the simulated absorbance signals is comparable to experimental ones. Further, the excellent agreement is used to substitute experimental calibration points. The presented method, named simulationassisted calibration, is evaluated with reference to experimental results. The analysis of the comparison shows eminent agreement for the used concentration range and NPs unaffected by the nano effect. The simulationassisted calibration is therefore competitive to the experimental calibration. On the basis of typical expenditure of time for the experimental calibration steps, two scenarios of a simulation-assisted calibration are presented, reducing calibration time up to 80%.

Automated summary

This study combines experimental and computational modeling to achieve simultaneous sizing and quantification of gold nanoparticles. The simulation-assisted calibration method shows competitiveness and can reduce calibration time by up to 80%.