**6. Conclusions (when using a large-size ICP spectrometer)**

Shallow depth ANNs for spectral interference correction were experimentally evaluated using a large-size ICP spectrometer with a scanning monochromator (**Figure 8**) that had resolution typical of commercial systems. The ability of ANNs to predict the concentration of an Analyte (**A**) in a mixture of **A** with an Interferent (**I**) was used a key figure-of-merit and it was studied extensively (**Figures 10** and **11**). To validate predictive ability, predicted **A** concentrations by ANNs were compared with those obtained by PLS. Using experimental spectral scans, the average prediction error for ANNs was 4.1% and for PLS was 4.4%. Simulations were used to understand the origin of prediction errors for both of these methods. The average errors in predictive ability for simulated spectral scans and for Analyte (**A)** by ANNs was 5.0% and for PLS was 5.1%. The higher errors obtained when using simulations over those obtained when using experimentally obtained spectral scans is likely due to use of high (by experimental standards) levels of noise. When low levels of noise were used, the prediction errors were less than 1% (**Figure 11**). In other words the predicted concentrations by both methods were essentially error free. Clearly, methods capable of better discriminating between signals and noise are desirable.

ANNs may also find applicability in portable, miniaturized systems that can be used for *"taking part of the lab to the sample"* types of applications. Due to the short focal length of portable spectrometers employed in miniaturized systems, such spectrometers suffer from significant spectral overlaps (but not from wavelength shift). Interference using miniaturized systems will be discussed next.
