[Modern spectral estimation of ICP-AES]

Area of Science:

• Analytical Chemistry
• Spectroscopy

Context:

• Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES) is a widely used analytical technique.
• Understanding signal characteristics is crucial for accurate ICP-AES measurements.
• Traditional spectral analysis methods may have limitations.

Purpose:

• To explore the application of modern spectral estimation techniques to ICP-AES.
• To investigate the use of auto-regression (AR) models for power spectra density (PSD) calculation.
• To evaluate the effectiveness of the Levinson-Durbin recursion method in parameter estimation for ICP-AES.

Summary:

• This study applied modern spectral estimation techniques, specifically auto-regression (AR) models and the Levinson-Durbin recursion method, to analyze inductively coupled plasma atomic emission spectrometry (ICP-AES) signals.
• Power spectra density (PSD) was computed using estimated AR model parameters.
• The results demonstrated that these spectral estimation methods provide valuable insights into spectral composition and signal characteristics of ICP-AES.

Impact:

• The findings suggest that modern spectral estimation offers a more profound understanding of ICP-AES spectral data.
• This improved understanding can lead to enhanced accuracy and reliability in ICP-AES analyses.
• The technique provides a valuable tool for researchers working with ICP-AES instrumentation.