Multi-wavelength internal standardization using inductively coupled plasma optical emission spectrometry

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Trace Analysis

Background:

• Current trace analyte determination methods increasingly use "multi-signal" approaches, relying on instrumental signals for both calibration curve axes.
• Existing multi-signal methods face limitations in sample throughput, matrix effect correction, and the requirement for multiple measurable signals per analyte.
• Multi-wavelength internal standardization (MWIS) is introduced as a novel strategy to overcome these limitations by utilizing multiple emission wavelengths for analytes and internal standards.

Purpose of the Study:

• To introduce and validate Multi-wavelength internal standardization (MWIS) as an advanced calibration technique.
• To demonstrate MWIS's superiority over traditional and other multi-signal calibration methods.
• To showcase MWIS's effectiveness in complex matrices and for analytes with limited spectral signals.

Main Methods:

• Proof-of-concept established using inductively coupled plasma optical emission spectrometry (ICP-OES).
• Spike recovery experiments conducted in complex matrices to assess accuracy and precision.
• Comparison of MWIS performance against traditional calibration and other multi-signal techniques.
• Validation using certified reference materials for comprehensive performance evaluation.

Main Results:

• Analyte recoveries near 100% with relative standard deviations around 1% in complex matrices.
• MWIS outperformed traditional calibration strategies and other multi-signal methods.
• Certified reference material analysis yielded analyte recoveries between 90% and 118%.

Conclusions:

• MWIS provides significant improvements over existing multi-signal calibration techniques, generating numerous calibration points from minimal solutions.
• The method effectively handles analytes with few suitable emission wavelengths, such as Arsenic (As) and Lead (Pb), by monitoring multiple internal standard signals.
• Spectral interferences are readily identifiable and can be excluded from calculations, simplifying data analysis.