Premium
Application of partial least‐squares regression for signal resolution in differential pulse anodic stripping voltammetry of thallium and lead
Author(s) -
Henrion André,
Henrion René,
Henrion Günter,
Scholz Fritz
Publication year - 1990
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.1140020408
Subject(s) - partial least squares regression , thallium , anodic stripping voltammetry , analytical chemistry (journal) , stripping (fiber) , chemistry , analyte , resolution (logic) , voltammetry , linear regression , signal (programming language) , pulse (music) , calibration , materials science , mathematics , electrode , statistics , inorganic chemistry , chromatography , electrochemistry , computer science , physics , optics , detector , composite material , artificial intelligence , programming language
This work addresses the problem of signal resolution by partial least‐squares regression (PLS) for differential pulse stripping voltammograms. The performance of PLS is demonstrated for an example of calibration with mixtures of two analytes (Tl + and Pb 2+ ) with strongly overlapping voltammograms. The accuracy of the determination of concentrations for validation mixtures was found to be considerably higher with PLS than with simple evaluation using currents observed at two potentials (requiring resolution of a system of two linear equations with two unknowns). Hence, PLS is recommended for computer‐assisted, on‐line voltammetric analysis of multicomponent systems.