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Visual Artificial Tongue for Quantitative Metal‐Cation Analysis by an Off‐the‐Shelf Dye Array
Author(s) -
Lee Jae Wook,
Lee JunSeok,
Kang Mira,
Su Andrew I.,
Chang YoungTae
Publication year - 2006
Publication title -
chemistry – a european journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.687
H-Index - 242
eISSN - 1521-3765
pISSN - 0947-6539
DOI - 10.1002/chem.200600307
Subject(s) - analyte , chemistry , absorbance , alkali metal , analytical chemistry (journal) , dilution , principal component analysis , metal ions in aqueous solution , detection limit , electronic tongue , chromatography , metal , organic chemistry , computer science , physics , food science , artificial intelligence , taste , thermodynamics
A chemical‐probe array composed of 47 off‐the‐shelf dyes was prepared in solution format (New York Tongue 1: NYT‐1) and was tested in the identification and quantitation of 47 cation analytes, including 44 metal ions, in addition to H + , NH 4 + , and tetrabutylammonium (TBA). The cation solutions were tested in a series of concentrations and the fold‐change in effective absorbance was analyzed by principal‐component analysis (PCA), hierarchical‐cluster analysis (HCA), and nearest‐neighbor decision to determine both identity and quantity of the analytes. Apart from alkali‐metal ions (Na + , K + , Li + , Cs + , and Rb + ), which behave very similarly to each other due mainly to their low response, most of the cations were clearly distinguishable at 10 m M concentration. The practical detection limit of each analyte was also determined by a sequential dilution and the nearest‐neighbor decision method. In the finalized working analyte concentration range (approximately 10 m M down to 0.33 μ M ), by considering alkali metals as one analyte group, most of the analytes were correctly identified (99.4 %). Furthermore, the success rate at which the concentration of each analyte was correctly determined was also high (96.8 %).