Visual Artificial Tongue for Quantitative Metal-Cation Analysis by an Off-the-Shelf Dye Array

Title
Visual Artificial Tongue for Quantitative Metal-Cation Analysis by an Off-the-Shelf Dye Array
Authors
이제욱이준석강미라Su Andrew I장영태
Keywords
metal discrimination; colorimetric sensor array; alkali metals; cations; dyes/pigments; hierarchical-cluster analysis; principal-component analysis
Issue Date
2006-07
Publisher
Chemistry : a European journal
Citation
VOL 12, NO 22, 5691-5696
Abstract
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,i ncluding 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 mm 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 mm down to 0.33 μM),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%).
URI
http://pubs.kist.re.kr/handle/201004/37518
ISSN
0947-6539
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KIST Publication > Article
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