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PubMed · 10695130

Visual and colorimetric lithium ion sensing based on digital color analysis.

Abstract

A new optical analytical method, "Digital Color Analysis (DCA)", is proposed based on a digital color analyzer instead of the conventional optical methodology, "Spectrophotometry". The digital color analyzer is a hand-held-size instrument for measuring "colors", and it can transform the color information into numerical values, color library data, etc., that can be treated as analytical information. DCA gives us a more informative analytical method than spectrophotometry by treating colors as digital information. In addition, DCA can also simulate the optimum color variations for optimization of the visual sensor with computer assistance. By utilizing colors as digital information, colorimetric analysis that has been used for only semiquantitative analysis can serve as an accurate determination method. On the basis of DCA, we developed a plasticized PVC film optode and a paper optode for Li+ determination in saliva. After the optimization of color variation and the detection range for the Li+ measurements, the optode membrane gives colorless gray in the Li+ therapeutic range (at 10(-3) M) in saliva. Consequently, whether or not the optimum therapeutic Li+ concentration is maintained can be easily evaluated with these optodes. Especially, the sensing paper optode can be easily handled within a short measurement time (approximately 80 s) which is suitable for home use. Using the digital color analyzer with QxQy coordinates, a linear relation calibration curve can be obtained over the range from 10(-5) to 10(-1) M Li+, in which the analyzer can detect a concentration difference of approximately 0.1 mM Li+. For the near future, an accurate and simple analysis is needed for a health check at home that does not require going to a hospital. The optode based on DCA has great potential for this analytical purpose.

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BibTeXRIS

E Hirayama, T Sugiyama, H Hisamoto, K Suzuki. 2000-02-01. Visual and colorimetric lithium ion sensing based on digital color analysis.. https://doi.org/10.1021/ac990588w

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