Visual artificial tongue for quantitative metal-cation analysis by an off-the-shelf dye array

Area of Science:

• Analytical Chemistry
• Chemical Sensing
• Spectroscopy

Background:

• Developing selective and sensitive methods for cation detection is crucial in environmental monitoring, industrial processes, and biomedical research.
• Existing methods often face challenges in distinguishing between similar ions or require complex sample preparation.

Purpose of the Study:

• To develop and validate a high-throughput chemical-probe array for the simultaneous identification and quantitation of multiple cation analytes.
• To assess the array's performance in terms of accuracy, detection limits, and distinguishability of various cations.

Main Methods:

• Preparation of a solution-based chemical-probe array (New York Tongue 1: NYT-1) using 47 off-the-shelf dyes.
• Analysis of cation solutions (44 metal ions, H+, NH4+, TBA) across a range of concentrations.
• Application of multivariate statistical methods, including principal-component analysis (PCA) and hierarchical-cluster analysis (HCA), for data interpretation.

Main Results:

• The array demonstrated high accuracy, with 99.4% correct identification of analytes (treating alkali metals as a group) and 96.8% correct concentration determination within the working range (0.33 microM to 10 mM).
• Most cations were clearly distinguishable at 10 mM, with practical detection limits determined for each analyte.
• Alkali-metal ions showed similar responses but were manageable as a group.

Conclusions:

• The developed chemical-probe array provides a robust and efficient platform for the simultaneous analysis of diverse cation analytes.
• This approach offers a significant advancement in cation sensing, enabling accurate identification and quantification with high success rates.