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Corrective protocol to predict interference free sensor response for paper-based solution sampling coupled with heavy

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This study addresses heavy metal ion detection challenges using paper-based potentiometric sensors. A new corrective protocol predicts accurate sensor responses by accounting for ion adsorption on paper substrates without modifications.

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Area of Science:

  • Analytical Chemistry
  • Electrochemistry
  • Materials Science

Background:

  • Paper-based microfluidics offers a low-cost platform for chemical sensing.
  • Detecting heavy metal ions using paper substrates is hindered by ion adsorption.
  • Existing methods often require paper substrate modifications to prevent ion adsorption.

Purpose of the Study:

  • To quantitatively investigate heavy metal ion adsorption on paper substrates during potentiometric measurements.
  • To explain the super-Nernstian response observed in paper-based potentiometric sensors.
  • To develop a corrective protocol for accurate heavy metal ion detection without paper modification.

Main Methods:

  • Quantitative investigation of heavy metal ion adsorption on paper substrates.
  • Development of a corrective potential protocol for potentiometric sensors.
  • Analysis of competitive ion adsorption in mixed metal ion solutions.
  • Validation of the protocol for interference-free sensor response prediction.

Main Results:

  • Heavy metal ion adsorption on paper substrates was quantitatively measured.
  • Ion adsorption was identified as the cause of super-Nernstian sensor responses due to local ion depletion.
  • A corrective potential protocol was successfully established to predict interference-free sensor responses.
  • The method accurately predicts sensor responses for mixed ion solutions without paper modification.

Conclusions:

  • A novel, modification-free corrective protocol enables accurate heavy metal ion detection using paper-based potentiometric sensors.
  • Understanding and correcting for ion adsorption on paper substrates is crucial for reliable sensing.
  • This approach simplifies paper-based sensing by focusing on potential readout correction rather than substrate alteration.