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Photodegradation Kinetics and Deep Learning-Based Intelligent Colorimetric Method for Bioavailability-Based Dissolved

Jiayi Luo1, Zhaojing Huang1, Shunxing Li1,2

  • 1College of Chemistry, Chemical Engineering & Environmental Science, Minnan Normal University, Zhangzhou 363000, China.

Analytical Chemistry
|October 14, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent system for real-time monitoring of bioavailable iron (Fe(III)) in seawater. The method uses photodegradation kinetics to accurately determine dissolved iron species, predicting phytoplankton uptake.

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Area of Science:

  • Environmental Chemistry
  • Oceanography
  • Analytical Chemistry

Background:

  • Dissolved iron (dFe) photodegradation releases bioavailable Fe(III), crucial for phytoplankton in the euphotic zone.
  • Existing methods for dissolved iron speciation lack the precision needed for bioavailability assessments.
  • There is a critical need for advanced methods to monitor bioavailable iron dynamics in marine environments.

Purpose of the Study:

  • To develop and validate an intelligent system for real-time monitoring of newly generated Fe(III) ions.
  • To establish bioavailability-based dissolved iron speciation (BDIS) methods using photodegradation kinetics.
  • To predict algal dissolved iron uptake based on determined iron species.

Main Methods:

  • An intelligent system combining dissolved iron pretreatment and a colorimetric sensor was developed.
  • Photocatalytic-assisted colorimetric sensing coupled with a deep learning model was used for dFe speciation.
  • Photodegradation kinetics, including kinetic constants and photogenerated time, were analyzed.

Main Results:

  • The system accurately determined 3 sources, 6 kinds, and 12 species of dissolved iron within 20 minutes.
  • Bioavailability-based dissolved iron speciation (BDIS) successfully predicted algal dFe-uptake over 4 days (R²=0.85).
  • The findings were supported by the hard and soft acids and bases (HSAB) theory and density functional theory (DFT).

Conclusions:

  • The developed intelligent system offers a novel approach for real-time monitoring of bioavailable iron.
  • Photodegradation kinetics provide a robust basis for dissolved metal speciation and bioavailability assessments.
  • This proof-of-concept demonstrates the potential for advanced analytical methods in marine biogeochemical studies.