A Dual Approach to Detecting Iron Ions and Analyzing Water Quality
Author | Paramparambath, Sreedevi |
Author | Oflaz, Kamil |
Author | Geetha, Mithra |
Author | El-Azazy, Marwa |
Author | El-Shafie, Ahmed S. |
Author | Sadasivuni, Kishor Kumar |
Available date | 2025-06-19T10:02:29Z |
Publication Date | 2025-04-01 |
Publication Name | Chemistry Africa |
Identifier | http://dx.doi.org/10.1007/s42250-024-01177-w |
Citation | Paramparambath, S., Oflaz, K., Geetha, M. et al. A Dual Approach to Detecting Iron Ions and Analyzing Water Quality. Chemistry Africa 8, 1115–1126 (2025). https://doi.org/10.1007/s42250-024-01177-w |
ISSN | 25225758 |
Abstract | This research establishes the foundation for developing an IoT (internet of things)-enabled sensor developed for the rapid and precise detection of Fe ions (Fe+ 3 and Fe+ 2) in drinking water. The investigation incorporates the utilization of Phenol red (PR), Universal indicator (UI), and Eriochrome black T (EBT) dyes, revealing their effectiveness in Fe ion detection. UV-visible tests and calibration graphs determined remarkably low average detection limits and exhibited stability at varying temperatures. Their exceptional sensitivity and selectivity across all Fe ionic states are crucial for continuous monitoring and on-site testing, making them well-suited for practical applications. Moreover, the limit of detection (LOD) of Fe ions in dyes are found to be 0.0189 mM for PR dye, 0.2 mM for UI, and 0.192 mM for EBT dye solution. Validation of the procedure was achieved right through fabrication of a 3D-printed tool. The integration of RGB (Red Green Blue) analysis with the 3D-printed prototype enabled the assessment and detection of iron ions (Fe+ 3 and Fe+ 2), visually represented in a unique RGB chart. This technical progress involves notable implications for Fe detection, demonstrating its ability for using in evaluating environmental and health conditions. Additionally, this novel approach can replace well established sophisticated instruments due to their rapidity and selectivity. |
Sponsor | Open Access funding provided by the Qatar National Library. This work was supported by the Qatar National Research Fund under Grant No. MME03-1226-210042. The statements made herein are solely the responsibility of the authors. |
Language | en |
Publisher | Springer Nature |
Subject | Corrosion Internet of things (IoT) Iron ions Sensor Water quality |
Type | Article |
Pagination | 1115-1126 |
Issue Number | 3 |
Volume Number | 8 |
ESSN | 2522-5766 |
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