Engineering a Graphene Quantum Dot‐Enhanced Surface Plasmon Resonance Sensor for Ultra‐Sensitive Detection of Hg<sup>2</sup>⁺ Ions

Abstract The contamination of soil and water by heavy metals poses a significant environmental and public health concern worldwide. To address this issue, a novel graphene quantum dot (GQD)‐based surface plasmon resonance (SPR) sensor is developed for the detection of mercury ions (Hg 2+ ), a notorious heavy metal pollutant. The thiol and amine‐functionalized GQDs (S,N‐GQDs), synthesized via pyrolysis of citric acid and L‐cysteine, are directly immobilized onto the SPR chip surface without prior pretreatment, demonstrating their potential as efficient sensing materials. The SPR sensor exhibits high sensitivity and selectivity toward Hg 2+ ions, as confirmed by kinetic binding analysis and isotherm modeling. The Langmuir isotherm model, which accurately describes the interactions between Hg 2+ and S,N‐GQDs, provides insights into the sensor's mechanism of action. Furthermore, the sensor demonstrates robustness and reusability, with recoveries ranging from 98% to 104% over multiple cycles of analysis. Given the presence of contaminants in tap water, the developed sensor system holds significant importance for environmental monitoring and public health protection, offering a rapid, accurate, and cost‐effective solution for detecting Hg 2+ ions in such samples. Overall, this study represents a significant advancement in the field of heavy metal detection, with potential implications for addressing environmental pollution and ensuring water quality.

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Publication Details

Journal
Advanced Materials Interfaces
Published
2024-11-03
DOI
https://doi.org/10.1002/admi.202400679
Citations
8
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
1.87
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article

Engineering a Graphene Quantum Dot‐Enhanced Surface Plasmon Resonance Sensor for Ultra‐Sensitive Detection of Hg2⁺ Ions

Recep Üzek
8 citations
Advanced Materials Interfaces
Advanced biosensing and bioanalysis techniques
1.87
article

Engineering a Graphene Quantum Dot‐Enhanced Surface Plasmon Resonance Sensor for Ultra‐Sensitive Detection of Hg2⁺ Ions

Recep Üzek
article en
8 citations

Abstract

Abstract The contamination of soil and water by heavy metals poses a significant environmental and public health concern worldwide. To address this issue, a novel graphene quantum dot (GQD)‐based surface plasmon resonance (SPR) sensor is developed for the detection of mercury ions (Hg 2+ ), a notorious heavy metal pollutant. The thiol and amine‐functionalized GQDs (S,N‐GQDs), synthesized via pyrolysis of citric acid and L‐cysteine, are directly immobilized onto the SPR chip surface without prior pretreatment, demonstrating their potential as efficient sensing materials. The SPR sensor exhibits high sensitivity and selectivity toward Hg 2+ ions, as confirmed by kinetic binding analysis and isotherm modeling. The Langmuir isotherm model, which accurately describes the interactions between Hg 2+ and S,N‐GQDs, provides insights into the sensor's mechanism of action. Furthermore, the sensor demonstrates robustness and reusability, with recoveries ranging from 98% to 104% over multiple cycles of analysis. Given the presence of contaminants in tap water, the developed sensor system holds significant importance for environmental monitoring and public health protection, offering a rapid, accurate, and cost‐effective solution for detecting Hg 2+ ions in such samples. Overall, this study represents a significant advancement in the field of heavy metal detection, with potential implications for addressing environmental pollution and ensuring water quality.

Advanced Materials InterfacesVol. 12(5)
Hacettepe University (TR)
Clean water and sanitation
Openalex Percentile: Top 14%
Advanced biosensing and bioanalysis techniques
1.87
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Engineering a Graphene Quantum Dot‐Enhanced Surface Plasmon Resonance Sensor for Ultra‐Sensitive Detection of Hg<sup>2</sup>⁺ Ions — Recep Üzek · Advanced Materials Interfaces (2024) | TGRS Research Map | TGRS