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Graphyne-supported manganese single-atom nanozyme sensor array for bisphenol identification.

Jianing Xia1, Ruixue Fu1, Zhen Li1

  • 1Department of Chemistry & Institute for Sustainable Energy, College of Sciences, Shanghai University, Shanghai, 200444, PR China.

Talanta
|December 8, 2024
PubMed
Summary

This study developed a novel colorimetric sensor array using manganese nanozymes to detect multiple bisphenols, common in food packaging. The sensor offers a rapid, low-cost method for enhancing food safety by identifying these potentially harmful hormone-disrupting chemicals.

Keywords:
GraphyneManganese-basedSensor arraySingle-atom nanozyme

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Area of Science:

  • Analytical Chemistry
  • Materials Science
  • Environmental Science

Background:

  • Bisphenols are widely used in food packaging, posing health risks due to potential hormone disruption.
  • Existing detection methods for bisphenols are often costly, slow, or lack the ability to detect multiple compounds simultaneously.
  • There is a critical need for rapid, low-cost, and high-throughput methods for detecting various bisphenols in food products.

Purpose of the Study:

  • To develop a novel, high-throughput colorimetric sensor array for the simultaneous detection of multiple bisphenols.
  • To synthesize and characterize manganese single-atom nanozymes supported on graphyne for enhanced peroxidase-like activity.
  • To evaluate the sensor array's performance in detecting various bisphenols in complex and real food samples.

Main Methods:

  • Synthesis of manganese single-atom nanozymes (Mn-GY, Mn-GY-2N) supported on graphyne.
  • Construction of a colorimetric sensor array utilizing three types of nanozymes (Mn-GY, Mn-GY-2N, GY-2N).
  • Colorimetric detection based on the differential inhibition of nanozyme activity by various bisphenols.
  • Application of machine learning algorithms for bisphenol identification and quantification.

Main Results:

  • The sensor array demonstrated good linear relationships for the determination of five bisphenols (BPA, BPS, BPF, BPAF, Diphenolic Acid) across a range of concentrations.
  • Achieved low limits of detection (LODs) for the target bisphenols, with values as low as 0.277 μM.
  • Successfully identified and quantified multiple bisphenols in mixed and real food samples with high accuracy and sensitivity.
  • The sensor array showed high throughput and could distinguish structurally similar compounds effectively.

Conclusions:

  • A novel, high-throughput colorimetric sensor array based on manganese nanozymes has been successfully developed for sensitive and accurate detection of multiple bisphenols.
  • This sensor array offers a low-cost, rapid, and simple alternative to traditional methods for bisphenol detection, significantly enhancing food safety monitoring.
  • The integration with machine learning provides a powerful tool for analyzing complex samples and identifying structurally similar compounds, paving the way for future advancements in precise chemical analysis.