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Engineering Molecular Recognition with Bio-mimetic Polymers on Single Walled Carbon Nanotubes

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Functionalized graphene quantum dots based non-enzymatic sensor for selective tyrosine detection.

Priyadharshini Sriram^1,2, Noel Nesakumar³, John Bosco Balaguru Rayappan^1,2

¹Centre for Nanotechnology & Advanced Biomaterials (CeNTAB), SASTRA Deemed University Thanjavur - 613 401 India rjbosco@ece.sastra.edu +91 4362 264 120 +91 4362 350009.

|January 16, 2026

Summary

This summary is machine-generated.

A novel electrochemical sensor using Graphene Quantum Dots (GQDs) offers rapid detection of tyrosine, crucial for diagnosing tyrosinemia. This advancement aids in timely management of the inherited metabolic disorder in newborns.

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Area of Science:

Biomedical Engineering
Analytical Chemistry
Nanotechnology

Background:

Tyrosinemia is an inherited metabolic disorder resulting from impaired tyrosine breakdown.
Elevated tyrosine levels can lead to severe liver failure and neurological damage in newborns.
Accurate and rapid tyrosine detection is critical for early diagnosis and management.

Purpose of the Study:

To develop a non-enzymatic electrochemical sensor for sensitive and selective tyrosine detection.
To utilize Graphene Quantum Dots (GQDs) functionalized screen-printed carbon electrodes for enhanced sensing capabilities.

Main Methods:

Fabrication of a screen-printed carbon electrode functionalized with Graphene Quantum Dots (GQDs).
Electrochemical characterization of the fabricated sensor for tyrosine detection.
Evaluation of sensor selectivity in the presence of interfering amino acids.

Main Results:

The GQD-functionalized electrode demonstrated efficient binding and recognition of tyrosine.
Achieved a sensitivity of 0.03 µA µM^-1, a detection limit of 0.102 µM, and a linear range of 5-60 µM.
The sensor exhibited high selectivity against potential interfering amino acid species.

Conclusions:

The developed non-enzymatic electrochemical sensor shows significant promise for accurate tyrosine quantification.
The sensor's performance metrics suggest its potential utility in clinical diagnostics for tyrosinemia.
Further testing in clinical samples is warranted to validate its real-world applicability.