A New Electrochemical Sensor for Dopamine Detection Based on Reduced Graphene Oxide Modified with Samarium Oxide
Rodrigo Vieira Blasques1, Vinicius Aparecido Pedro Oliani da Silva2, Amanda Caroline Nascimento Sousa1
1Electrochemistry and Biotechnology Laboratory, University of CEUMA - UNICEUMA, 65065-470 São Luís, MA, Brazil.
None:
This work reports the fabrication of a novel electrochemical sensor leveraging reduced graphene oxide (rGO) modified with samarium oxide (Sm2O3) nanoparticles to enhance dopamine (DA) detection. The primary goal was to create a sensitive and selective platform capable of distinguishing DA in complex biological environments. The sensor was synthesized using a hydrothermal method to form rGO/Sm2O3 composites, followed by characterization employing scanning electron microscopy (SEM), X-ray diffraction (XRD), transmission electron microscopy (TEM), and high-resolution TEM (HR-TEM) and Raman spectroscopy to confirm morphological and structural integrity. Electrochemical assessments were conducted via cyclic voltammetry and square wave voltammetry, with the latter exhibiting an optimal response characterized by a linear range from 0.5 to 20.0 μmol L-1 and a limit of detection (LOD) of 0.030 μmol L-1. Comparative analyses highlighted the sensor's enhanced performance over conventional materials, with a 10-fold improvement in electron transfer rate, resulting from the higher electroactive area and the inherent functional properties of Sm2O3. The high selectivity was confirmed by testing against common interfering substances, and the sensor demonstrated reliable DA detection in synthetic human serum, achieving recovery rates between 95.27% and 99.39%. The findings suggested that the rGO/Sm2O3 sensor offers a robust, low-cost, and effective solution for DA detection with potential applications in clinical diagnostics and real-time monitoring of neurotransmitter levels in complex biological systems. This advancement underscores the relevance of integrating rare-earth oxides in sensors technology to address selectivity and sensitivity challenges in neurochemical analysis.
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