A non-enzymatic electrochemical method was developed for glucose detection using a glassy carbon electrode modified with platinum nanoflowers supported on graphene oxide (PtNFs-GO). PtNFs-GO was synthesized using a nontoxic, rapid, one-pot and template-free method. Low-cost, green solvent ethanol acted as the reductant, and the advanced and effective 2D carbon material-GO nanosheet acted as the stabilizing material. Their morphologies were characterized using transmission electron microscopy. Cyclic voltammetry and amperometric methods were used to evaluate the electrocatalytic activity towards glucose in neutral media. The modified electrode exhibited strong and sensitive amperometric responses to glucose even in the presence of a high concentration of chloride ions. The response time was within 5s. The interference effects from ascorbic acid and uric acid were comparatively small when operated at suitable potential. Under optimal detection potential (0.47 V with a saturated calomel reference electrode) the PtNFs-GO modified electrode performed a current response towards glucose at a broad concentration range from 2 μM to 20.3mM. Two linear regions could be observed at 2 μM to 10.3mM with a sensitivity of 1.26 μA mM(-1)cm(-2) (correlation coefficient 0.9968), and at 10.3mM to 20.3mM with a sensitivity of 0.64 μA mM(-1)cm(-2)(correlation coefficient 0.9969). The LOD of 2 μM was lower than many non-enzymatic electrochemical glucose sensors. The modified electrode was also applied to the determination of glucose in glucose injection solutions, and the satisfactory results obtained indicated that it was promising for the development of a novel non-enzymatic electrochemical glucose sensor.
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http://dx.doi.org/10.1016/j.talanta.2012.10.066 | DOI Listing |
Sci Rep
January 2025
Department of Chemistry, Amrita School of Physical Sciences Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India.
Nanomaterials (Basel)
December 2024
Guangdong Provincial Key Laboratory of Electronic Functional Materials and Devices, Huizhou University, Huizhou 516001, China.
Non-enzymatic glucose detection is an effective strategy to control the blood glucose level of diabetic patients. A novel hierarchical core-shell structure of nickel hydroxide shell coated copper hydroxide core based on copper foam (Ni(OH)@Cu(OH)-CF) was fabricated and derived from NiO@CuO-CF for glucose sensing. Cyclic voltammetry and amperometry experiments have demonstrated the efficient electrochemical catalysis of glucose under alkaline conditions.
View Article and Find Full Text PDFAnal Chim Acta
January 2025
Hubei Provincial Key Laboratory of Green Materials for Light Industry, School of Materials and Chemical Engineering, Hubei University of Technology, Wuhan, 430068, PR China. Electronic address:
Background: Accurate monitoring glucose level is significant for human health management, especially in the prevention, diagnosis, and management of diabetes. Electrochemical quantification of glucose is a convenient and rapid detection method, and the crucial aspect in achieving great sensing performance lies in the selection and design of the electrode material. Among them, CuO, with highly catalysis ability, is commonly used as electrocatalyst in non-enzymatic glucose sensing.
View Article and Find Full Text PDFTalanta
December 2024
Key Laboratory of Consumer Product Quality Safety Inspection and Risk Assessment for State Market Regulation, Chinese Academy of Inspection and Quarantine, Beijing, China. Electronic address:
Accurate analysis of urinary creatinine levels is of great clinical significance. Non-enzymatic creatinine sensing systems (NECSs) have gained growing development because of higher stability and lower cost compared to enzymatic sensing systems. At present, there is a demand for simple approaches to develop NECSs with high sensitivity.
View Article and Find Full Text PDFTalanta
December 2024
NanoBiosensors and Biodevices Lab, School of Medical Science and Technology, Indian Institute of Technology Kharagpur, West Bengal, 721302, India. Electronic address:
This work presents a robust strategy for quantifying overlapping electrochemical signatures originating from complex mixtures and real human plasma samples using nickel-based electrochemical sensors and machine learning (ML). This strategy enables the detection of a panel of analytes without being limited by the selectivity of the transducer material and leaving accommodation of interference analysis to ML models. Here, we fabricated a non-enzymatic electrochemical sensor for L-lactic acid detection in complex mixtures and human plasma samples using nickel oxide (NiO) nanoparticle-modified glassy carbon electrodes (GCE).
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