Smartphone-interfaced flow injection amperometric system for enzyme-free glucose detection using a palladium-PANI/carbon microsphere@carbon nanotubes modified electrode

Kaewjangwad, Chanakarn; Somsiri, Sunita; Wangchuk, Sangay; Saichanapan, Jenjira; Saisahas, Kasrin; Samoson, Kritsada; Soleh, Asamee; Promsuwan, Kiattisak; Limbut, Warakorn

doi:10.1016/j.electacta.2024.144292

Electrochimica Acta

2024

DOI: 10.1016/j.electacta.2024.144292

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Smartphone-interfaced flow injection amperometric system for enzyme-free glucose detection using a palladium-PANI/carbon microsphere@carbon nanotubes modified electrode

Chanakarn Kaewjangwad,

Sunita Somsiri,

Sangay Wangchuk

et al.

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Cited by 4 publications

References 34 publications

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Promoted Non-enzymatic Glucose Sensor Based on Synergistic Effect of Hydrothermal Synthesized Ni(OH)2-Graphene Nanocomposite

Cai,

Cui,

Zhang

et al. 2024

Chem. Res. Chin. Univ.

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Promoted Non-enzymatic Glucose Sensor Based on Synergistic Effect of Hydrothermal Synthesized Ni(OH)2-Graphene Nanocomposite

Cai,

Cui,

Zhang

et al. 2024

Chem. Res. Chin. Univ.

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Tuning N-heterocyclic carbene wingtips to form electrochemically stable adlayers on metals

Jensen,

Clark,

Kirby

et al. 2024

Mater. Adv.

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Impact of Nitro Substituents on Dopamine Sensing and Nanostructure Morphology: A Machine Learning Approach for PANI:2- and 3-Nitro-1H-Pyrrole Nanocomposite Sensors

Gürsu,

Yıldız,

Taşaltın

et al. 2024

J. Electrochem. Soc.

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In this study, we explore the effects of nitro substituents on the morphology and dopamine (DOP) sensing performance of polyaniline (PANI) nanocomposites (NCs). The novelty of the study is the unique integration of 2-nitro-1H-pyrrole (D9A) and 3-nitro-1H-pyrrole (D9B) into PANI to develop advanced non-enzymatic voltammetric sensors, combined with machine learning for DOP sensitivity and morphology analysis. Structural and morphological insights were obtained through comprehensive characterization techniques including ¹H NMR, ¹³C NMR, Fourier transform infrared spectroscopy, scanning electron microscopy, and artificial intelligence-enhanced SEM analysis. The PANI: D9B NCs sensor demonstrated superior DOP detection in the range of 0.625–5 µM, with exceptional sensitivity (329.72 µAµM⁻¹ cm⁻²) and an ultra-low limit of detection of 0.078 µM. Its rapid sensing capability within 1 minute indicates potential for use in biomedical diagnostics. In contrast, the PANI NCs sensor exhibited lower sensitivity, which was linked to higher Zreel values and space charge effects. To further enhance DOP prediction accuracy, we employed machine learning (ML) models—ANN, SVM, XGBoost, and Linear Regression—to analyze sensor outputs, with a focus on feature extraction and multivariate data analysis. Our combined approach provides a robust framework for optimizing nitro-substituted PANI NCs for high-performance sensing applications.

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Smartphone-interfaced flow injection amperometric system for enzyme-free glucose detection using a palladium-PANI/carbon microsphere@carbon nanotubes modified electrode

Cited by 4 publications

References 34 publications

Promoted Non-enzymatic Glucose Sensor Based on Synergistic Effect of Hydrothermal Synthesized Ni(OH)2-Graphene Nanocomposite

Promoted Non-enzymatic Glucose Sensor Based on Synergistic Effect of Hydrothermal Synthesized Ni(OH)2-Graphene Nanocomposite

Tuning N-heterocyclic carbene wingtips to form electrochemically stable adlayers on metals

Impact of Nitro Substituents on Dopamine Sensing and Nanostructure Morphology: A Machine Learning Approach for PANI:2- and 3-Nitro-1H-Pyrrole Nanocomposite Sensors

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