Electroanalysis最新文献

This study reports the application of a solid bismuth microelectrode array for the determination of cobalt(II) ions by adsorptive stripping voltammetry (AdSV). The electrochemical properties of the proposed sensor were evaluated, highlighting its eco-friendly nature through the use of nontoxic electrode material. A significant advantage of this procedure is that it requires no surface modification of the working electrode. After optimization of the experimental parameters, including pH of supporting electrolyte, activation conditions, and accumulation potential and time, the sensor exhibited a linear response for Co(II) concentrations ranging from 5 × 10⁻¹⁰ to 1 × 10⁻⁷ mol L⁻¹ (with an accumulation time of 120 s). The limit of detection was equal to 2.2 × 10⁻¹⁰ mol L⁻¹. The repeatability, expressed as relative standard deviation, was 4.7% (n = 5) for a 2 × 10⁻⁸ mol L⁻¹ of Co(II). The developed procedure was successfully validated using certified reference materials and recovery studies in environmental water samples, confirming its suitability for practical analytical applications.

This study reports the application of a solid bismuth microelectrode array for the determination of cobalt(II) ions by adsorptive stripping voltammetry (AdSV). The electrochemical properties of the proposed sensor were evaluated, highlighting its eco-friendly nature through the use of nontoxic electrode material. A significant advantage of this procedure is that it requires no surface modification of the working electrode. After optimization of the experimental parameters, including pH of supporting electrolyte, activation conditions, and accumulation potential and time, the sensor exhibited a linear response for Co(II) concentrations ranging from 5 × 10⁻¹⁰ to 1 × 10⁻⁷ mol L⁻¹ (with an accumulation time of 120 s). The limit of detection was equal to 2.2 × 10⁻¹⁰ mol L⁻¹. The repeatability, expressed as relative standard deviation, was 4.7% (n = 5) for a 2 × 10⁻⁸ mol L⁻¹ of Co(II). The developed procedure was successfully validated using certified reference materials and recovery studies in environmental water samples, confirming its suitability for practical analytical applications.

To achieve high-precision and high-sensitivity detection of Pb²⁺ in random environments, a novel dual working electrode adaptive compensation and dual signal amplification sensor has been proposed. In a randomly fluctuating environment, one working electrode was modified with the target recognition element and thus generates both signal and noise, whereas the other electrode lacks the target modification and responds only to background noise. Two electrode signals were subtracted to eliminate background noise and achieve adaptive compensation. The imprinted sensor was prepared using chitosan as the functional monomer, followed by immobilization of specific DNA enzymes (DNAzyme) on its surface to construct a DNAzyme-imprinted dual-signal amplification sensor. The target Pb²⁺ interacted with the imprinting site and DNAzyme respectively, generating a dual signal amplification effect. The feasibility and adaptive compensation performance of the DNAzyme-imprinted sensor were analyzed, and the elementary reaction steps of the electrochemical process were investigated through kinetic analysis. The results indicate that the proposed method has a detection range of 10–80 nmol/L and a detection limit (LOD) of 5.52 nmol/L (3σ/slope). Within the temperature range of 20–36 °C, the detection error significantly decreased to 7.03%. The detection error significantly decreased to 6.21% within the pH range of 6.65–7.28, confirming the high sensitivity and adaptive compensation capability of this method. It has a high recovery rate in real water experiments, providing a high-precision and highly sensitive new method for detecting heavy metal ions in random water environments.

To achieve high-precision and high-sensitivity detection of Pb²⁺ in random environments, a novel dual working electrode adaptive compensation and dual signal amplification sensor has been proposed. In a randomly fluctuating environment, one working electrode was modified with the target recognition element and thus generates both signal and noise, whereas the other electrode lacks the target modification and responds only to background noise. Two electrode signals were subtracted to eliminate background noise and achieve adaptive compensation. The imprinted sensor was prepared using chitosan as the functional monomer, followed by immobilization of specific DNA enzymes (DNAzyme) on its surface to construct a DNAzyme-imprinted dual-signal amplification sensor. The target Pb²⁺ interacted with the imprinting site and DNAzyme respectively, generating a dual signal amplification effect. The feasibility and adaptive compensation performance of the DNAzyme-imprinted sensor were analyzed, and the elementary reaction steps of the electrochemical process were investigated through kinetic analysis. The results indicate that the proposed method has a detection range of 10–80 nmol/L and a detection limit (LOD) of 5.52 nmol/L (3σ/slope). Within the temperature range of 20–36 °C, the detection error significantly decreased to 7.03%. The detection error significantly decreased to 6.21% within the pH range of 6.65–7.28, confirming the high sensitivity and adaptive compensation capability of this method. It has a high recovery rate in real water experiments, providing a high-precision and highly sensitive new method for detecting heavy metal ions in random water environments.

Ions are ubiquitously present in all research fields, having an impact on living organisms. As such, the development of ion sensors is crucial in multiple fields, including diagnosis, agriculture, and water quality analysis. However, the long-term stability of ion-selective electrodes is limited by the poor reliability of conventional polymer-based capacitive interlayers, which are prone to oxidation, water uptake, and high electrochemical noise. To address this challenge, we present the first systematic study of six carbon allotropes, graphene flakes, graphite, single- and multi-walled carbon nanotubes, graphitised mesoporous carbon, and carbon black, as ion-to-electron transducers in PVC-based potassium-selective electrodes. By correlating morphology, crystallinity, and impedance characteristics with electrochemical outcomes, graphene was identified as the optimal interlayer, achieving ultra-low noise (27 µV h⁻¹) and minimal drift (105 µV h⁻¹), while single-walled carbon nanotubes exhibited record-low noise (11.6 µV h⁻¹) but reduced stability. The origins of these differences were investigated in terms of charge–transfer resistance, capacitance, and interfacial morphology. Density functional theory simulations were performed, demonstrating a strong correlation with these experimental observations. Furthermore, we demonstrated that non-equilibrium methodologies such as pulse-amperometry and pulse-voltammetry significantly enhance sensitivity beyond the Nernstian limit, with values up to 132 mV decade⁻¹, compared to 84 ± 17 mV decade⁻¹ for graphene flakes under standard potentiometry. Finally, we introduced a cost-effective and eco-friendly aerosol-assisted deposition method to fabricate interlayer/sensing PVC ionophore films with controlled microstructure, composition, and thickness. These results establish a clear structure–property–performance framework for carbon-based interlayers and highlight graphene flakes as a practical route toward developing stable, miniaturised, and high-sensitivity potassium ion sensors for biomedical, environmental, and wearable applications.

This study presents a voltammetric electronic tongue for the discrimination of fine particulate matter (PM 2.5) collected at three distinct urban locations in Rio de Janeiro, Brazil. A Screen-Printed Electrode (SPE) was developed using a low-cost handmade ink (optimized at 20% w/w glass varnish, 40% w/w graphite, and 40% w/w solvent, with PET bottles used as the substrate). The electrode was characterized by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), scanning electron microscopy (SEM), and Raman spectroscopy. Following acid digestion, PM samples collected from the Rio de Janeiro Botanical Garden (RJBG), the Rebouças Tunnel (RT), and the Institute of Chemistry at UFRJ were analyzed by square wave voltammetry (SWV). Exploratory analysis using principal component analysis (PCA) and hierarchical cluster analysis (HCA) demonstrated that raw voltammetric data provided significantly superior sample separation compared to normalized data. Temporal evaluation revealed that seasonal factors and dry weather conditions influenced the grouping behavior, causing partial overlap between RJBG and RT samples. Finally, an artificial neural network (ANN) classification model constructed using raw data achieved a classification accuracy of 75% in the independent test set, classifying samples according to their sampling-site labels, although temporal and seasonal factors may also have contributed to the observed differences.

Ions are ubiquitously present in all research fields, having an impact on living organisms. As such, the development of ion sensors is crucial in multiple fields, including diagnosis, agriculture, and water quality analysis. However, the long-term stability of ion-selective electrodes is limited by the poor reliability of conventional polymer-based capacitive interlayers, which are prone to oxidation, water uptake, and high electrochemical noise. To address this challenge, we present the first systematic study of six carbon allotropes, graphene flakes, graphite, single- and multi-walled carbon nanotubes, graphitised mesoporous carbon, and carbon black, as ion-to-electron transducers in PVC-based potassium-selective electrodes. By correlating morphology, crystallinity, and impedance characteristics with electrochemical outcomes, graphene was identified as the optimal interlayer, achieving ultra-low noise (27 µV h⁻¹) and minimal drift (105 µV h⁻¹), while single-walled carbon nanotubes exhibited record-low noise (11.6 µV h⁻¹) but reduced stability. The origins of these differences were investigated in terms of charge–transfer resistance, capacitance, and interfacial morphology. Density functional theory simulations were performed, demonstrating a strong correlation with these experimental observations. Furthermore, we demonstrated that non-equilibrium methodologies such as pulse-amperometry and pulse-voltammetry significantly enhance sensitivity beyond the Nernstian limit, with values up to 132 mV decade⁻¹, compared to 84 ± 17 mV decade⁻¹ for graphene flakes under standard potentiometry. Finally, we introduced a cost-effective and eco-friendly aerosol-assisted deposition method to fabricate interlayer/sensing PVC ionophore films with controlled microstructure, composition, and thickness. These results establish a clear structure–property–performance framework for carbon-based interlayers and highlight graphene flakes as a practical route toward developing stable, miniaturised, and high-sensitivity potassium ion sensors for biomedical, environmental, and wearable applications.

This study presents a voltammetric electronic tongue for the discrimination of fine particulate matter (PM 2.5) collected at three distinct urban locations in Rio de Janeiro, Brazil. A Screen-Printed Electrode (SPE) was developed using a low-cost handmade ink (optimized at 20% w/w glass varnish, 40% w/w graphite, and 40% w/w solvent, with PET bottles used as the substrate). The electrode was characterized by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), scanning electron microscopy (SEM), and Raman spectroscopy. Following acid digestion, PM samples collected from the Rio de Janeiro Botanical Garden (RJBG), the Rebouças Tunnel (RT), and the Institute of Chemistry at UFRJ were analyzed by square wave voltammetry (SWV). Exploratory analysis using principal component analysis (PCA) and hierarchical cluster analysis (HCA) demonstrated that raw voltammetric data provided significantly superior sample separation compared to normalized data. Temporal evaluation revealed that seasonal factors and dry weather conditions influenced the grouping behavior, causing partial overlap between RJBG and RT samples. Finally, an artificial neural network (ANN) classification model constructed using raw data achieved a classification accuracy of 75% in the independent test set, classifying samples according to their sampling-site labels, although temporal and seasonal factors may also have contributed to the observed differences.

Phenylalanine (Phe) enantiomers participate differently in biological metabolism, making their enantioselective recognition important for understanding chiral amino-acid interactions and developing enantioselective analytical interfaces. However, low-cost and environmentally benign chiral electrochemical interfaces remain difficult to construct because many natural chiral selectors have poor conductivity and limited exposure of effective recognition sites. Here, we report a dual-starch/graphene oxide chiral electrochemical recognition platform for Phe enantiomers. A composite polysaccharide (CS/SPS) was prepared from corn starch (CS) and sweet potato starch (SPS), and graphene oxide (GO) was introduced as an electroactive substrate to construct CS/SPS/GO/glassy carbon electrode (GCE). Compared with either single-starch layer, the dual-starch assembly provides a better-dispersed polysaccharide microenvironment with more accessible hydrogen-bonding and stereochemical recognition sites, while GO enhances interfacial electron transfer. The CS/SPS/GO/GCE interface produced a markedly stronger differential pulse voltammetry response toward L-Phe than toward D-Phe. Under optimized conditions (pH 6.0, 20 °C, 20 s incubation, and 5 mM Phe), the peak current ratio of L-Phe to D-Phe reached 3.47, exceeding those obtained with single-polysaccharide-modified electrodes. The interface showed good selectivity over representative interfering molecules, tolerance toward K⁺ and Na⁺, and storage stability, retaining 98.7% of its initial response after 16 days. Ultraviolet–visible (UV–vis) analysis gave higher apparent binding affinity for L-Phe than for D-Phe based on the mass concentration of CS/SPS (K_L = 0.3095 mL mg⁻¹ and K_D = 0.1516 mL mg⁻¹), and DFT calculations supported a more favorable L-Phe–associated complex under the same simplified host model. This work provides a simple strategy for constructing biomass-derived polysaccharide/graphene chiral interfaces for amino-acid enantioselective electrochemical recognition.

Phenylalanine (Phe) enantiomers participate differently in biological metabolism, making their enantioselective recognition important for understanding chiral amino-acid interactions and developing enantioselective analytical interfaces. However, low-cost and environmentally benign chiral electrochemical interfaces remain difficult to construct because many natural chiral selectors have poor conductivity and limited exposure of effective recognition sites. Here, we report a dual-starch/graphene oxide chiral electrochemical recognition platform for Phe enantiomers. A composite polysaccharide (CS/SPS) was prepared from corn starch (CS) and sweet potato starch (SPS), and graphene oxide (GO) was introduced as an electroactive substrate to construct CS/SPS/GO/glassy carbon electrode (GCE). Compared with either single-starch layer, the dual-starch assembly provides a better-dispersed polysaccharide microenvironment with more accessible hydrogen-bonding and stereochemical recognition sites, while GO enhances interfacial electron transfer. The CS/SPS/GO/GCE interface produced a markedly stronger differential pulse voltammetry response toward L-Phe than toward D-Phe. Under optimized conditions (pH 6.0, 20 °C, 20 s incubation, and 5 mM Phe), the peak current ratio of L-Phe to D-Phe reached 3.47, exceeding those obtained with single-polysaccharide-modified electrodes. The interface showed good selectivity over representative interfering molecules, tolerance toward K⁺ and Na⁺, and storage stability, retaining 98.7% of its initial response after 16 days. Ultraviolet–visible (UV–vis) analysis gave higher apparent binding affinity for L-Phe than for D-Phe based on the mass concentration of CS/SPS (K_L = 0.3095 mL mg⁻¹ and K_D = 0.1516 mL mg⁻¹), and DFT calculations supported a more favorable L-Phe–associated complex under the same simplified host model. This work provides a simple strategy for constructing biomass-derived polysaccharide/graphene chiral interfaces for amino-acid enantioselective electrochemical recognition.