Herein, Tecoma stans (TS) flower extract was used as an efficient green reducing agent for graphene oxide (GO) to produce reduced graphene oxide (rGO) for the first time. The organic heterocyclic benzotriazole (BTA) was incorporated onto the rGO surface through a nucleophilic substitution reaction to produce covalently bonded BTA-rGO. The prepared materials were analyzed by UV-visible spectroscopy, powder Xray diffraction measurements (XRD), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, and Scanning Electron Microscopy (SEM). A screen-printed carbon electrode (SPCE) was modified with BTA-rGO. The fabricated electrode was electrochemically analyzed by using K 3 [Fe (CN) 6 ] as a redox probe. To evaluate the sensing ability of BTA-rGO/SPCE electrode towards arsenic ions using differential pulse voltammetry (DPV) and amperometry techniques. The BTA functional was play the major role in significant improving the conductivity and sensitivity of the designed electrode. The BTA-rGO/SPCE modified electrode demonstrates voltammetric determination of As 3 + ions with a limit of detection, high sensitivity, and linear range values of 2.89 nM, 1.8 μA nM À 1 , and 2-40 nM, respectively. Furthermore, all of these impressive results indicate that BTA-rGO can be used as an electrodematerial with capability for electrochemical arsenic sensors. The fabricated sensors showed repeatability and reproducibility in this study.
4-Nitrophenol (4-NP) is a hazardous organic pollutant with detrimental effects on plants, animals, and humans. Detection of 4-NP in the environment is therefore a necessary requirement. We demonstrate a facile green synthesis of nickel-oxide (NiO) nanoparticles employing Brassica oleracea vegetable extract (cauliflower) as a green stabilizing and reducing agent. Green synthesized NiO nanoparticles were used as an efficient electrode material for the highly sensitive electrochemical detection of 4-NP. The abundant polyphenolic component in the vegetable extract of Brassica oleracea is capable of reducing and stabilizing C 2 NiO 4 into NiO nanoparticles. The as-synthesized NiO nanoparticles were characterized by UV-Vis spectroscopy, FTIR spectroscopy, Raman spectroscopy, photolumines-cence spectroscopy, and X-ray photoelectron spectroscopy (XPS), and the structural phase of NiO nanoparticles was confirmed using powder X-ray diffraction technique. The surface morphology of the NiO nanoparticles was analyzed using scanning electron microscopy (SEM). Linear sweep voltammetry (LSV) and Differential pulse voltammetry (DPV) techniques were adopted to for the electrochemical determination of 4-NP after drop casting the NiO nanoparticles onto the screen-printed carbon electrode (SPCE). The developed sensor (NiO/SPCE) showed a high sensitivity of 1.055 μA/nM over a wide linearrange from 1 to 10 nM with a detection limit of 0.519 nM for the detection of 4-NP using DPV technique.
In human blood serum, the concentration of magnesium ions typically ranges from 0.7 mM to 1.05 mM. However, exceeding the upper limit of 1.05 mM can lead to the condition known as hypermagnesemia. In this regard, a highly sensitive and selective electrochemical sensor for Mg(II) ion detection was successfully fabricated by immobilizing cerium oxide (CeO2) microcuboids, synthesized via microwave radiation method, onto the surface of glassy carbon electrode (GCE). Cyclic voltammetry studies revealed the exceptional electrocatalytic effect of CeO2 microcuboid-modified GC electrode, particularly in relation to the irreversible reduction signal of Mg(II). The microcuboid-like structure of CeO2 microparticles facilitated enhanced adsorption of Mg(II) ion (Γ=2.17×10−7mol cm−2) and electron transfer (ks=8.94 s−1) between the adsorbed Mg(II) ions and GCE. A comprehensive analysis comparing the performance characteristics of amperometry, differential pulse voltammetry, cyclic voltammetry, and square wave voltammetry was conducted. The square wave voltammetry-based Mg(II) sensor exhibited remarkable sensitivity of 2.856 μA mM−1, encompassing a broad linear detection range of 0–3 mM. The detection and quantification limits were impressively low, with values of 19.84 and 66.06 μM, respectively. Remarkably, the developed electrode showed a rapid response time of less than 140 s. Multiple linear regression and partial least squares regression models were employed to establish a mathematical relationship between magnesium ion levels and electrochemical parameters. Notably, the proposed sensor exhibited excellent anti-interferent ability, repeatability, stability, and reproducibility, enabling the fabricated electrode to be used effectively for Mg(II) ion sensing in real-world samples.
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