article · Scientific Reports
Abstract Lately, children's daily consumption of some products, such as cereals and candies, has been rising, which provides a compelling rationale for determining any metallic substances that may be present. Monitoring the concentration of certain metals, like nickel, in these products is necessary due to medical issues in humans when consumed regularly. So, in this work, a novel and highly selective carbon paste as a Ni(II) ion-selective sensor was prepared and investigated using ceramic magnesium aluminum spinel nanoparticles as the ionophore and tritolyl phosphate (TOCP) as a plasticizer. A modified co-precipitation method was used to synthesize the spinel nanoparticles. X-ray diffraction, scanning electron microscope with EDAX, transmission electron microscope, and BET surface area were used to determine the phase composition, microstructure, pores size, particle size, and surface area of the synthesized nanoparticles. The spinel nanoparticle was found to have a nano crystallite size with a cubic crystal system, a particle size ranging from 17.2 to 51.52 nm, mesoporous nature (average pore size = 8.72 nm), and a large surface area (61.75 m 2 /g). The composition ratio of graphite carbon as a base: TOCP as binder: spinal as ionophore was 67.3:30.0:2.7 (wt%) based on potentiometric detections over concentrations from 5.0 × 10 −8 to 1.0 × 10 −2 mol L −1 with LOD of 5.0 × 10 −8 mol L −1 . A measurement of 29.22 ± 0.12 mV decade −1 over pH 2.0–7.0 was made for the Nernstian slope. This sensor demonstrated good repeatability over nine weeks and a rapid response of 8 s. A good selectivity was shown for Ni(II) ions across many interferents, tri-, di-, and monovalent cations. The Ni(II) content in spiked real samples, including cocaine, sweets, coca, chocolate, carbonated drinks, cereals, and packages, were measured. The results obtained indicated no significant difference between the proposed potentiometric method and the officially reported ICP method according to the F- and t-test data. In addition to utilizing ANOVA statistical analysis, validation procedures have been implemented, and the results exceed the ICP-MS methodology.
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DOI: 10.1038/s41598-024-64052-1
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