Spectrophotometric Detection of Nickel in Water by Lab-on-a-chip Technology: Application to Electroplating
Mossotti, Giulia
Catania, Felice
Perrucci, Francesco
Scaltrito, Luciano
Periolatto, Monica
Ferrero, Sergio
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How to Cite

Mossotti G., Catania F., Perrucci F., Scaltrito L., Periolatto M., Ferrero S., 2023, Spectrophotometric Detection of Nickel in Water by Lab-on-a-chip Technology: Application to Electroplating, Chemical Engineering Transactions, 99, 127-132.
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Abstract

Nickel is a metal member of the transition series in the periodic table, and as such shows outstanding properties interesting to the world of industry, namely corrosion resistance to air, water and alkali and electrical conductivity. In fact, nickel is widely employed in electroplating, where high analyte concentrations, up to 100g/L, are required to achieve excellent final results. The process monitoring is required not only to ensure constant and adequate metal-finishing concentration but also to guarantee the safety of wastewater products. To detect nickel, either in high and low metal concentration, a colorimetric method was selected. The spectrophotometric study reveals a well-defined absorption peak at 396nm, giving a calibration curve with remarkable linearity toward metal concentrations, ranging from 1 to 22g/L. By proper optimization process, the detection field can be simply enlarged at least from 100 g/L (100000ppm) to 3*10-3 g/L (3ppm). Due to the presence of an acid part in the electroplating bath, the behaviour of the metal in an acid solution has also been investigated, and the calibration curve still depicts a good linearity of the system.
Achieved results pointed out the suggested colorimetric method as a promising candidate for addressing the requirement for capillary and regular monitoring of nickel in water, throughout a wide range of concentrations. The laboratory method may be readily improved and adapted for microfluidic technology by lowering sample and reagent amounts, miniaturizing sensors, and automating the entire process, from sampling to data recovery.
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