Novel paper-based potentiometric combined sensors using coumarin derivatives modified with vanadium pentoxide nanoparticles for the selective determination of trace levels of lead ions.
Saad S M HassanMahmoud Abdelwahab FathyPublished in: Mikrochimica acta (2024)
Novel miniaturized Pb(II) paper-based potentiometric sensors are described using coumarin derivatives I and II as electroactive ionophores and nano vanadium pentoxide as a solid contact material for the sensitive and selective monitoring of trace lead ions. Density functional theory (DFT) confirms optimum geometries, electronic properties, and charge transfer behaviors of 1:2 Pb(II): coumarin complexes. The sensors are prepared by using two strips of 20 × 5 mm filter paper with two circular orifices. One orifice is coated with vanadium pentoxide (V 2 O 5 ) nanoparticles in colloidal conductive carbon as a solid-contact, covered by a PVC membrane containing coumarin ionophore to act as a sensing probe. The other orifice is treated with Ag/AgCl in a polyvinyl butyral (PVB) film, to act as a reference electrode. Sensors with ionophores (I) and (II) exhibit Nernstian slopes of 27.7 ± 0.2 and 30.2 ± 0.2 mV/decade over the linear concentration range 4.5 × 10 -7 to 6.2 × 10 -3 M and 8.5 × 10 -8 to 6.2 × 10 -3 M, with detection limits of 1.3 × 10 -7 M (26.9 ppb) and 2.1 × 10 -8 M (4.4 ppb), respectively. The sensors are satisfactorily used for accurate determination of lead ions in drinking water, lead-acid battery wastewater, and electronic waste leachates. The results compare favourably well with data obtained by flameless atomic absorption spectrometry.
Keyphrases
- density functional theory
- heavy metals
- drinking water
- low cost
- quantum dots
- fluorescent probe
- aqueous solution
- living cells
- health risk
- molecular dynamics
- solid phase extraction
- risk assessment
- molecularly imprinted
- molecular docking
- reduced graphene oxide
- water soluble
- deep learning
- real time pcr
- loop mediated isothermal amplification
- gas chromatography
- neural network
- electron microscopy