A Novel Cloud Point Extraction Method Using a Benzimidazole-Based Ligand for the Preconcentration of Toxic Heavy Metals in Water and Food Samples

Abstract

In the present research, a novel cloud point extraction (CPE) method was developed for the separation and preconcentration of toxic Cu(II), Ni(II), Pb(II), and Cd(II) ions in environmental water and vegetable samples, prior to their determination by flame atomic absorption spectrometry (FAAS). The ligand 2-(2-(4-fluorobenzyl)-1H-benzo[d]imidazol-1-yl)acetohydrazide (FB-BIAH) was employed for the first time as an analytical complexing agent for the aforementioned metal ions, and Triton X-114 (TX-114) was preferred as the nonionic surfactant. Within the scope of optimizing CPE conditions, experimental parameters such as pH, FB-BIAH and surfactant amount, incubation temperature and time, as well as centrifuge speed and duration were systematically investigated. The optimal conditions for the simultaneous quantitative recovery of analyte ions were established as pH 7.0, FB-BIAH amount 2.5 mg, TX-114 quantity 25 mg, incubation temperature 60°C, and incubation time 30 min. Under optimal conditions, the proposed method was successfully applied to river water and seawater, as well as different vegetable samples such as lettuce, parsley, and pepper. The results obtained demonstrated that the analyte ions could be reliably determined in complex matrices and that the method exhibited high analytical performance. Due to its simplicity, rapid applicability, environmentally friendly nature, and cost-effectiveness, the proposed CPE–FAAS method represents a promising approach for the routine analysis of toxic heavy metals in environmental water and food samples.

Article information

Article type
Paper
Submitted
08 Jan 2026
Accepted
20 Jan 2026
First published
20 Jan 2026

Anal. Methods, 2026, Accepted Manuscript

A Novel Cloud Point Extraction Method Using a Benzimidazole-Based Ligand for the Preconcentration of Toxic Heavy Metals in Water and Food Samples

O. Ozdemir, C. Duran, E. Menteşe and D. Ozdes, Anal. Methods, 2026, Accepted Manuscript , DOI: 10.1039/D6AY00036C

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