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Simultaneous determination and extraction of ultra- trace amounts of estradiol valerate from whole blood using FFT square wave voltammetry and low-voltage electrically enhanced microextraction techniques

Ultra-trace detection of estradiol valerate (EV) in whole blood samples was done by coupling Fast Fourier transform square wave voltammetry (FFTSWV) and electromembrane extraction (EME). For the first time, a novel carbon paste electrode (CPE) modified with Terbium carbonate (Tb2(CO3)3) nanoparticle...

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Published in:Journal of electroanalytical chemistry (Lausanne, Switzerland) Switzerland), 2018-03, Vol.813, p.83-91
Main Authors: Mofidi, Zahra, Norouzi, Parviz, Larijani, Bagher, Seidi, Shahram, Ganjali, Mohammad Reza, Morshedi, Mahboobe
Format: Article
Language:English
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Summary:Ultra-trace detection of estradiol valerate (EV) in whole blood samples was done by coupling Fast Fourier transform square wave voltammetry (FFTSWV) and electromembrane extraction (EME). For the first time, a novel carbon paste electrode (CPE) modified with Terbium carbonate (Tb2(CO3)3) nanoparticles was used for FFTSWV determination of EV. The important parameters in electro membrane extraction recovery of EV, containing extraction time, electrical potential and pH of donor phases, were optimized by Central composite design and response surface methodology. By applying a low voltage of 7 V during 20 min of extraction, EV was migrated from the sample solution (pH 4), into a thin layer of 1-octanol in the pores of a porous flat sheet membrane and then into the acceptor solution (pH 5). Under the optimal conditions, EV was effectively extracted from the whole blood sample with recovery percentage of 67%.The method showed two wide linear ranges 0.1–1300 and 1300–10,000 ng/mL with determination coefficients of 0.995 and 0.991, respectively. Limits of detection and quantification of 0.01 ng/mL and 0.1 ng/mL were acquired, respectively. The intra- and inter-day precisions (RSD%, n = 3) were
ISSN:1572-6657
1873-2569
DOI:10.1016/j.jelechem.2018.01.048