Health, Medicine

Online coupling of fully automatic in-syringe dispersive liquid-liquid microextraction with oxidative back-extraction to inductively coupled plasma spectrometry for sample clean-up in elemental analysis: A proof of concept

Publication date: 1 October 2017
Source:Talanta, Volume 173
Author(s): Burkhard Horstkotte, Kateřina Fikarová, David J. Cocovi-Solberg, Hana Sklenářová, Petr Solich, Manuel Miró
A proof of concept of a novel automatic sample cleanup approach for metal assays in troublesome matrixes as a front-end sample pre-treatment to inductively coupled plasma optical emission spectroscopy – ICP-OES – is herein presented. Target metals, namely, copper, lead, and cadmium were complexed in-system quantitatively using ammonium pyrrolidine dithiocarbamate (APDC) and transferred into a minute volume of toluene as extractant employing lab-in-syringe magnetic stirring-assisted dispersive liquid-liquid microextraction (LIS-MSA-DLLME). After discharge of the sample, the analytes were back-extracted into nitric acid and injected on-line into ICP-OES. To promote and expedite this process in-syringe, advantage was taken from oxidative decomposition of the chelate by potassium iodate, reported in this article for the first time.Experimental conditions for LIS-MSA-DLLME were optimized by Box-Benkhen multivariate analysis using the geometric mean of analyte recoveries as the desirability function. Times of extraction and back-extraction of 300s and 100s, respectively, pH 5.5 at 30mmol/L acetate, 300µL of extraction solvent, and 600µmol/L of APDC were finally applied. Online interfacing to ICP-OES for back-extract analysis yielded average repeatabilities for Cd, Cu, and Pb of 2.9%, 3.5%, and 3.5% with limits of detections (3s) of 1.9, 1.4, and 5.6ng/mL, respectively. Oxidative back-extraction was proven reliable for the determination of metal species in coastal seawater, surrogate digestive fluids and soil leachates with recovery values for Cd, Cu, and Pb ranging from 90% to 118%, 68% to 104%, and 86% to 112%, respectively.

Graphical abstract



Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s