2 research outputs found
In-Vial Temperature Gradient Headspace Single Drop Microextraction Designed by Multiphysics Simulation
Presented herein
is a novel headspace single drop microextraction
(HS-SDME) based on temperature gradient (TG) for an on-site preconcentration
technique of volatile and semivolatile samples. First, an inner vial
cap was designed as a cooling device for acceptor droplet in HS-SDME
unit to achieve fast and efficient microextraction. Second, for the
first time, an in-vial TG was generated between the donor phase in
a sample vial at 80 °C and the acceptor droplet under the inner
vial cap containing cooling liquid at −20 °C for a TG-HS-SDME.
Third, a simple mathematic model and numerical simulations were developed
by using heat transfer in fluids, Navier–Stokes and mass balance
equations for conditional optimization, and dynamic illumination of
the proposed extraction based on COMSOL Multiphysics. Five chlorophenols
(CPs) were selected as model analytes to authenticate the proposed
method. The comparisons revealed that the simulative results were
in good agreement with the quantitative experiments, verifying the
design of TG-HS-SDME via the numerical simulation. Under the optimum
conditions, the extraction enrichments were improved from 302- to
388-fold within 2 min only, providing 3.5 to 4 times higher enrichment
factors as compared to a typical HS-SDME. The simulation indicated
that these improvements in the extraction kinetics could be attributed
due to the applied temperature gap between the sample matrix and acceptor
droplet within the small volume of headspace. Additionally, the experiments
demonstrated a good linearity (0.03–100 μg/L, <i>R</i><sup>2</sup> > 0.9986), low limit of detection (7–10
ng/L), and fair repeatability (<5.9% RSD, <i>n</i> =
6). All of the simulative and experimental results indicated the robustness,
precision, and usefulness of TG-HS-SDME for trace analyses of analytes
in a wide variety of environmental, pharmaceutical, food safety, and
forensic samples
Summary of LF morbidity prevalence, socio-economic and environmental factors by division.
Summary of LF morbidity prevalence, socio-economic and environmental factors by division.</p