Recovery
One of the inherent limitations with quantitative applications of FFF–ICP-MS can be low recoveries, which are attributed to
several factors. Probably the most significant problem area is the physical interaction of the analyte with the membrane by
an adsorption mechanism, resulting in the particles sticking to the membrane and not being eluted. In addition, losses through
the accumulation wall based on membrane cut-off values have been reported for samples containing dissolved and macromolecular
components (13). Analyte loss can also occur in the ICP-MS nebulizer, spray chamber and sample tubing, but these losses are
relatively small compared to membrane interactions.
 Figure 5: Comparison of recoveries of three silver nanoparticle sizes (10, 40 and 70 nm) at different concentrations (200,
150, 100 and 50 ppb), under various FFF field conditions. Adapted from reference 7.
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However, when the analytical conditions are favourable, good recoveries can be achieved as demonstrated by the silver nanoparticle
data shown in Figure 5. Recoveries of the three silver nanoparticle sizes tested (10 nm, 40 nm and 70 nm) at different concentrations
(200 ppb, 150 ppb, 100 ppb and 50 ppb) are illustrated in the coloured bar graph, which shows the integrated ICP-MS response
signal (peak area) for the FFF cross-flow field off (blue); bypassing the FFF system entirely (brown); and with the FFF cross-flow
field on (green). The inset graph shows the raw fractogram data for the different concentrations of the 10-nm particles, but
as can be seen by the coloured bar graphs for the 40-nm and 70-nm particles, the fractograms generated similar data. In fact,
the recoveries for the four concentrations of the three different particle sizes of silver in this study were all in the range
of 88–98%, based on integrated peak areas (7).
Detection Limits
 Figure 6: (a) The detection limit in FFF–ICP-MS studies is defined as a mass, where the mass-based detection limit (mDL) is
the product of the instrument detection limit and the peak width. Adapted from reference 14. (b) In a three-particle mixture,
the effect of polydispersity degrades the detection limit. Adapted from reference 15.
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Traditional ICP-MS analysis generally has instrumental detection limits in the range of 1–100 ng/L (parts per trillion), depending on the specific element and the abundance of the isotope measured. However, in FFF
applications, the mass of metal nanoparticles being detected is distributed over a size range that is diluted as the mass
is spread out over the effluent volume. Spreading is a function of sample polydispersity, nonideal membrane interactions and
band broadening. For this reason, the detection limit is more appropriately defined as a mass, where the mass-based detection
limit (mDL) is the product of the instrument detection limit and the peak width, as shown in Figure 6(a). This example shows
the uranium elution profile during the measurement of uranium bound to monodisperse hematite (Fe2O3) nanoparticles along with fractograms scaled down by factors of 2 and 10. If the area (mass) under the elution peak is compared
with the area (mass) defined by the mDL, it is clear that the 0.1 scale fractogram is roughly the same area as the mDL and,
as a result, the mass of uranium would be very difficult to accurately quantitate (14).
In particle mixtures the effect of polydispersity is even more dramatic. Figure 6(b) shows a fractogram of a mixture of three
sizes of silver nanoparticles (10, 40 and 70 nm) containing a total Ag concentration of 201 µg/L (67 µg/L each of the three
sizes of particles), together with serial dilutions of five-fold (purple peaks) and 10-fold (red peaks) of the mixture. Of
the diluted samples, clearly only the five-fold dilution sample (total 40.2 µg/L Ag) is far enough above the background to
allow it to be quantified with good accuracy and precision. With the 10-fold dilution sample, probably only the 40-nm particles
have generated a quantifiable peak, as the 6.7-µg/L (20.1 µg/L total) three-particle mixture results in a fractogram that
is only slightly above the background (15).
Conclusion
This overview of the capabilities of field-flow fractionation coupled with ICP-MS has demonstrated that this hyphenated technique
shows a great deal of promise to separate, detect and quantitate nanoparticles in environmental matrices. FFF is a mature
separation technique that has been used for more than 35 years and, when combined with detection techniques such as UV absorbance,
has proved to be very capable of separating low concentrations of polydisperse particles. The recent coupling of ICP-MS with
FFF has lowered its detection capability by more than three orders of magnitude and has allowed for multielement detection,
which is proving to be absolutely critical when performing environmental risk assessments studies of different engineered
nanoparticles.
However, there are still challenges to overcome, both in the FFF system and in the ICP-MS system. One of the recognized problem
areas is poor recoveries, which can be partly attributed to the nanoparticles sticking to the FFF membrane and not being eluted
into the detection system. It is also critical to develop optimized FFF run conditions as well as external and internal ICP-MS
calibration routines, which are each extremely important to achieve good accuracy, precision and recoveries of metal concentrations
in fractionated samples. As more studies are published, researchers in this field will have a better understanding of how
to minimize these problem areas and it is only a matter of time before FFF–ICP-MS becomes a routine analytical technique for
the measurement of ENPs in environmental samples.
Robert Thomas is a consultant and science writer specializing in trace element analysis.
Ken Neubauer is a Senior Scientist with PerkinElmer, specializing in ICP-MS and LC–ICP-MS.
Denise Mitrano is in the final year of her doctoral research at the Colorado School of Mines in the Department of Chemistry and Geochemistry.
Dr. James Ranville is an associate professor in the Department of Chemistry and Geochemistry at the Colorado School of Mines. Please direct
correspondence to: jranvill@mines.edu
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