1
2
K.L. Vikse et al. / International Journal of Mass Spectrometry 323–324 (2012) 8–13
4. Conclusions
The Hagen–Poiseuille equation can be used to reliably estimate
flow rates using pressurized sample infusion, but calibration of
flow rate for a given piece of tubing is recommended in order to
estimate the internal diameter accurately. Once this simple, one-
off experiment is performed, the analyst has a reliable pumping
system for ESI-MS with a low internal volume and robustness
towards a wide variety of solvents. The high dynamic range of mass
spectrometer in conjunction with continuous monitoring allows
the simultaneous measurement of all charged species in solution,
including low abundance intermediates, as exemplified by the acid-
catalyzed deprotection of an amino acid. Air-sensitive systems
in unconventional solvents at temperatures up to reflux are also
readily accessible to this method, as shown by the silane redistri-
bution experiment. We anticipate our approach to be useful for
all chemists interested in reproducible, continuous monitoring of
reactions in which the relative abundance of ions is dynamic and
varies across several orders of magnitude.
Fig. 7. Experimental flow rates plotted vs. theoretical flow rates calculated using
the Hagen–Poiseuille equation. The 100 data points include flow rates calculated
using five different solvents, four different tube lengths and five different values
of overpressure (see Supporting information for data used to generate this plot).
The dashed lines indicate the variation expected if the inner diameter was 25% less
(
1:0.32) or 25% more (1:2.44) than the claimed value.
Acknowledgements
JSM thanks NSERC for operational funding (Discovery and Dis-
covery Accelerator Supplement), and CFI, BCKDF and the University
of Victoria for instrumental support. Thanks to Fraser Hof and
Ori Granot for useful discussions. We extend our thanks to the
two Chemistry 361 Analytical Chemistry classes that performed
some of the experimental work for this paper. From 2010: Bryan
Boots, Chelsea Burns, Alana Chester, Haeun Chung, Rebecca Courte-
manche, Sean Davidoff, Rebecca Dixon, Rowan Fox, Jenna Frerot,
Jesse Gallop, Michael Hamilton, Lisa Hart, Ian Holley, Marc-Andre
Hoyle, Christy Hui, Megan Kilduff, Philip Klein, Aiko Kurimoto,
Jessamyn Logan, Cara Manning, Rebeccah McLean, Kirsten Medd,
Krista Morrow, Joshua Nero, Dean Neville, Emma Nicholls-Allison,
Kevin Nikelski, Jaimie Parton, Gillian Reay, Travis Schwantje, Shawn
Slavin, Dirk Slot, Sinan Soykut, Liana Stammers, Christine Tough,
Derek Waghray, Sophie Waterman and Kevin Weinreich. From
2011: Qinqi Chen, James Chircoski, Kaitlin Desilets, Morgan Ehman,
Emily Eng, Nicholas Erb, Patrick Fergusson, Heather Fitzpatrick,
Graham Garnett, Damon Gilmour, Ryan Hanson, Bochao Huang,
Chih-Hao Huang, Eric Janusson, Talon Jones, Manuel Ma, Angus
MacKay, Ashley March, James McFarlane, Jamie McGuire, Simon
McPhedran, Tanya Murray, Brett Nesmoe, Elisabeth Pharo, Sarah
Polkinghorne, Lauren Rainsford, Ryan Roberts, Andrew Rosenberg,
be seen indicating high precision in the flow rate measurements.
Some slight deviations from linearity are observed and this can
be attributed to the precision with which the pressure was set
for each experiment—the errors in the pressure reading were esti-
mated to be of the order of ± 0.1 psi (gauge markings are at 0.2 psi
increments). The relative (to water) viscosities of the solvents at
◦
2
0 C are 0.36 for acetonitrile, 0.44 for dichloromethane, 0.59 for
methanol, 0.68 for 50:50 acetonitrile:water (approximated from
◦
data collected at 25 C) [17], and 1 for water [18].
The large amount of data collected is best summarized by
plotting the actual flow rate at a given combination of solvent,
overpressure and tubing length and plot it against the calculated
value using the Hagen–Poiseuille equation (Fig. 7). In all cases, the
flow rates vs. overpressure graphs were almost perfectly linear
2
(
R > 0.99).
What is immediately clear from the plot is that different pieces
of tubing produce markedly different results. Because the over-
pressure, tubing length and solvent viscosity can be measured
accurately, the likely source of error is in the inner diameter of
the tube, for which any discrepancy in the listed value is magni-
fied to the fourth power. A ± 25% error in diameter is enough to
4
4
account for most of the variation (1.25 = 2.44, 0.75 = 0.32). The
ꢀ
ꢀ
ꢀꢀ
manufacturer’s listed tolerance for 1/16 o.d. 0.005 i.d. PEEK tub-
ꢀ
ꢀ
ing is ± 0.001 , i.e. ± 20% error, and this tolerance matches well with
our observed experimental variability of ± 25%. Nonetheless, it is
very easy to calibrate a given length of tubing by following the pro-
cedure we describe here (i.e. using a stopwatch and a balance) and
apply the appropriate correction to the Hagen–Poiseuille equation
for all samples run using the PSI method. Once this correction is
obtained, the equation simplifies to Q = kꢀP/ꢂ, where k combines
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
References
4
the experimental correction with ꢁd /128L, which is a constant for
a given piece of tubing. We regard this approach to be more reliable
than direct measurement of the diameter, because not only is it dif-
ficult to measure inner diameters of PEEK tubing accurately on the
sub-millimeter scale, there is no guarantee that that diameter at
the end(s) is representative of the entire length of tubing. Knowing
the flow rate at a given pressure allows for quick optimization of
the experimental set-up, helping ensure that good spray conditions
are obtained and that consumption of the solution is appropriate
for the length of the experiment. Reproducibility of conditions is a
key consideration when attempting to extract kinetic information
from an online monitoring experiment.
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