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SUPPLEMENT TO
RECENT DEVELOPMENTS
IN HPLC AND UHPLC
Volume 33, Number s4 April 2015www.chromatographyonline.com
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www.chromatographyonline.com
HPLC and UHPLCHPLC and UHPLC
Recent Developments inRecent Developments in
4 RECENT DEVELOPMENTS IN HPLC AND UHPLC APRIL 2015
Articles
Recent Developments in HPLC and UHPLC . . . . . . . . . . . . . . . . . . . 8Mary Ellen McNally
A brief introduction to the articles — and ideas — presented in this supplement
The Simple Use of Statistical Overlap Theory in Chromatography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Mark R. Schure and Joe M. Davis
How can statistical overlap theory be applied to chromatography in everyday usage?
Determination of Preservatives in Cosmetics and Personal Care Products by LC–MS-MS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Emily A. Myers, Thomas H. Pritchett, and Thomas A. Brettell
The sample preparation for this LC–MS-MS method is short and simple, and the
method is capable of separating and identifying eight preservatives (including five
parabens) in <8 min, with excellent sensitivity.
Enhanced-Fluidity Liquid Chromatography: Connecting the Dots Between Supercritical Fluid Chromatography, Conventional Subcritical Fluid Chromatography, and HPLC . . . . . . . . . . . . . . . . 24Susan V. Olesik
In enhanced-fluidity LC (EFLC), a dissolved gas, such as carbon dioxide, is added
to the mobile phase. The resulting lower viscosity of the mobile phase and the
increased diffusivity decreases analysis time and often improves efficiency.
Selectivity and Sensitivity Improvements for Ionizable Analytes Using High-pH-Stable Superficially Porous Particles . . . . . . . . . . . 31William J. Long, Anne E. Mack, Xiaoli Wang, and William E. Barber
A novel approach to enhancing the selectivity of ionizable compounds using
superficially porous particles that are stable in a wider pH range is reported here.
Precision of Internal Standard and External Standard Methods in High Performance Liquid Chromatography . . . . . . . . . 40Karyn M. Usher, Steven W. Hansen, Jennifer S. Amoo, Allison P. Bernstein,
and Mary Ellen P. McNally
The internal standard method can significantly improve method precision, but attention
must be paid to the injection volume and the method by which the standard is added.
Cover images courtesy of Joe Zugcic, Joe Zugcic Photography; Tuomas Marttila/Pascal Broze/
Paul Tillinghast/Getty Images; Mark R. Schure and Joe M. Davis; Dan Ward
April 2015Volume 33 Number s4
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6 Recent Developments in Hplc anD UHplc April 2015 www.chromatographyonline.com
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www.chromatographyonline.com8 Recent Developments in Hplc anD UHplc APRIL 2015
FROM the Guest eDItOR
When I was asked to edit a supplement for LCGC again, I was delighted. My back-
ground in physical chemistry has always made me captivated by separation theory;
my career in industry has taught me to be practical in its use. My criterion to
choose contributors is the same as always: I ask fellow researchers who conduct work that I
find interesting. The selections here are quite varied, but they illustrate both the theory and
the practical perspectives of separation science.
Mark Schure and Joe Davis explain statistical overlap theory to a point that it can be
used in everyday chromatographic applications. This theory shakes the foundation for
many practicing chromatographers in that it statistically evaluates the probability of a peak
being pure. The results are not terrific. Simply, the authors show that for a moderately dif-
ficult separation the probability that a component of interest is resolved as a singlet peak
on a single column is only 14%. All is not lost however; multiple columns can be used to
increase this probability, although not as dramatically as I personally would like Ñ the
authors report the probability only increases to 52% for five columns in series. For those
of us who love the theory of chromatography, this is a fascinating article. For the rest who
know how important theory is to the practice of separations, this is an awakening and a reminder of what could be going
on inside our chromatographic systems. Chromatographers take heed!
Every morning when we reach inside our bathroom cabinets, we are probably not awake enough to think about the chemistry
behind the products we use. Brettell, Myers, and Pritchett, researchers at Cedar Crest College, have investigated liquid chroma-
tographyÐmass spectrometry (LCÐMS) for a series of parabens, BHT, and BHA. These compounds are used as preservatives in
everyday products such as toothpaste, hand lotion, deodorant, foundation, hand sanitizer, and lipstick. Methyl and ethyl parabens
were the most common preservatives and were found at the highest levels in deodorant and foundation samples. We should feel
safer knowing that there is a way to make sure preservatives can be accurately measured in the personal care products we use daily.
Supercritical fluids were first used in chromatography in 1962 by Ernst Klesper, and enhanced-fluidity chromatography (EFC)
was first examined by Susan Olesik and her group in 1991. Supercritical fluid chromatography (SFC) is when the mobile phase,
either a pure or modified gas, is operated above its critical point. Enhanced-fluidity solvents are solvents that have added dissolved
gases. Ironically, much of the literature using SFC with mixed solvents is mislabeled, as the temperature and pressures are too low
for criticality. In actuality, these supercritical separations are conducted with subcritical conditions. For the practicing chromatog-
rapher, Olesik explains the theory behind the appropriate choice of solvent and operating conditions given the variety of options
open to us: SFC, EFC, high performance liquid chromatography (HPLC), and even subcritical chromatography conditions.
At the frontier of column technology, there has always been a quest to control pH at extreme levels and adjust selectivity
while maintaining long column lifetimes. Long, Mack, Wang, and Barber showed that by keeping a gradient constant and
altering pH, the elution order of a group of eight acid, base, and neutral compounds could be dramatically changed and reso-
lution improved with a superficially porous column. Positive ion electrospray mass spectrometry of basic compounds using
high and low pH gradient HPLC showed improved peak shape, increased retention as well as signal and sensitivity increases.
With these new superficially porous particle technology columns, separation scientists can examine a wider range of method
development options. Here comes high efficiency, high speed, and durability, yeah!
With my coauthors Usher, Hansen, Bernstein, and Amoo, my laboratory has pursued the never-ending question of whether
or not better precision is obtained when an internal standard is used instead of an external standard. In all of our experiments,
the internal standard method significantly improved the precision. However, additional influencing factors on the precision
are the injection volume and the method by which the internal standard is added to the analyte. Does this definitively settle
this question? Only time will tell.
My hope is that you appreciate the articles in this supplement as much as I have taken pleasure in reading and editing them.
These are some of my favorite scientists, who have challenged and continue to challenge my own experimental design as well
as interpretation of results. I am confident that their advancements to the field of separation science will challenge you in your
laboratory. Thank you to the authors Ñ excellent work!
Recent Developments in HPLC and UHPLC
Mary Ellen McNally, PhDDuPont Crop Protection
Now for my next trick: Essential Macromolecular Characterization
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©2014 Wyatt Technology. DAWN, HELEOS, Optilab, Mobius and DynaPro are registered trademarks and Eclipse is a trademark of Wyatt Technology Corporation.
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10 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
1
0.8
0.6
0.4
k = 1
k = 2
k = 3
k = 4
k = 5
0.2
00 0.2 0.4 0.6 0.8 1.2 1.4 1.6 1.8 21α
s/m
Mark R. Schure
and Joe M. Davis
The Simple Use of Statistical Overlap Theory in Chromatography
The statistical overlap theory (SOT) of chromatography relates the
number of peaks that appear in a chromatogram to the number
of detectable components and the peak capacity. This theory
transformed chromatography in how it revealed that on a statistical
basis the number of peaks underestimates the number of components
present in the chromatogram. In this paper, we show how this
theory can be applied to chromatography in everyday usage.
The statistica l overlap theory
(SOT) is a useful theory that
gives the relationship between
the number of peaks observed in a
chromatogram, p, and the number
of detectable components, m. This
theory, originally devised by Davis
and Giddings (1), assumed that these
components were distributed using
Poisson statistics leading to peaks
being distributed randomly across
a chromatogram. The results were
rather sobering as one of the many
predictions of this theory states that
“a random chromatogram will never
contain more than about 37% of its
potential peaks and, worst of all from
an analytical point of view, 18% of its
potential single-component peaks” (1).
In other words, only 18% of the peaks
are from single, pure components and
only 37% or approximately one-third
of the components, show up as unique
peaks because of peak overlap. It is also
stated “that a chromatogram must be
approximately 95% vacant in order to
provide a 90% probability that a given
component of interest will appear as
an isolated peak.”
Simple Derivation
SOT shows that one of the most impor-
tant parameters in any chromato-
graphic separation is the peak satura-
tion, because it dictates how crowded
the separation is. The common label
for saturation is α, but it is not the
same as selectivity, which often has
the same label. For complex biological
samples α > 1 and for typical samples
with a few components α < 1. For a
separation of moderate complexity, α
≈ 1. The key to deciding whether to
proceed with a multidimensional sepa-
ration as opposed to a single column
separation is to understand the origin
and magnitude of α.
The treatment that follows is based
on time as the independent variable.
Space (as is the case for thin-layer chro-
matography, for example) and time are
equivalent in this treatment (1).
The peak saturation α is a metric of
peak crowding equal to
α = 4mσR*s/
1D [1]
where m is the number of detectable
single component peaks (SCPs) with
temporal standard deviation σ that
occupy a separation space of extent 1D. The term 1D is the time differ-
ence between the first and last peaks
in a chromatogram. A single component
peak is specif ically a peak in which
a pure component resides; in other
words, an SCP is a peak that is chemi-
cally pure, such as would be obtained
APRIL 2015 Recent Developments in Hplc anD UHplc 11www.chromatographyonline.com
on chromatographing a single com-
pound. The attribute R*s is the average
minimum resolution, which measures
the average smallest interval between
adjacent SCPs that are separated. R*s is
not a free parameter, but it depends on
the type of interpeak statistics func-
tion (for example, for random spacing
of SCPs or ordered, such as fractal
spacing of SCPs), the amount of peak
overlap, and the distribution of SCP
heights (2).
The attribute R*s differs from the
traditional resolution R s, which is
a parameter freely chosen by the
researcher. The traditional resolution
Rs is an important attribute of the peak
capacity that is defined (2) as the num-
ber of equi-spaced SCPs that fit within
a discrete time increment between t1
and tm so that
nc
−tm 1
4σR
Dt1
s 4σRs
= = [2]
By combining equations 1 and 2, one
obtains an alternate metric of peak
crowding, the effective saturation αe
= α / σ /= 4m = m / (ncRs)α D1R*
e s [3]
which depends only on m, σ, and 1D
(3). The effective saturation is a prac-
titioner-friendly metric for comparing
peak overlap in different separations,
because it is independent of R*s which
varies, as noted above, with saturation.
The predictions of SOT are derived
relative to α, but are more easily inter-
preted relative to αe.
Different approaches to SOT have
been proposed, including some based
on Fourier analysis (4,5) and pulse-
point statistics (6). Various reviews of
the different methods have been pub-
lished (7,8). In this article, we consider
only point-process statistics, in which
the distribution of intervals between
the retention times of successive SCPs
is considered. For simplicity, we con-
sider only cases where SCPs are spread
more or less equally throughout the
separation.
The simplest interpeak statistics
function in SOT is based on Poisson
statistics, which assume that SCPs are
distributed across the separation space
randomly. This assumption is well-
founded both empirically (1,9–12) and
theoretically (13,14) for a number of
mixtures. This random placement of
SCPs requires that the arrival times
of SCPs are governed by a Poisson
process based on exponential waiting
times (15):
P(t) = λe-λt [4]
where P(t) is the probability density of
finding the next SCP some time t after
the last SCP. This relationship gov-
erns such random processes as radio-
active decay and is called a renewal
process (16) in the probability litera-
ture. The quantity λ in equation 4 is
the component density or the number
of components per total separation
space so that λ = m/1D. The expecta-
tion (or average) value of the density
P(t) is E and is equal to 1/λ. This can
be generalized: E = 1D/m. Therefore,
the expectation value of the density
can be interpreted as the average sepa-
ration space between SCPs.
The probability that the interval
between two SCP centers exceeds
some time t′= 4σR *s, allowing these
SCPs to be resolved from each other is
Pr(t ≥ t')t'
∞
P(t)dt =exp [–λt']∫= [5]
Noting that α = λt′, one ultimately
finds
Pr(t ≥ t') p/m ≡γ=exp (–α)= [6]
where p is the number of peaks in the
chromatogram and the ratio γ = p/m
is the fraction of components that are
interpretable as peaks. Thus, this frac-
tion is a simple function of the satura-
tion α. For the appropriate choice of
R*s (17,18), p is the number of visible
maxima.
Another quantity of interest is the
fraction of components that are singlet
peaks (1):
12
P =exp (–2α)=γ [7]
In general, the fraction Pn of compo-
nents appearing in peaks containing n
components (for example, for doublets,
n = 2; for triplets, n = 3; and so on) is
as follows (1):
nn ne=P (1–γ) (1–e–α)=
2γn 1– n 1––2α [8]
Equations 6–8 are valid for different
interpeak statistics functions produc-
ing different renewal processes, as long
as the ratio γ = p/m is replaced by the
appropriate function of α (19).
Consequences of Overlap
We show the consequence of over-
lap using the random SCP approach
developed in the equations above in
Figure 1. Other renewal processes
besides the (random) Poisson process,
for example, two power-law (fractal)
1
0.8
0.6
0.4
0.2
0.5
Poisson
p/m
Gamma process
Fractal D = 0.2
Fractal D = 1.0
1.5α
2.5 3.53 4200 1
Figure 1: Plot of p/m, the fraction of peaks found in the chromatogram as a func-tion of the saturation α for four renewal processes: Poisson (random) process, solid line; power-law (fractal) process with D = 1.0, β = 10, dashed line, D = 0.2, β = 10, dotted line; and gamma process (P = 4, as explained in reference 19), dash-dotted line. The β parameter is explained in reference 2.
12 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
renewal processes (2) and a Γ process
based on the gamma distribution
(19), are a lso shown. While these
processes differ in the assumptions
of the statistical SCP spacing, the
trends are apparent. The dimension-
ality D used in Figure 1 and below
is explained in great detail in refer-
ence 2 and is a measure of the order-
ing of a chromatogram. At higher D
values ordering increases and at low
D values there are many gaps in the
chromatogram.
As the saturation α increases, the
fraction of components that appear as
peaks decreases rapidly. In the case of
SCPs that are more ordered, as found
in the fractal and Γ processes, the
decrease in peaks as α increases does
not fall as rapidly as a random order-
ing, at least at low saturations. How-
ever, Figure 1 also shows that as α
approaches one, ordering causes more
loss of peaks than a random filling of
the peak space.
The consequences of overlap are
shown in a complementary way in
Figure 2, where we use synthetic chro-
matograms comprising sums of Gauss-
ian peaks that are distributed randomly
throughout the retention time range
and have uniformly random heights.
The zone (or SCP) standard deviation
used here is obtained from the follow-
ing well-known equation (20):
t / N =—
√σ [9]
so that given a number N of theoreti-
cal plates and a retention time t the
zone standard deviation σ is deter-
mined. For Figure 2, the retention
time in equation 9 is that of the first
retained SCP, and a model of con-
stant zone width is assumed, which
is approximated in temperature-pro-
grammed gas chromatography (GC)
and gradient-elution liquid chroma-
tography (LC).
The four chromatograms in Figure
2 vary in efficiency (number of plates),
and this is ref lected in the Gaussian
zone standard deviation, σ, which in
turn affects αe and nc (as calculated
from equations 2 and 3, with Rs = 1).
The number of components, m, is 100.
The retention times are represented at
the bottom of Figure 2 by stick loca-
tions that show what the chromato-
gram would look like, except for the
distortion of peak heights, if the peaks
were infinitely narrow, that is, if σ = 0
and hence αe = 0 and nc = ∞.
As can be seen from Figure 2, at high
eff iciency with N = 100,000 plates,
94 peaks are present. This number
drops off to 87 when the plate count
is reduced to 50,000. At 10,000 plates,
75 peaks are present and at 5000 plates
only 66 peaks are present. Only a frac-
tion of these peaks are singlets; a good
number of these are fused doublets
and triplets (and even more complex
multiplets). Hence, as eff iciency is
reduced, as measured by increases of
αe, the number of peaks present drops
monotonically.
The consequences of this phenom-
enon are well known. Peak fusion
interferes with proper quantitation. It
also interferes with the identification
of specific components. Often times
this can be aided with mass spectrom-
etry (MS) detection. However, this is
not always the case as peak fusion can
lower ionization efficiency, and mass
spectrometry often cannot distinguish
between closely related compounds
with the same molecular weight (and
hence the same parent ion).
Chromatography is particularly
problematic for samples of biological
origin because of the multiplicity of
forms, called isoforms. These isoforms
are closely related in structure (but are
not the same) yet may have different
chromatographic retention. In addi-
tion, many biological molecules have
dynamic structure so that chromato-
graphic retention occurs with a mul-
tiplicity of different molecular con-
formations, all of which lead to zone
broadening and a lowering of the over-
all effective efficiency. These effects
reduce the apparent efficiency of the
chromatographic process and cause
an artif icial increase in α, making
chromatographic separation more dif-
ficult for biomolecules than in the case
of small molecules. This is why bio-
molecules are often denatured before
analysis in the hopes of minimizing
the conformational shifts during the
separation process.
Use of the SOT as a Ratio
Another useful view of SOT is to
express equation 6 as a ratio. In this
way, we can estimate what the gain or
loss of peaks will be by changing effi-
ciencies at constant sample, constant
selectivity, and constant relative sol-
vent program.
A common shortcoming in SOT cal-
culations is the failure to distinguish
between the freely chosen traditional
resolution Rs and the average mini-
mum resolution R*s. The assumption
that they are the same introduces
αe = 0.769
αe = 0.544
αe = 0.243
αe = 0.172
σ (s) = 2.68
σ (s) = 1.89
σ (s) = 0.847
σ (s) = 0.599
N = 5000
N = 10000
N = 50000
N = 100000
0 10 155Time (min)
Re
lati
ve
in
ten
sity
2520 30
nc = 130
nc = 184
nc = 411
nc = 581
p = 66
p = 75
p = 87
p = 94
Figure 2: The effect of varying effciency (number of plates) on the number of visible peaks. The numbers of peaks detected (p) are 94, 87, 75, and 66 for four different eff-ciency scenarios given 100 components. The symbols are effective saturation, αe, number of plates, N, peak capacity, nc, Gaussian standard deviation zone width in s, σ, and the number of visible peaks, p.
APRIL 2015 Recent Developments in Hplc anD UHplc 13www.chromatographyonline.com
error, and the distinction must be kept
in rigorous work. However, it is con-
venient to identify them to simplify
matters and evaluate trends. We do
so here for simplicity’s sake, but the
results obtained must be interpreted as
only guidelines.
Consider a case in which the dura-
tion 1D of two separations is the same
but the SCP standard deviations
therein are different. Evaluating the
ratio of equation 6 with fixed m (con-
stant sample component number), one
f inds, with the subscripts denoting
two different columns:
( )
=
p1p2
= = =
e 1
1 1
–α1–α
e 2–αe e
m2
nc 1nc
2α
–
4mR s { }exp [ ]D
1 2σ 1σ– [10]
where α1 and α2 are two different satu-
rations, nc1 and nc2 are two different
peak capacities, and σ1 and σ2 are two
different SCP standard deviations.
Using equation 10 and H = L/N,
where H is the plate height, L is the
column length, and the nondimen-
sional retention parameter k′ = (t/t0)–1,
with t0 equaling the void time, one can
show that
4mRs {=exp [ }]p
1p
2
dL
1+ h2 h1–k'kmax'• •
[11]
where d is the particle diameter, k′max
is the maximum k′ used in the analy-
sis, and h is the nondimensional plate
height, H/d. As an example in LC,
consider the chromatographic values
of Rs = 1, k′ = 5, k′max = 20, L = 15 cm,
d = 2.7 µm, h2 = 1.5, and h1 = 1.0. For
these parameters, the ratio in equa-
tion 11 for a 200 component mixture
(m = 200) is equal to 1.25, indicating
that 25% more peaks would appear
in a chromatogram using a column
that was extremely high in efficiency
where h = 1.0, as compared to a more
conventional very high performance
column, for example a core–shell par-
ticle where h = 1.5. This number sug-
gests that the pursuit of even higher
performance column technology is a
most desirable goal in increasing the
number of detectable peaks. Further-
more, it is known that even if this level
of performance is not warranted, the
speed of separation can be increased
when high efficiency column technol-
ogy is utilized.
For situations where zones are ordered,
using fractal statistics, the ratio approach
is powerful. It can be shown (2) that
under limiting conditions the ratio of
the number of peaks found is related to
the two plate counts, N1 and N2, and the
fractal dimension D, such that
=
p1
p2
D/2N 1N 2( ) [12]
Multidimensional
Separation by k Columns
The results presented earlier show
that the limited separation space of
one column, even those of very high
eff iciency, stil l has limited separa-
tions capabilities. Of historic inter-
est is the use of multiple columns to
increase the likelihood that a given
compound is separated by at least one
column. The probability of success
was f irst addressed by Connors (21)
and subsequently reexamined (22).
For k separations (that is, columns)
of the same mixture, with the separa-
tions having the same saturation but
independent separation mechanisms,
the probability s/m that a component
appears as a singlet peak on at least
one column is
(1–γ ) –2αs/m 2 k k= =–1 (1–e )–1 [13]
where the last equality applies to a
Poisson distribution of SCPs. Figure
3 is a graph of the f inal expression
in equation 13 for k values between
1 and 5. The k = 1 graph represents
separation by a single column. As k
increases, the likelihood of separation
increases. For a saturation α equal to 1,
corresponding to a separation of mod-
erate difficulty, the likelihood that a
component of interest is resolved as a
singlet peak on a single column (k =
1) is only 14%. However, this number
increases to 25%, then 35%, then 44%,
and finally 52% as the number of col-
umns is increased from two, to three,
to four, and finally to five.
Other types of multidimensional
separations (k ⩾ 2) can be considered.
A classic method is column switch-
ing, in which a subsection of the
entire chromatogram is transferred
to another column. Two-dimensional
chromatography (k = 2) attempts to
increase the peak capacity by provid-
ing a separation area rather than a
line, and this is needed for very com-
plex mixtures. A few cases of separa-
tions in higher dimensions (for exam-
ple, k = 3) have been reported. SOTs
have been developed for all of these
methods (23–26).
Conclusions
SOT started in the early 1980s, and a
glance at the references below shows
that many were published long ago.
What is the relevance of SOT today?
The hope of early researchers that
1
0.8
0.6
0.4
k = 1
k = 2
k = 3
k = 4
k = 5
0.2
00 0.2 0.4 0.6 0.8 1.2 1.4 1.6 1.8 21α
s/m
Figure 3: Graph of the probability that a given component appears as a singlet peak, s/m, versus the saturation of k independent columns.
14 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
SOT could be used routinely to esti-
mate the number of components in
mixtures is largely unfulf illed. The
reason is that too many unknowns
exist in rea l chromatograms, per-
haps most importantly the type of
interpeak statistics function (and its
possible variation over the separa-
tion) governing the spacing between
SCPs. The large variation of SOT
predictions for different functions is
shown in Figure 1. Various functions
have been proposed over the years
(1,2,4,19), with assessments based
on the quality of their description of
experimental data. Nevertheless, an
inf inite number of such functions
can be proposed (based on known or
empirical statistical laws), and unless
one knows on a physicochemica l
basis what functions are favored for a
given mixture and column, one is left
with uncertainty.
However, SOT does serve two pur-
poses. First, it provides the basis for
semiquantitative to quantitative pre-
dictions of the expected outcome of
the completeness of a separation in a
chromatogram, and how much effort
is required to improve that chromato-
gram. This is especially true for a
single column, where the validity of
the assumption of Poisson statistics
is often justif ied. Several such pre-
dictions were presented here. Second,
theory can be used to model attributes
of interest in chromatograms, even
when the assumptions of SOT do not
apply. For example, the correlation of
retention times in many two-dimen-
sional chromatograms inva lidates
the assumption of SCP randomness.
Nevertheless, two-dimensional SOT
has been used on model systems to
understand the undersampling of
f irst-dimension peaks in comprehen-
sive two-dimensional chromatography
(27), the improvement of resolution
therein by the use of multivariate
selectivity (28), and the comparison
of one- and two-dimensional chroma-
tography (29).
SOT offers powerful, yet practical
insight into the statistical mechanics
of separation. As with many areas of
separation science, the development
of SOT is an interdisciplinary task,
in this case between chemistry and
applied probability theory. The ini-
tia l mathematical dif f iculties have
been overcome by a continuous
ref inement of SOT conducted by
a multitude of authors involved in
developing and ref ining chromato-
graphic theory. The results and pre-
dictions are meaningful and make
very practical guides to experimental
methods development.
Biomedical areas of research such
as the search for biomarkers, metab-
olomics ana lysis, and proteomics
research a l l dea l with saturation
issues in chromatography. The con-
sequences of saturation include an
undeniable loss in unique identif ica-
tion in single channel detectors. The
instrumenta l development of the
chemical analysis process requires
coupling high resolution columns,
perhaps even multiple separation
stages, together with multichannel
detectors such as mass spectrometers
and multiple MS stages. Sometimes
zones can be resolved with unique
ion identif ication schemes, and some-
times zones have mixtures that are
not resolvable by MS. This coupling
and its ref inement towards reach-
ing reliable molecular identif ication
needs to be understood quantitatively
in the context of chromatography by
the extension of SOT.
References
(1) J.M. Davis and J.C. Giddings, Anal .
Chem. 55, 418–424 (1983).
(2) M.R. Schure and J.M. Davis, J. Chro-
matogr. A 1218, 9297–9306 (2011).
(3) J.M. Davis and P.W. Carr, Anal. Chem.
81, 1198–1207 (2009).
(4) A. Felinger, L. Pasti, and F. Dondi, Anal.
Chem. 62, 1846–1853 (1990).
(5) M.C. Pietrogrande, M.G. Zampolli, and
F. Dondi, Anal. Chem. 78, 2579–2592
(2006).
(6) F. Dondi, A. Bassi, A. Cavazzini, and
M.C. Pietrogrande, Anal . Chem. 70,
766–773 (1998).
(7) M.C. Pietrogrande, A. Cavazzini, and F.
Dondi, Rev. Anal. Chem. 19, 123–156
(2000).
(8) A. Felinger and M.C. Pietrogrande, Anal.
Chem. 73, 619A–626A (2001).
(9) D.P. Herman, M.-F. Gonnord, and G.
Guiochon, Anal. Chem. 56, 995–1003
(1984).
(10) M. Martin, D.P. Herman, and G. Gui-
ochon, Anal . Chem . 58, 2000–2007
(1986).
(11) C. Samuel and J.M. Davis, J. Chromatogr.
A 842, 65–77 (1999).
(12) C. Samuel and J.M. Davis, J. Microcol.
Sep. 12, 211–225 (2000).
(13) A. Felinger, Anal. Chem. 67, 2078–2087
(1995).
(14) J.M. Davis, M. Pompe, and C. Samuel,
Anal. Chem. 72, 5700–5713 (2000).
(15) J.F.C. Kingman, Poisson Processes (Oxford
University Press, 2002).
(16) D.R. Cox, Renewal Theory (Methuen &
Co. 1967).
(17) A. Felinger, Anal. Chem. 69, 2976–2979
(1997).
(18) J.M. Davis, Anal. Chem. 69, 3796–3805
(1997).
(19) M.C. Pietrogrande, F. Dondi, A. Felinger,
and J.M. Davis, Chemom. Intell. Lab. Sys.
28, 239–258 (1995).
(20) J.C. Giddings, Unified Separation Science,
(Wiley, 1991).
(21) K.A. Connors, Anal. Chem. 46, 53–58
(1974).
(22) J.M. Davis and L.M. Blumberg, J. Chro-
matogr. A 1096, 28–39 (2005).
(23) J.M. Davis, Anal. Chem. 65, 2014–2023
(1993).
(24) M. Martin, Fresenius’ J. Anal. Chem. 352,
625–632 (1995).
(25) C. Samuel and J.M. Davis, Anal. Chem.
74, 2293–2305 (2002).
(26) S. Liu and J.M. Davis, J. Chromatogr. A
1126, 244–256 (2006).
(27) J.M. Davis, D.R. Stoll, and P.W. Carr,
Anal. Chem. 80, 461–473 (2008).
(28) J.M. Davis, S.C. Rutan, and P.W. Carr, J.
Chromatogr. A 1218, 5819–5828 (2011).
(29) J.M. Davis, Talanta 83, 1068–1073
(2011).
Mark R. Schure is with Kroungold
Analytical, Inc. in Blue Bell, Pennsylvania.
Joe M. Davis is with the Department of Chemistry and Biochemistry at Southern Illinois University at Carbondale in Carbondale, Illinois. Direct correspondence to: [email protected] ◾
For more information on this topic,
please visit
www.chromatographyonline.com
16 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
Emily A. Myers, Thomas H. Pritchett, and Thomas A. Brettell
Determination of Preservatives in Cosmetics and Personal Care Products by LC–MS-MS
A liquid chromatography–electrospray ionization tandem mass
spectrometry (LC–ESI-MS-MS) method has been developed to determine
multiple preservatives in cosmetics and personal care products.
Cosmetic and personal care products
that contain water require protec-
tion against the growth of microor-
ganisms to ensure product safety. Preserva-
tives are natural or synthetic ingredients
added to products to prevent spoilage,
microbial growth, undesirable chemical
changes, or to extend the product’s shelf
life (1). The use of preservatives in per-
sonal care products is important because
not only do they prevent product damage
caused by microorganisms but they also
help protect the product from inadvertent
contamination by the consumer during
use. Without the addition of preservatives,
the product may become contaminated,
which can lead to product degradation
and, in the case of cosmetic foundations,
ultimately increase the risk of irritation or
even infection. Preservatives are added to
personal care products at relatively low lev-
els to ensure products remain safe and per-
form as intended over their lifetime. The
determination of preservatives in these
products is important for quality control
to prevent allergic reactions and other
health issues.
The most widely used preservatives
in cosmetic products are a class of com-
pounds generally referred to as parabens
(1). These compounds are alkyl esters of
p-hydroxybenzoic acid (Figure 1). They
are used for their preservative properties
in cosmetic and personal care products
because of their antimicrobial activities,
low toxicity, and low production cost (2).
Methylparaben (MeP) is found in nearly
all cosmetics and many pharmaceuticals
(3). The use of parabens in personal care
products has caused concern because of
their potential adverse effects, including
proliferation of breast cancer (4–8) and
reduction of sperm count and testosterone
levels (9–12). The United States Food and
Drug Administration (FDA) finds that
although parabens can mimic estrogen,
the levels found in these products are at
such low levels that their activity on the
body does not cause cancer in any higher
incidence than naturally occurring estro-
gen despite contrary belief (13). However,
when counterfeit products make it to
market, they are unregulated and may
contain preservative levels that may pose a
health risk to the user. Therefore, accurate
methods to determine the levels of these
compounds need to be available for moni-
toring preservative concentrations in cos-
metic and personal care products.
Current analytical methods for the
determination of preservatives in cos-
metic and personal care products include
high performance liquid chromatogra-
phy (HPLC) (14,15), ultrahigh-pressure
liquid chromatography (UHPLC) (16),
UHPLC–tandem mass spectrometry
(MS-MS) (17), gas chromatography–mass
spectrometry (GC–MS) (18), GC (19,20),
solid-phase microextraction (SPME)-GC–
MS-MS (21), and micellar electrokinetic
chromatography (MEKC) (22).
Most methods have previously deter-
mined single preservatives in pharmaceu-
tical or personal products. The methods
that have been published have focused on
a small group of preservatives, but only a
few methods have included the simultane-
ous measurement of multiple preservatives.
Methods for the preservative analysis of cos-
metic products have mainly focused on the
APRIL 2015 Recent Developments in Hplc anD UHplc 17www.chromatographyonline.com
determination of parabens. The analysis of
more than one class of preservatives is still a
field under development. We have included
not only parabens in this study, but also
compounds such as DL-α-tocopherol ace-
tate (Toco) and butylated hydroxytoluene
(BHT). In previous chromatographic meth-
ods the sample preparation has focused on
specific product categories; most are GC
methods requiring derivatization. Cur-
rently, there is no universally accepted
sample preparation or analytical method
for different types of sample matrices such
as pastes, liquids, creams, and ointments.
In this study, we have developed a simple
sample preparation method using liquid
chromatography–electrospray ionization
tandem mass spectrometry (LC–ESI-MS-
MS) to analyze preservatives in cosmetic
and personal care products using a relatively
small sample, 100 mg. Experimental condi-
tions were optimized for sample preparation
and analysis to achieve maximum sensitiv-
ity and accuracy. The optimized method
was used to analyze the following preserva-
tives: methylparaben, ethylparaben, propyl-
paraben, isopropylparaben, benzylparaben,
O
O
HO
Name
Methylparaben (MeP)
Ethylparaben (EtP)
n-Propylparaben (PrP)
n-Butylparaben (BuP)
Benzylparaben (BzP)
R
–CH3
–CH2CH3
–CH2CH2CH3
–CH2CH2CH2CH3
R
CH2
Figure 1: Chemical structures of parabens.
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to a specifc brand of instrument or geographic region. We live and breathe phase chemistry,
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countries and six continents with unrivaled Plus 1 service, applications, and expertise. From LC
and GC columns to sample prep, reference standards to accessories, Restek is your frst and
best choice for chromatography.
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18 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
butylparaben, triclosan, DL-α-tocopherol
acetate, butylated hydroxyanisole (BHA),
and butylated hydroxytoluene (BHT).
The procedure can simultaneously ana-
lyze these preservatives in a single chro-
matographic analysis of various kinds of
sample matrices from cosmetic and per-
sonal care products.
Experimental
Sample Preparation
Cosmetic and personal care samples were
purchased from local stores. Products
analyzed included lipstick, foundations,
deodorant, hand lotion, hand soap, and
toothpaste. Standard preservative sample
and cosmetic and personal care prod-
uct preparation was as follows: 100 mg
sample was placed into 5 mL of 1:1 (v/v)
methanol–acetonitrile. This solution was
then sonicated for approximately 10 min
and then centrifuged for 5 min at 800g.
The supernatant was then filtered using
a 0.2-µm Millipore filter. Then, 1 mL of
the filtered supernatant was placed into an
autosampler vial along with 60 µL of 100
ppm internal standard (BHA).
The following reagents were purchased
from VWR: HPLC-grade methanol,
HPLC-grade water, formic acid, and ace-
tonitrile.
Preservative Standards
The following preservatives were purchased
from Sigma Aldrich: ethyl 4-hydoxybenzo-
ate (ethylparaben) (lot STBC0530V), pro-
pyl 4-hydroxybenzoate (propylparaben)
(lot BCBK9343V), methyl 4-hydroxyben-
zoate (methylparaben) (lot MKBG5184V),
butyl 4-hydroxybenzoate (butylparaben)
(lot MKBR1951V), benzyl 4-hydroxyben-
zoate (benzylparaben) (lot MKBL1242V),
triclosan (lot LRAA1072), and butylated
hydroxyanisol (BHA) (lot MKBJ4456V).
The preservatives DL-α-tocopherol acetate
(lot SLBB9917V) and 2,6-di-tert-butyl-4-
methylphenol (BHT) (lot 10156687) were
purchased from Alfa Aesar. Isopropylpara-
ben (lot S5QHD-CE) was purchased from
Santa Cruz Biotechnology.
Liquid Chromatography
Liquid chromatography was performed
on a Shimadzu LC-20 Prominence sys-
tem equipped with two Shimadzu LC-20
AD prominence liquid chromatography
binary pumps, a Shimadzu DGO-20A3
Prominence degasser, and a Shimadzu
SIL-20AC Prominence autosampler. A 50
mm × 3.0 mm, 3.0-µm Ultra Biphenyl
column (Restek) was used for all analyses.
A binary mobile phase was used: the weak
mobile phase (A) was 0.1% (v/v) formic
acid in HPLC-grade water and the strong
mobile phase (B) was 0.1% (v/v) formic
acid in 2-propanol. The flow rate was 0.3
mL/min. Before running the method on
the preservative standards and samples,
the lines and the column were flushed
using the mobile phase to elute any
compounds that may have been present.
Pumps A and B were also purged before
any experimental run to eliminate any
cross contamination. The LC oven tem-
perature was held constant at 25 °C. To
m/z
Inte
nsi
ty (
cps)
4.2e7139.1
167.2
95.1
121.1
4.0e7
3.8e7
3.6e7
3.4e7
3.2e7
3.0e7
2.8e7
2.6e7
2.4e7
2.2e7
2.0e7
1.8e7
1.6e7
1.4e7
1.2e7
1.0e7
8.0e6
6.0e6
4.0e6
2.0e6
50 55 60 65 70 75 80 55 90 55 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170
Figure 3: Enhanced product ion 10 eV ethylparaben spectrum (Q1 mass: 167 amu; Q3 masses: 95, 139 amu).
100
80
60
40
20
00.0 5.0
Time (min)
%B
10.6
Figure 2: Gradient profle of %B versus time.
APRIL 2015 Recent Developments in Hplc anD UHplc 19www.chromatographyonline.com
obtain optimal separation the following
gradient was used: start with 50% B and
hold for 2.5 min; from 2.50 to 3.00 min
linearly increase the concentration of B to
95%; hold the concentration of B at 95%
to 7.5 min. After completion of the data
acquisition, the concentration of B was
dropped back to 50% and the column was
allowed to reequilibrate for 3 min. The
gradient profile can be seen in Figure 2.
The autosampler injection volume was set
constant at 2 µL for each sample.
Mass Spectrometry
MS analysis of all samples was performed
on an AB Sciex 3200 QTRAP triple-
quadrupole mass spectrometer equipped
with an ESI interface. Electrospray ioniza-
tion was carried out in positive-ion mode.
Q1 and Q3 were both operated with unit
resolution. The source temperature was
500 °C and the ionization voltage was
4500 V. The preservatives were quantified
in multiple reaction monitoring (MRM)
mode with a dwell time of 100 ms. Opti-
mized parameters for MS-MS analysis are
listed in Table I. The collision energy (CE)
and declustering potential (DP) for each
preservative analyte are listed in Table II.
Results and Discussion
Using 100 ppm preservative stock solutions,
the enhanced product ions (EPIs) for each
preservative were determined using ESI-
MS-MS with the exception of BHT, whose
EPI spectrum was determined using a 1000
ppm solution. The data obtained are listed
in Table II, and an example EPI spectrum
of ethylparaben can be seen in Figure 3. The
LC gradient conditions were optimized to
achieve the best separation of a mixture of
standard preservatives. The chromatogram
of a standard preservative mixture (30.0 ppm
each) can be seen in Figure 4. The respective
retention times of the standard preservatives
in the mixture are listed in Table III. The
relative responses of the parabens were con-
sistent. However, BHT showed poor ioniza-
tion efficiency and did not give enough of a
response to give detection limits that were
acceptable enough to detect it in some sam-
ples. On the other hand, DL-α-tocopherol
acetate gave a larger response than the para-
bens. We attempted to include triclosan in
the method, but it was only detectable in the
negative ion mode so this analyte was not
included in the procedure.
The following calibrator solutions were
made by dilution with HPLC-grade
methanol of the stock preservative mixture
solution: 0.1, 0.5, 1.0, 5.0, 30.0, 70.0, and
100.0 ppm. Calibration curves were gener-
ated by analyzing samples in triplicate over
six days. As an example, the calibration
curve for ethylparaben can be seen Figure
5. Figures of merit were obtained from the
calibration curve data. The figures of merit
data for all of the preservatives including
Table II: The enhanced product ion data for standard preservatives
Preservative Q1 Mass (amu) Q3 Mass (amu) CE (V) DP (V)
Methylparaben 153 121 20 29
Methylparaben 153 65 45 29
Ethylparaben 167 139 15.5 25
Ethylparaben 167 95 24 25
Ethylparaben 167 121 28 25
Propylparaben 181 139 15.5 21.5
Propylparaben 181 95 26 21.5
Propylparaben 181 121 29.5 21.5
Tocopherol acetate 473 207 28 85
Tocopherol acetate 473 165 55 85
BHT 220 205 23 39
BHT 220 145 40 39
BHA 180 165 21 37
BHA 180 137 33 37
BHA 181 166 22 37
BHA 181 138 32 37
Butylparaben 195 139 15.5 26
Butylparaben 195 121 31 26
Butylparaben 195 95 25.5 26
Benzylparaben 229 91 22 26
Benzylparaben 229 65 50 26
Isopropylparaben 181 139 15.5 21.5
Isopropylparaben 181 121 30 21.5
Isopropylparaben 181 95 25 21.5
Table I: Optimized MS-MS parameters for the determination of standard preservatives
Parameter Optimized Value
Source temperature (°C) 500
Ionization voltage (V) 4500
Ion source (GS1) settings 40
Ion source (GS2) settings 40
Curtain gas settings 40
CAD gas settings 4
Declustering potential (DP) See Table II for individual analytes
Entrance potential (V) 10
Collision energy (CE) See Table II for individual analytes
Collision cell exit potential (V) 2.3
20 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
the equation for regression, R2 values, limit
of detection (LOD), and limit of quanti-
fication (LOQ) are listed in Table IV. All
analytes produced linear data plots with
R2 values >0.99. The LOD and LOQ were
determined by first plotting the calibration
curves for each standard preservative. After
they were plotted, the following equation
was used to calculate the LOD:
LOD = (3 × SEINTERCEPT)/S [1]
and LOQ was calculated using the follow-
ing equation:
LOQ = (10 × SEINTERCEPT)/S [2]
The LOD and LOQ values from each
individual preservative resulted in an over-
all LOD range of 0.91–4.19 ppm and an
LOQ range of 3.03–14.00 ppm.
Using the sample preparation procedure
described above, the chromatographic
method was applied to the following cos-
metics and personal care products: founda-
tions, lipstick, deodorant, hand lotion, hand
sanitizer, and toothpaste. Sample prepara-
tion was identical to that used to create the
standard preservative solutions. For example,
the chromatogram of a toothpaste sample
can be seen in Figure 6. Methylparaben
and ethylparaben were both detected in this
sample. Figure 7 shows the chromatogram
from a foundation sample. The preserva-
tive peaks methylparaben, ethylparaben,
and propylparaben as well as the peak for
the internal standard, BHA, can easily be
seen. Although the peaks for BHT and
DL-α-tocopherol acetate cannot be readily
observed on the chromatogram since they
were present in relatively low concentrations,
they were detected and quantified. The per-
cent concentrations for the samples analyzed
are listed in Table V. BHT, methylparaben,
and ethylparaben were detected in most of
the samples. Benzylparaben and butylpara-
ben were not detected in any of the samples
tested. Figure 8 is a bar graph comparing
the relative quantities of the different pre-
servatives in the sample products tested. It
is interesting to note that the deodorant
sample tested and one of the foundation
samples (F4) had relatively larger quantities
of parabens compared to the other products.
Specifically, methylparaben and ethylpara-
ben were present in larger concentrations.
Propylparaben was also detected in the one
foundation sample (F4).
Concentration (µg/mL)
y = 0.1999x + 0.1586R2 = 0.99952
LOD: 1.17 µg/mLLOQ: 3.89 µg/mL
Tota
l avera
ge p
eak r
ati
os
2.50E+01
2.00E+01
1.50E+01
1.00E+01
5.00E+00
0.00E+000 20 40 60 80 100 120
Figure 5: Calibration curve for ethylparaben.
Table III: Retention times for preservatives in the 30.0 ppm mixture solution
Preservative Retention Time (min)
Methylparaben 1.60
Ethylparaben 1.83
Propylparaben 2.21
Butylparaben 2.70
BHA (internal standard) 2.84
Benzylparaben 3.59
BHT 5.37
Tocopherol acetate 6.11
Time (min)
Inte
nsi
ty (
cps)
BuP
BzP
BHT
6.11
Toco
PrP
EtP
MeP
8.0e4
7.5e4
7.0e4
6.5e4
6.0e4
5.5e4
5.0e4
4.5e4
4.0e4
3.5e4
3.0e7
2.5e4
2.0e4
1.5e4
1.0e4
5000.0
0.0
8.5e4
0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5
Figure 4: Chromatogram of standard preservative mixture (methylparaben = MeP; ethylparaben = EtP; propylparaben = PrP; butylparaben = BuP; benzylparaben = BzP; butylated hydroxytoluene = BHT; tocopherol acetate = Toco).
APRIL 2015 Recent Developments in Hplc anD UHplc 21www.chromatographyonline.com
It was noticed that some of the prod-
ucts analyzed contained peaks belonging
to preservatives that were not listed on the
product label ingredient list. For example,
in the foundation sample (Figure 7) the
chromatogram shows peaks consistent
with methylparaben, ethylparaben, and
propylparaben; however, these preserva-
tives were not listed on the ingredient
list of the product label. The analysis of
the hand lotion sample also resulted in
an ethylparaben peak, but ethylparaben
is not listed on the product label ingredi-
ent list. Similarly, the toothpaste sample
contained methylparaben and ethylpara-
ben peaks yet they were not listed on the
product ingredient list. Unfortunately, the
threshold values are unclear for preserva-
tives in cosmetics and personal care prod-
ucts sold in the United States. Because of
this, the FDA may not require companies
to list certain preservatives if they fall
below a certain cutoff value. However,
the European Union has a set maximum
concentration of preservatives allowed in
cosmetics, as follows: 0.4% one single
ester, 0.8% ester mixtures of parabens,
0.5% benzoic-salicylic acid, 0.6% sorbic
acid, and 1.0% phenoxyethanol (15).
Conclusion
An LC–ESI-MS-MS method has been
developed to determine multiple pre-
servatives in cosmetic and personal care
products. The sample preparation is short
and simple and when combined with the
optimal chromatographic conditions, the
method allows for a quick analysis time.
In under 8 min, the developed method is
capable of separating and identifying eight
preservatives (including five parabens) in a
100-mg sample of cosmetic and personal
care product with an LOD ranging from
0.91 to 4.19 µg/mL and an LOQ ranging
from 3.03 to 14.00 µg/mL. Compared
to other literary references, this method
combines a simple and cheap sample
preparation procedure along with a short
analysis time while providing similar if not
improved separation and sensitivity.
Acknowledgments
This research was supported by the Foren-
sic Science Program in the Chemical and
Physical Sciences Department of Cedar
Crest College and the 2014 Carol DeFor-
est Research Grant, Northeastern Associa-
tion of Forensic Scientists.
Time (min)
Inte
nsi
ty (
cps)
5180
5000
4800
4600
4400
4200
4000
3800
3600
3400
3200
3000
2800
2400
2200
2000
1800
1600
1400
1200
1000
800
600
400
200
00.5 1.5 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0
6.22
6.5 7.0
MP
EP
BHA(internal standard)
Figure 6: Chromatogram of toothpaste sample. Preservative peaks (left to right): methyl-paraben, ethylparaben, and BHA (internal standard).
Table V: Product analysis
Compound Concentration of Preservative in Sample (% [w/w])
Product Tocopherol EtP MeP BHT PrP BuP BzP
Deodorant 0.00 0.35 1.60 0.07 0.00 0.00 0.00
Foundation (F1) 0.06 0.04 0.00 0.00 0.00 0.00 0.00
Foundation (F4) 0.01 1.04 0.55 0.01 0.51 0.00 0.00
Toothpaste 0.00 0.04 0.14 0.02 0.00 0.00 0.00
Hand sanitizer 0.02 0.00 0.00 0.02 0.00 0.00 0.00
Lipstick 0.03 0.00 0.03 0.06 0.00 0.00 0.00
Hand lotion 0.00 0.03 0.05 0.02 0.00 0.00 0.00
Table IV: Figures of merit determined from calibration curves
Compound IonEquation for Regression
R2 LOD (µg/mL)
LOQ (µg/mL)
LDR (µg/mL)
Butyl 139 y = 0.3499x + 0.3565 0.9993 1.37 4.56 4.56–100
Butyl 95 y = 0.1625x + 0.1932 0.9988 1.84 6.15 6.15–100
Benzyl 91 y = 0.3417x + 0.6639 0.9975 2.69 8.96 8.96–100
Benzyl 65 y = 0.06x + 0.1105 0.9972 2.84 9.45 9.45–100
Propyl 139 y = 0.2983x + 0.088 0.9995 1.17 3.91 3.91–100
Propyl 95 y = 0.1584x + 0.0877 0.9995 1.14 3.79 3.79–100
Ethyl 139 y = 0.1999x + 0.1586 0.9995 1.17 3.89 3.89–100
Ethyl 95 y = 0.138x + 0.1674 0.9985 2.06 6.87 6.87–100
Methyl 121 y = 0.0488x + 0.061 0.9986 1.99 6.65 6.65–100
Methyl 65 y = 0.0193x + 0.0.0447 0.9977 2.55 8.50 8.50–100
BHT 205 y = 0.0053x + 0.0024 0.9943 4.02 13.40 13.40–100
BHT 145 y = 0.0014x + 0.0137 0.9939 4.19 14.00 14.00–100
Toco 207 y = 0.3161x + 0.5548 0.9997 0.91 3.03 3.03–100
Toco 165 y = 0.215x + 0.4146 0.9995 1.21 4.02 4.02–100
22 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
References
(1) http://www.cosmeticsinfo.org/HBI/6 (last
accessed January 8, 2014).
(2) M. Soni, I. Carabin, and G. Burdock, Food
Chem. Toxicol. 43, 985 (2005).
(3) I Branowska, I. Wojciechowska, N. Solarz, and
E. Krutysza, J. Chromatogr. Sci. 52, 88–94 (2014).
(4) Q. Zhang, M. Lian, L. Liu, and H. Cui,
Anal. Chim. Acta 537, 31–39 (2005).
(5) J. Byford, L. Shaw, M. Drew, G. Pope, M.
Sauer, and P. Darbre, J. Steroid Biochem.
Mol. Biol. 80, 49 (2002).
(6) P. Darbre, J. Byford, L. Shaw, R. Horton, G. Pope,
and M. Sauer, J. Appl. Toxicol. 22, 219 (2002).
(7) P. Darbre, J. Byford, L.Shaw, S. Hall, N.
Coldham, and M. Sauer, J. Appl. Toxicol.
23, 43 (2003).
(8) P. Darebre, A. Aljarrah, W. Miller, N. Cold-
ham, M. Sauer, and G. Pope, J. Appl. Toxi-
col. 24, 5 (2004).
(9) S. Oishi, Toxicol . Ind. Health 17, 31
(2001).
(10) S. Oishi, Arch. Toxicol. 76, 423 (2002).
(11) D. Oishi, Food Chem. Toxicol. 40, 1807
(2002).
(12) X.Q. Li et al., Anal. Chim. Acta 608, 165–
177 (2008).
(13) http://www.truthinaging.com/ingredients/
ethylparaben-2 (last accessed January 6,
2014).
(14) P. Perez-Lozano, E. Garcia-Montoya, A.
Orriols, M. Minarro, J.R. Tico, and J.M.
Sune Negre, J. of Pharmaceutical and
Biomed. Anal. 39, 920–927 (2005).
(15) A. Aoyama, T. Doi, T. Tagami, and
K.J. Kajimura, Chromatogr. Sci. 51, 1–6
(2013).
(16) T. Wu, C. Wang, X. Wang, and Q. Ma, J.
Cosmetic Sci. 30, 367–372 (2008).
(17) M. Pedrouzo, F. Borrull R.M. Marce, and
E. Pocurull, J. Chromatogr. A 1216, 6994–
7000, (2009).
(18) A.M.C. Ferreira, M. Moder, and M.E.F.
Laepada, J. Chromatogr. A 1218, 3837–
3844 (2011).
(19) M. Abbasghorbani, A. Attaran, and M.
Payehghadr, J. Sep. Sci. 36, 311–319
(2013).
(20) H. Wei, J. Yang, H. Zhang, and Y. Shi, J.
Sep Sci. 37, 2349–2356 (2014).
(21) G. Alvarez-Rivera, M. Vila, M. Lores, C.
Garcia-Jares, and M. Llompart, J. Chro-
matogr. A 1339, 13–25 (2014).
(22) F. Han, Y.Z He, and C.Z. Yu, Talanta 74,
1371–1377 (2008).
Emily A. Myers, Thomas H. Pritchett, and Thomas A. Brettell are with the Forensic Science Program in the Department of Chemistry and Physical Sciences at Cedar Crest College in Allentown, Pennsylvania. Direct correspondence to: [email protected] ◾
BzP
BuP
PrP
BHT
MeP
EtP
Tocopherol
Co
nce
ntr
ati
on
(%
w/w
)
2.50%
2.00%
1.50%
1.00%
0.50%
0.00%
Deo
dorant
Foundat
ion (F
1)
Foundat
ion (F
4)
Tooth
paste
Han
d saniti
zer
Lipst
ick
Han
d lotio
n
Figure 8: Relative quantities of preservatives in cosmetic and personal care products analyzed.
MP
PP
EP
BHA(internal standard)
Time (min)
0.5 1.5 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0
6.21 6.55 6.74
6.5 7.0
Inte
nsi
ty (
cps)
7.0e4
6.5e4
6.0e4
5.5e4
5.0e4
4.5e4
4.0e4
3.5e4
3.0e4
2.5e4
2.0e4
1.5e4
1.0e4
5000.0
0.0
Figure 7: Chromatogram of foundation sample (F4). Preservative peaks (left to right): methylparaben, ethylparaben, propylparaben, and BHA (internal standard).
For more information on this topic,
please visit
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Cadenza CD-C18HT Outperforms UPLC Columns
Our fully optimized 3µ Cadenza CD-C18HT columns outperform UPLC columns in both
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water / acetonitrile / acetic acid = 60 / 40 / 0.1
37 deg.C, 260 nm, 1 uL ( 0.02- 0.16ug)
1 2 3
4
1
23
4
1
23
4
1.7um ODS, 100 x 4.6 mm3um Cadenza CD-C18 HT, 150 x 4.6 mm
mA
U
0 5 10 min
0
50
100
0
5000
10000
15000
20000
25000
0.4 0.9 1.4 1.9 2.4
Flow Rate, mL/min
Pla
te C
ount, N
( 3)
0.0
0.5
1.0
1.5
2.0
2.5
0.4 0.9 1.4 1.9 2.4
Flow Rate, mL/min
Resolu
tion, R
s(3
/2)
O
COCH2CH2CH2CH3HO
COCHHO
O
CH3
CH3HO
O
COCH2CH2CH3
O
HN
NH
O
150
butylparaben
isopropylparaben propylparabenuracil
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
0.4 0.9 1.4 1.9 2.4
Flow Rate, mL/min
Pre
ssure
(P
, M
Pa)
Pressure
Plate Count
Resolution
1.7um ODS
100 x 4.6 mm
1 mL/min
3um Cadenza CD-C18 HT
150 x 4.6 mm
1.5 mL/min
Rs(3/2) = 2.0
N(3) = 22000
P = 13 MPa
Rs(3/2) = 1.8
N(3) = 18600
P = 18 MPa
24 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
Vis
cosi
ty (
cP)
0.6
0.5
0.4
0.3
0.1
0
0.2
0 0.2 0.4 0.6 0.8 1
Carbon dioxide mole fraction
Susan V. Olesik
Enhanced-Fluidity Liquid Chromatography: Connecting the Dots Between Supercritical Fluid Chromatography, Conventional Subcritical Fluid Chromatography, and HPLC
Enhanced-fluidity liquids are organic solvents or organic–aqueous
solvents mixed with high proportions of liquefied gases, such as
carbon dioxide. These subcritical solvents share the positive attributes
of supercritical fluids (fast diffusion rates and low viscosities) and the
positive attributes of commonly used liquids (high solvent strength).
These solvent properties provide enhanced efficiency for reversed-
phase, conventional normal-phase, hydrophilic-interaction, and size-
exclusion chromatography. The capabilities of enhanced-fluidity liquid
chromatography for highly polar compounds is described and the value of
using the entire continuum of 0–100% carbon dioxide solvent systems is
discussed in terms of changes in mobile-phase properties and applications.
Enhanced-f luidity liquids (EFL)
are mixtures of conventional
l iquids to which dissolved
gases, such as carbon dioxide, are
added. Our group coined this term
in 1991 to explain the fact that these
solvents possess f luidity (inverse of
viscosity) that is markedly higher
than typical liquids (1). This was at
a time when supercritical f luid chro-
matography (SFC) was gaining inter-
est. These mixtures are described as
gas expanded liquids (GXLs) in the
chemical engineering literature (2),
but both terms are merely descriptive
of the physical phenomena involved
in producing the mixture. The addi-
tion of a liquefied gas to a conven-
tional liquid causes considerable vol-
ume expansion of the mixture, and
the f luidity of mixture increases sub-
stantially. Today, much of the work
in SFC is actually performed under
subcritical f luid conditions, meaning
the separations are being performed
below the critical point of the solvent.
Enhanced-f luidity liquids are indeed
subcritical solvents, but enhanced-f lu-
idity liquid chromatography (EFLC)
uses a smaller proportion of liquefied
gas in the mobile phase than in typi-
cal subcritical f luid chromatography,
which is 0Ð50% organic modifier. In
EFLC, conditions from 100% to 50%
conventional liquid combined with a
liquefied gas are used in the mixtures.
Therefore, by combining conventional
subcritical f luid chromatography with
EFLC, the entire solvent range of
0Ð100% organic solvent is spanned.
This solvent range is highly useful for
chromatographic applications. Like
in SFC, EFLC typically uses carbon
dioxide as the liquefied gas, but other
liquefied gases have also been evalu-
ated, such as f luoroform (3,4).
Optimization of
Chromatography
In high performance liquid chroma-
tography (HPLC), the fastest separa-
tions are achieved when working at
Automatic extraction of target compounds from up to 48 solid samples with seamless transfer to SFC/MS provides:
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between automated sample preparation and
chromatographic analysis using a supercritical
mobile phase. Eliminating the need for
complicated sample preparation while offering
a wide range of separation modes, the
unique Nexera UC enables the analysis of a
wide range of compounds with outstanding
reliability and sensitivity.
■ Very fast separation speed due to the relatively low viscosity of supercritical fluid
■ Improved peak capacity and chromatographic resolution compared to standard LC
■ Enhanced separation of analogues and/or chiral compounds by high-penetration mobile phase
■ High sensitivity by utilizing different separation modes
■ Splitless introduction into MS detector for additional sensitivity
■ Less environmental impact and lower operating cost by reducing the amount of organic solvent required
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26 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
the highest possible pressure of the
chromatographic instrument. Using
reduced (dimensionless) plate height,
h, and reduced velocity, ν, as defined
in equations 1 and 2, the Knox-Sal-
eem equation (equation 3) illustrates a
linear relationship between retention
separation time, to, and viscosity,
h = H/dp [1]
ν = udp/Dm [2]
to = Φh2
minN2
reqη/ΔP2
[3]
N/tR = Dm/d2
p(ν/h)(1/1 + k) [4]
where H is plate height, u is linear
velocity, dp is the particle size of the
packing, Dm is the diffusion coef-
f icient of the analyte, Nreq is the
required chromatographic eff iciency
for a given separation, to is the reten-
tion time (seconds), Φ is the dimen-
sionless f low resistance parameter, η
is the viscosity of the mobile phase,
ΔP is the pressure drop across the
column, and tR is the retention time
(5). Equation 3 assumes an optimized
chromatographic system in terms
of column length, particle size, and
f low rate. Assuming maintenance
of operating conditions near these
conditions, a substantial decrease in
time of analysis is observed by lower-
ing the viscosity of the mobile phase.
Finally, Guiochon and others illus-
trated that the separation power, N/
tR (6,7) can be increased by increasing
the mobile-phase diffusion coefficient
assuming the other parameters do not
vary much and the entire separation is
functioning at the optimum reduced
velocity where k is the retention factor.
N/tR = Dm/d2
p(ν/h)(1/1 + k) [4]
Properties of EFL Mixtures
Solvent Strength and
Dielectric Constant
An interesting attribute of enhanced-
f luidity liquid mixtures is that as much
as 60 wt% liquefied gas can be added
before considerable loss of solvent
strength occurs (1,4,8). Mixtures of
alcohols and carbon dioxide are robust
in their solvent strength, particularly
methanol–carbon dioxide mixtures.
Aida and Inomato (9) studied the
molecular structure of methanol-car-
bon dioxide mixtures using molecular
dynamics (MD) simulations. Their
study illustrated that up to 50 wt% car-
bon dioxide can be added to methanol
before impacting the hydrogen bond
(H-bond) network. However, below
1.00 0.65
0.55
0.45
0.35
0.25
0.15
0.80
0.60
0.40
0.20
0.000.00 0.20 0.40 0.60 0.80 1.00
Carbon dioxide mole fraction
∏*, α
β
20 40 60 80 100 120 140
Temperature (oC)
D1
2 (
cm2/s
)
0.25
0.3
0.4
0.25
0.2
0
0.20
0.15
0.05
0.00
Mole fraction
carbon dioxide
Figure 1: Variation of Kamlet-Taft solvatochromic parameters for methanol–water–carbon dioxide mixtures as a function of added carbon dioxide with the mole ratio of methanol–water held at 2.3 at 25 °C and 172 bar (⦁ = A, ♦ =E, ◾ = π*). Data adapted from reference 11.
Figure 2: Variation of the diffusion coefficient of benzene at 138 bar in 0.70:0.30 methanol–water (+), 0.56:0.24:0.20 (▲), 0.52:0.23:0.25 (⦁), 0.49:0.21:0.30 (♦), 0.42:0.18:0.40 (◾) methanol–water–carbon dioxide. Data adapted from reference 13.
APRIL 2015 aDvances in Hplc sYstems tecHnoloGY 27www.chromatographyonline.com
that percentage the H-bond network
degraded. Their data and the solvent
strength measurements correlate well.
The dielectric constant of methanol-
carbon dioxide mixtures (50 °C and
110 bar) decrease linearly with added
carbon dioxide until 0.45 mole fraction
methanol is added. Further addition of
carbon dioxide to methanol decreases
the dielectric constant, but at a slower
rate. The dielectric constant with 0.60
mole fraction methanol was nearly half
that of pure methanol (10).
Figure 1 shows the variation of sol-
vent strength when carbon dioxide
is added to a 0.70:0.30 mole ratio
methanol-water mixture at 25 °C and
172 bar (11). Similarly, carbon dioxide
can be added to other solvent systems
with minimal loss in solvent strength.
However, the unique attribute of these
data is that the hydrogen bond basic-
ity of the ternary mixtures appears to
increase with added carbon dioxide.
Buffers
When high proportions of carbon
dioxide are added to liquids, the sol-
vents become weakly acidic unless
other additives are included to con-
trol the pH. Buffers can be readily
produced in these mixtures. We pre-
viously illustrated that buffers could
be produced in methanol–water–car-
bon dioxide mixtures with pH values
from 2.2 to 6.8 (12). The addition of
carbon dioxide to methanol–water
mixtures with a mole ratio of 69:31
produces a buffer with pH varying
from 4.54 to 4.73 depending on the
proportion of carbon dioxide added.
The formation of carbonic acid and
the presence of dissolved carbon
dioxide provides the buffering com-
ponents of this system. This buffer
is very interesting because nonvola-
tile buffer additives are not neces-
sary. The other interesting aspect of
this study was that for the metha-
nol–water–carbon dioxide mixtures
studied, increasing the pressure from
120 to 207 bar did not significantly
impact the measured pH.
Diffusion Coefficients
Chromatographic band dispersion in
liquid chromatography is typically
highly inf luenced by the resistance
to mass transfer between the mobile
phase and the stationary phase, which
is inversely proportional to the diffu-
sion coefficient of the mobile phase.
Therefore, for low band dispersion,
high diffusion coefficients are desired.
Diffusion coefficients of solutes in a
number of enhanced f luidity liquids
were measured. For the methanol–
carbon dioxide mixtures at 25 °C and
172 bar, the diffusion coeff icient of
benzene increases by approximately
75% by adding carbon dioxide up to
50 mol% (1). With increasing carbon
dioxide above 50 mol% the diffusion
coefficients increase at a faster rate up
to that of pure carbon dioxide.
The variation of solute diffusion
coeff icients in methanol–water–car-
bon dioxide mixtures are also nonideal
(13). Temperatures in excess of 60 °C
were needed to increase the diffusion
coeff icient of benzene to the same
value as the addition of 0.30 mole frac-
tion carbon dioxide (Figure 2). How-
ever, by increasing the temperature and
adding carbon dioxide to this metha-
nol–water mixture, the greatest benefit
was observed. For a 0.70:0.30 mole
ratio methanol–water mixture, the
addition of 0.30 mole fraction carbon
dioxide and an increase in temperature
to 58 °C caused a ninefold increase in
the diffusion coefficient of benzene.
Viscosity
Foster’s group studied the change in
viscosity in both methanol–carbon
dioxide and ethanol–carbon dioxide
mixtures. For methanol–carbon diox-
ide mixtures for pressures ranging
from 12 bar to 78 bar and tempera-
tures varying from 25 °C to 40 °C, the
viscosity of the EFL decreased linearly
to approximately 50% of the original
viscosity from 0 to 50 mol% carbon
dioxide (14). The viscosity continued
to decrease with further addition of
carbon dioxide, but not at the same
rate. This change occurred at 50 mol%
carbon dioxide for the entire tempera-
ture range. Ethanol–carbon dioxide
mixtures were different; the viscosity
decreased substantially with added
carbon dioxide (15). However, the
composition where the rate of change
slowed varied with temperature. At
25 °C the reduction was linear up to
0.70 mole fraction carbon dioxide. For
30 °C, 35 °C, and 40 °C the rate of
viscosity reduction slowed at 0.60, 0.45,
and 0.25 mole fraction carbon dioxide,
respectively. These data clearly show
that the addition of carbon dioxide to
conventional solvents will substantially
impact the separation time.
Instrumentation
The instrumentation necessary to accom-
plish enhanced-fluidity chromatography
Vis
cosi
ty (
cP)
0.6
0.5
0.4
0.3
0.1
0
0.2
0 0.2 0.4 0.6 0.8 1
Carbon dioxide mole fraction
Figure 3: Variation of viscosity of a methanol–carbon dioxide mixture as a func-tion of added carbon dioxide at 25 °C (red curve, pressure increased from 0 bar to 56.7 bar with increasing carbon dioxide) and 40 °C (blue curve, pressure increased from 1 bar to 76.7 bar with increasing carbon dioxide). Data adapted from reference 14.
28 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
is the same as that used in SFC with
the condition that the software must
allow use of more than 50% modifier.
Alternatively, a conventional HPLC
system can be used to deliver the
organic solvents and a carbon diox-
ide compatible pump and mixer can
be added at the outlet of the HPLC
pump to allow for the use of carbon
dioxide in the mobile phase. With this
setup, a restrictor (small diameter tub-
ing) must be added at the exit of the
detector to control the pressure and
f low rate of the mobile phase. For
example, Sandra (16) used an Agilent
1200 HPLC system combined with
a separate carbon dioxide pump and
mixer at the outlet of the Agilent 1200
HPLC pumps. A stainless steel f low
restrictor (4 m × 0.12 mm i.d.) and a
needle valve were placed at the detec-
tor outlet to control the f low.
Commercial SFC instrumentation
can be used under subcritical condi-
tions all the way to EFLC conditions
as long as the pressure limit of the
instrument or the software for the
solvent programming doesn’t limit
the mobile-phase conditions. (Note:
These instruments use back-pressure
regulators to control f low instead
of f ixed restrictors, as an example,
an Agilent 1260 system can be used
without modification for EFLC sepa-
rations.)
Previous EFLC and a Range of
Chromatographic Mechanisms
EFLC has been used effectively for
reversed-phase, normal-phase, chiral,
and size-exclusion modes of chroma-
tography (17). In reversed-phase chro-
matography previous work has shown
the separation time can be reduced by
nearly half by adding carbon dioxide.
Using normal-phase conditions for
gradient polymer elution chromatog-
raphy, Kawai also showed that the use
of carbon dioxide in the mobile phase
provided the highest resolution for
poly(styrene-co-methyl acrylate) mix-
tures compared to the use of conven-
tional liquids (30). In addition, chiral
separations are typically faster and
more efficient than in HPLC or SFC
(17). As summarized by Guiochon
and Tarafder (18), higher mobile-
phase velocities, longer columns, and
finer particles can be used with EFLC
compared to HPLC with conventional
solvents. These attributes are shared
with high-temperature HPLC and
ultrahigh-pressure liquid chromatog-
raphy (UHPLC). The higher diffusion
coeff icients cause higher optimum
mobile-phase velocities compared to
HPLC and lower resistance to mass
transfer, which increases the overall
efficiency.
Separation of Polar
Compounds — Subcritical
Conditions Including
EFLC Conditions
There continues to be considerable
interest in providing fast and efficient
separations for highly polar com-
pounds. Taylor and coworkers (19)
have been studying the use of subcriti-
cal chromatography for the separation
of polar compounds with encouraging
results. For example, Zheng and col-
leagues (19) described the separation
of polypeptides up to 40-mers using a
2-ethylpyridine bonded silica station-
ary phase and carbon dioxide–metha-
nol mobile phases with trif luoroacetic
acid as an additive in the methanol
to suppress the deprotonation of car-
boxylic acid groups and protonate
the peptide amino acid groups on the
protein. A 5–50% methanol gradient
was used. Electrospray mass spectra
with high signal-to-noise ratios were
obtained with this technique and a
lower separation time was achieved as
well when comparing the optimized
protein separations under SFC and
HPLC conditions. Ashraf-Khorassani
and Taylor (20) also showed that alco-
hol–carbon dioxide mixtures with up
to 5% water using gradient conditions
Nu
mb
er
of
pla
tes/
m
Nu
mb
er
of
pla
tes/
m
AMP UMP CMP GMP ADP UDP CDP GDP
AMP UMP CMP GMP ADP UDP CDP
12,000 2500
2000
1500
1000
500
0
10,000
8000
6000
4000
2000
10,000
9000
1200
1000
800
600
400
200
0
8000
7000
6000
5000
4000
3000
2000
1000
0
0
Figure 4: Effect of different bases on the effciency of the nucleotides: (a) in LC and (b) with 0.1 mole fraction carbon dioxide added. Conditions: 5 mM of each base was added to a 75 mM ammonium phosphate solution, which was used to prepare the 90:10 (v/v) methanol–aqueous mobile phase. The y-axis on the left corresponds to the effciency values for the monophosphate compounds, the axis on the right corresponds to the values for the diphosphate compounds. No base (◾), TEA (◾), DABCO (◾), and DBN (◾). Data adapted from reference 24.
APRIL 2015 aDvances in Hplc sYstems tecHnoloGY 29www.chromatographyonline.com
up to 50% alcohol were effective in
separating the nucleobases, thymine,
uracil, adenine, and cytosine.
Guillarme and coworkers (21) illus-
trated the value of subcritical f luid
chromatography using a methanol–
carbon dioxide mixture with 2–40%
methanol at 40 °C and 150 bar with
a 2-ethylpyridine column (100 mm
× 3.0 mm, 1.7-µm dp Acquity UPC2
BEH-2-EP, Waters) or an Acquity
BEH Shield RP18 hybrid column (50
mm× 2.1 mm, 1.7-µm dp, Waters)
using 20 mM ammonium hydrox-
ide in the mobile phase at a f low
rate of 1.5 mL/min for the separa-
tion of highly polar compounds such
as nucleobases and carbohydrates. A
comparison of column types showed
that gradient subcritical f luid chroma-
tography could separate well at least
70% of the compounds studied with
enhanced mass spectral sensitivity.
For chiral separations, Armstrong
(22) evaluated subcritical conditions
for chiral separations using macrocy-
clic glycopeptides. For the separation
of polar analytes such as native amino
acids using macrocyclic glycopeptides
stationary phases, a combination of
both acidic and basic modifiers and
subcritical conditions with 48% to
nearly 70% methanol were quite effec-
tive in providing excellent separations.
Sandra’s group (16) was the f irst
to study the possibility of using
EFLC conditions for hydrophilic-
interaction chromatography (HILIC).
In this study, using a silica column
(250 mm× 4.6 mm, 5-µm dp Zor-
bax Rx—SIL, Agilent Technologies)
the five nucleobases, thymine, uracil,
cytosine, guanine, and adenine were
separated using 95:5 (v/v) ethanol–20
mM ammonium formate buffer at pH
3.0 combined with carbon dioxide.
Increasing amounts of carbon diox-
ide increased the elution window and
the separations were similar to those
obtaining using acetonitrile–water
mobile phases. Plate counts of 16,200
and 19,000 were obtained for 3 mL/
min and 0.9 mL/min conditions.
Our group studied EFLC-HILIC
separation of RNA nucleosides (ade-
nosine [A], uridine [U], cytidine
[C], and guanosine [G]) using EFLC
mobile phases under isocratic condi-
tions (23). Using a 150 mm × 4.6
mm, 3-µm dp Tosoh amide column
and a 90:10 methanol–20 mM acetate
buffer mobile phase, the addition of
increasing proportions of carbon diox-
ide caused increased retention with a
slight increase in band dispersion for
the chromatographic bands. For exam-
ple, the addition of 0.2 mole fraction
carbon dioxide causes changes in the
retention factor for A, C, U, and G of
72%, 66%, 97%, and 138%, respec-
tively. With 20 mol% carbon dioxide,
a separation time of 15 min was pos-
sible with resolution values >4 for all
pairs. Alternatively, under optimized
HPLC conditions with the same col-
umn using a 90:10 acetonitrile–20
mM acetate buffer, a complete sepa-
ration was achieved in approximately
50 min.
To attempt separations of even more
polar compounds, the separation of
mono-, di-, and triphosphorylated
nucleosides were studied (24). These
compounds are typically separated
using aff inity chromatography, ion-
exchange, or electrophoresis (25–27).
A 150 mm × 4.6 mm, 3.5-µm dp
Waters X-bridge amide column was
used with 90:10 methanol–aqueous
mobile phases buffered with ammo-
nium phosphate. Often, phosphory-
lated compounds have poor peak
shapes because of strong tailing in
a broad range of chromatographic
retention mechanisms using silica as a
support. Phosphorylated compounds
are strong hydrogen bond bases that
interact with free silanols on a silica
column through very strong hydrogen
bonding interactions (28). The slow
kinetics of desorption are the likely
cause of the peak asymmetry. Strong
bases such as triethylamine (TEA)
are often added to the mobile phase
to compete with the interactions with
the free silanols (29). Two bases that
are widely used in organic synthesis
and described as superbases because of
their strong basicity in both aqueous
and organic solvents were also consid-
ered and compared to TEA: 1,4-diaz-
abicyclo [2.2.2] octane (DABCO) and
1,5- diazabicyclo [4.3.0] non-5-ene
(DBN).
Figure 4 compares the eff iciency
and the peak asymmetry for the
Time (min)
(a)
(b)
(c)
(d)
5+1
4+6
4+5
7+6+3
2 4
4
6
6
5
5
2
2
1
1
1
3
3
32
6
8
7
7
7
8
8
3.5 5.5 7.5 9.5 11.5 13.5 15.5 17.5 19.5 21.5
8
Figure 5: Separation of various nucleosides and nucleotides: (a) LC, (b) 0.15 mole fraction of carbon dioxide, (c) 0.20 mole fraction of carbon dioxide, and (d) 0.25 mole fraction of carbon dioxide. Mobile phase: 90:10 methanol–75 mM ammonium phosphate + 5 mM DBN. Peaks: 1 = adenosine, 2 = cytidine, 3 = uri-dine, 4 = guanosine, 5 = AMP, 6 = CMP, 7 = UMP, 8 = GMP. Data adapted from reference 24.
30 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
mono- and diphosphorylated nucleo-
sides obtained with TEA, DABCO,
and DBN in a mobile phase that con-
tained ammonium dihydrogen phos-
phate buffer under LC conditions
(Figure 4a) and with the addition
of 0.1 mole fraction carbon dioxide
to the mobile phase with a mobile-
phase velocity of 1 mL/min. When
compared to the data where no base
was added, DBN provides the best
results with a 12% to 18% increase
in eff iciency in LC for monophos-
phate nucleotides and 111% to 320%
for the diphosphates. In EFLC, the
eff iciency increased from 9% to 39%
for monophosphates, and from 67%
to 115% for diphosphates. For both
HPLC and EFLC, tailing was the
major contributor to low eff iciency
for the phosphorylated compounds;
the impact of base addition on the
asymmetry of the peak was studied
to better understand the impact of
each base on eff iciency. DBN pro-
vided both the greatest decrease in
peak asymmetry and increase in eff i-
ciency, followed by DABCO. Both
bases great ly improved the peak
shape while marginally affecting the
retention of the analytes; no signif i-
cant decrease in k was observed in
EFLC, and an average 10% decrease
in k was observed in LC. TEA either
increased the peak asymmetry or did
not impact it significantly.
Similar to other HILIC separations
of polar compounds, the addition of
a salt to the mobile phase was quite
important. Sodium chloride (0.02
M) was used to assist the formation
of the adsorbed water phase, and 75
mM ammonium phosphate was used
to decrease the retention of the phos-
phate groups. Figure 5 shows that
carbon dioxide expands the elution
window for the compounds.
Summary
Now that SFC chromatographic
instruments have a much larger range
of operating pressures with accompa-
nying precise temperature control,
it is time to consider using lique-
fied gases such as carbon dioxide in
mobile phases for a broader range of
chromatographies. The lower viscos-
ity of mobile phase and increased
dif fusivity for analyte separations
using 0–100% liquefied gas provides
decreased analysis time and often
improved eff iciency. The entire range
of this solvent continuum is valuable
for separation science. A continuous
change in viscosity, solvent strength,
diffusivity, and permittivity occurs
across this range of mobile-phase
compositions. In particular, EFLC
mobile phases are a lso providing
value for the separation of highly
polar compounds with similar oper-
ating parameters as in conventional
HPLC. While advantages in perfor-
mance are often noted when using
acetonitrile–water for reversed-phase
HPLC and HILIC compared to alco-
hol–water mixtures, the addition of
carbon dioxide to the alcohol–water
mixtures improves the chromato-
graphic performance signif icantly.
A lso, both a lcohol–carbon dioxide
and a lcohol–water–carbon dioxide
are environmentally friendly.
References
(1) Y. Cui and S.V. Olesik, Anal. Chem. 63,
1813–1819 (1991).
(2) C.J. Chang and A.D. Randolph, AIChE J.
36, 939–942 (1990).
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1595–1603 (1998).
(4) J. Zhao and S.V. Olesik, J. Chromatogr. A
923, 107–117 (2001).
(5) H. Chen and Cs. Horváth, J. Chromatogr.
A 705, 3–20 (1995).
(6) G. Guiochon, Optimization in Liquid
Chromatography in High Performance
Liquid Chromatography: Advances and
Perspectives, Vol . 2, C. Horvath, Ed.
(Academic Press, New York, 1980), pp.
1–56.
(7) F. Erni, J. Chromatogr. 282, 371–382
(1983).
(8) H. Yuan and S.V. Olesik, J. Chromatogr.
Sci. 35, 409–416 (1997).
(9) T. Aida and H. Inomata, Mol. Simulat.
30, 407–412( 2004).
(10) S.B. Lee, R.L. Smith, H. Inomata, and
K. Arai, Rev. Sci. Instr. 72, 4226–4230
(2000).
(11) Y. Cui and S.V. Olesik, J. Chromatogr. A
691, 151–162 (1995).
(12) D. Wen and S.V. Olesik, Anal. Chem. 72,
475–480 (2000).
(13) S.T. Lee and S.V. Olesik, Anal. Chem. 66,
4498–4506 (1994).
(14) R. Sih, F. Dehghani, and N.R. Foster, J.
Supercrit. Fluids 41, 148–157 (2007).
(15) R. Sih, M. Armenti, R. Mammucari, F.
Dehghani, and N.R. Foster, J. Supercrit.
Fluids 43, 460–468 (2008).
(16) A. dos Santos Pereira, AJ. Girón, E.
Admasu, and P. Sandra, J. Sep. Sci. 33,
834–837 (2010).
(17) S.V. Olesik, Adv. Chromatogr. 46, 424–
449 (2008).
(18) G. Guiochon, and A. Tarafder, J. Chro-
matogr. A 1218, 1037–1114 (2011).
(19) J. Zheng, J.D. Pinkston, P.H. Zouten-
dam and L.T. Taylor, Anal. Chem. 78,
1535–1545 (2006).
(20) M. Ashraf-Khorassani and L. Taylor, J.
Sep. Sci. 33, 1682–1690 (2010).
(21) A. Periat, A. Grand-Guillaume, and D.
Guillarme, J. Sep. Sci. 36, 3141–3151
(2013).
(22) Y. Liu, A. Berthod, C.R. Mitchell, T.L.
Xiao, B. Zhang, and D. Armstrong, J.
Chromatogr. A 978, 185–204 (2002).
(23) J.W. Treadway, G.S. Philibert, and S.V.
Olesik, J. Chromatogr. A 1218, 5897–
5902 (2011).
(24) G. Philibert and S.V. Olesik, J. Chro-
matogr. A 1218, 8222–8230 (2011).
(25) M. Hossel, M.G. Corneliu, J. vom
Brocke, and H.H. Schmeiser, Electropho-
resis 31, 299–302 (2010).
(26) N.J. Alves, S.D. Stimple, M.W. Hand-
logten, and J.D. Ashley, Anal. Chem. 84,
7721–7728 (2012).
(27) N. Tomiya, E. Ailor, S.M. Lawrence,
M.J. Betenbaugh, and Y.C. Lee, Anal.
Biochem. 293, 129–137 (2001).
(28) E.D. Davis, W.O. Gordon, A.R. Wilms-
meyer, D. Troya, and J.R. Morris, J. Phys.
Chem. Lett. 5, 1393–1399 (2014).
(29) D.V. McCalley, Adv. Chromatogr. 46,
305–350 (2008).
(30) E. Kawai, K. Shimoyama, K. Ogino, and
H. Sato, J. Chromatogr. A 991, 197–203
(2003).
Susan V. Olesik is the Dow
Professor and Chair in the Department
of Chemistry and Biochemistry at
Ohio State University in Columbus,
Ohio. Direct correspondence
to: [email protected] ◾
For more information on this topic,
please visit
www.chromatographyonline.com
APRIL 2015 Recent Developments in Hplc anD UHplc 31www.chromatographyonline.com
William J. Long, Anne E. Mack, Xiaoli Wang, and William E. Barber
Selectivity and Sensitivity Improvements for Ionizable Analytes Using High-pH-Stable Superficially Porous Particles
The most significant recent advancement in liquid chromatography
(LC) column technology is the new generation of superficially
porous silica particles. While chromatographers enjoy the
ultrahigh efficiency of these particles, they also desire more
selectivity options to facilitate method development. These
can be achieved with different bonded phases and different pH
mobile phases. However, the latter requires particles that can
withstand extremes in pH. Here, we report a novel approach
to enhancing the selectivity of ionizable compounds using
superficially porous particles that are stable in a wider pH range.
High performance liquid chro-
matography (HPLC) method
development for chemical and
pharmaceutica l ana lysis is a cha l-
lenging task. It involves screening a
range of chromatographic parameters
to generate robust separations with
sufficient resolution. While there are
many approaches to method develop-
ment, such as changing one factor
at a time and design of experiments
(DoE), the goals and factors used for
optimizing separations are the same.
They all involve changing columns or
mobile phase to increase the resolu-
tion between the desired analytes and
other compounds.
Resolution is affected by three fac-
tors: eff iciency (N ), retention (k ′),
and selectivity (α), as shown in the
resolution equation:
Rs4
. .=√N
∝
(∝−1) k'
k' +1[1]
It is well known that selectivity is the
most powerful factor that affects res-
olution. Selectivity can be controlled
through several factors including the
choice of stationary phase, the type
of organic modif ier, gradient slope,
f low rate, and temperature. For ion-
izable compounds, pH of the buffer
is a lso a powerful parameter. Opti-
mizing the separation of ionizable
compounds to f ind robust conditions
has become an important part of
method development in liquid chro-
matography (LC).
Most pharmaceutica l and bio-
logical compounds contain ionizable
moieties such as carboxylic or amino
groups. Because retention in reversed-
phase LC is strongly dependent on
the analyte charge, pH can be used to
make large changes in selectivity. At
pH values below their pKa, acids have
their maximum retention because
they are neutral, but bases have their
minimum retention because they
are fully charged. At pH levels more
basic than the pKa of the compound,
bases have their maximum retention
because they are neutral, and acids are
fully ionized and have their minimum
retention. For the best peak shape,
retention and sample loading of basic
analytes in reversed-phase LC, the
mobile-phase pH should be two units
32 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
higher than the pKa of the compound
of interest. In this work, the adjust-
ment of pH is used to control selec-
tivity using a high-pH-compatible
superficially porous particle C18 col-
umn that is designed to be stable over
a broad pH range, including high-pH
mobile phases.
Superficially porous particle (SPP)
technology is based on particles with
a solid core and a porous shell. The
most common particles consist of
a 1.7-μm solid core with a 0.5-μm
porous shell. In total, the particle size
is about 2.7 μm. The 2.7-μm SPPs
provide 40–50% lower back pressure
and 80–90% of the efficiency of sub-
2-μm totally porous particles (TPPs)
for small molecule separation. The
SPPs have a narrower particle size dis-
tribution than TPPs. This results in a
more homogeneous column bed and
reduces dispersion in the column. At
the same time, the thin porous shell
gives reduced longitudinal diffusion
and slightly lower resistance to mass
transfer for small molecules. The
result is minimal loss of efficiency at
higher f low rates (1–3).
Until recently, all SPP materials
were silica based and possessed lim-
ited lifetime in higher pH buffers,
including phosphate or bicarbonate
buffers. To achieve longer lifetimes, it
is necessary to protect the base silica
particle by either surface modif ica-
tion or special bonding modification.
The surface of newer high-pH-stable
SPP particles is chemically modi-
fied to form an organic layer that is
resistant to silica dissolution at high
pH conditions. The high-pH-stable
SPP particles are bonded with C18
and endcapped. The lifetime of these
new SPP C18 columns was compared
to the original 100% silica SPP col-
umns as well as another commercially
available column packed with totally
porous silica particles that have a
hybrid surface.
Experimental
A 1260 Infinity Binary LC (Agilent)
was used for this work. It consisted
of a binary pump, an autosampler, a
column thermostat, and a diode-array
detector equipped with a 10-mm
pathlength (1-μL) f low cell. OpenLab
110
100
90
80
Init
ial
eff
cie
ncy
(%
)
70
60
500 1000 2000 3000
Stress buffer (mL)
Silica SPP-C18
High-pH-stableSPP-C18
Figure 1: Lifetime of SPP columns in phosphate buffer, pH 8, at elevated temperature. Mobile phase: premixed 60% 30 mM sodium phosphate buffer at pH 8 and 40% methanol; fow rate 0.4 mL/min; UV absorbance 254 nm; 65 °C; column dimensions: 50 mm × 2.1 mm, 2.7 µm; analyte: naphthalene.
Figure 2: Column stability test under high-pH bicarbonate buffer conditions: (a) 50 mm × 2.1 mm HPH SPP-C18, (b) a commercially available high-pH-compatible 50 mm × 2.1 mm TPP C18. Mobile-phase A: 10 mM ammonium bicarbonate adjusted to pH 10.0 in water; mobile-phase B: acetonitrile; gradient: 5–95% B in 5 min, return to 5% in 1 min, hold 1 min at 5%; fow rate: 0.4 mL/min; detection: UV absorbance at 220 nm; temperature: 40 °C. Peaks: 1 = methyl salicylate, 2 = 4-chlorocinnamic acid, 3 = acetophenone, 4 = quinine, 5 = nortryptyline, 6 = heptanophenone, 7 = amitriptyline.
1
1.5
(a)
2.5 3.5 4.52 3 4
1.5 2.5 3.5 4.52 3 4
1.5 2.5 3.5 4.52 3 4
1.5 2.5 3.5Time (min)
4.52 3 4
23
4
56
7Injection 1
Injection 500
Injection 1000
Injection 2000
1
2 3
45 6
7
Injection 1
1.5 2.5 3.5 4.52 3 4
1.5 2.5 3.5 4.52 3 4
1.5 2.5 3.5 4.52 3 4
1.5 2.5 3.5 4.52 3 4Time (min)
Injection 2000
Injection 1000
Injection 500
(b)
APRIL 2015 Recent Developments in Hplc anD UHplc 33www.chromatographyonline.com
Chromatography Data System (Agi-
lent) was used to control the HPLC
system and process the data. Columns
packed with 2.7-μm Poroshell HPH-
C18 (high-pH-stable SPP), or 2.7 μm
Poroshell EC-C18 (Agilent) in 50 mm
× 2.1 mm, 100 mm × 2.1 mm, or 50
mm × 4.6 mm dimensions were used.
A model 6140 single-quadrupole mass
spectrometer (Agilent) was added
to the instrument configuration to
determine the impact of pH on mass
spectrometry (MS) sensitivity of basic
compounds.
Stability of High-pH-Stable SPP
Column at Mid and High pH
HPLC column stability is a critical
factor impact ing method per for-
mance and has been widely stud-
ied (4,5). Column stability can be
a f fected by temperature, type of
aqueous buffer and their concentra-
tion, choice of organic solvents, addi-
tives, and mobile-phase pH. A column
that is not stable during method develop-
5.52.7-μm high-pH-stableSPP-C18
2.7-μm silica SPP-C185.0
4.5
4.0
3.0
3.5
2.5
1.5
1.0
0.50 2 4 6 8 10
Reduced interstitial linear velocity
Re
du
ced
pla
te h
eig
ht
12 14 16 18 20
2.0
Figure 3: Van Deemter curves of a silica SPP C18 column (50 mm × 4.6 mm) and a high-pH-stable SPP C18 column (HPH SPP-C18, 50 mm × 4.6 mm). Mobile phase: 60:40 acetonitrile–water; temperature: 25 °C; detection: UV absorbance at 254 nm, 80 Hz; analyte: naphthalene.
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delivers innovation … in
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34 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
ment leads to inaccurate results and
frustration. A robust HPLC method
using a durable column leads to suc-
cessful support of new clinical and
manufacturing projects.
Column degradation at elevated
pH and temperatures is caused by
si l ica d issolut ion, bonded-phase
removal, or through the exposure of
silanols through the loss of end cap-
ping (hydrolysis). Both dissolution
and hydrolysis of silica columns are
known to be related to pH and tem-
perature (increased degradation rate
at higher pH or temperatures).
One mobile phase that is f re-
quently used for lifetime testing at
mid-pH levels is pH 7 phosphate
buffer in methanol. However, most
silica columns lose eff iciency after
prolonged exposure to these condi-
tions. Kirkland and colleagues (6)
and Tindall and Perry (7) discussed
possible reasons for the reduced life-
time of silica columns in phosphate
buffer, but both agree that columns
do not last long.
A lthough phosphate buffers are
considered diff icult to use at pH 7
and above, they are commonly used
because of their clean UV baseline
during gradients. In a lifetime test
experiment, 50 mM sodium phos-
phate dibasic and sodium phosphate
monobasic buffer was made at pH
8 and diluted with methanol to a
60:40 buffer–methanol mixture with
a f inal buffer concentration of 30
mM. The column temperature was
raised to 65 °C. By elevating the tem-
perature and using a pH 8 phosphate
buffer, the rate of column degrada-
tion is signif icantly increased. Note
that this test was designed to accel-
erate the degradation of silica-based
columns and is not recommended as
an analytical method condition. A
sample containing naphthalene was
injected every 10 min. This method
was used to compare a standard
silica SPP C18 column and a high-
pH-stable SPP C18 column. The
high-pH-stable SPP particles were
synthesized by chemically modifying
the surface of the silica SPP particles
with an organic layer. As can be seen
in Figure 1, the standard silica SPP
C18 lasted approximately 200 mL
in this mobile phase before 10% of
eff iciency was lost. At 1000 mL, eff i-
ciency was reduced by 40%. When
the high-pH-stable SPP C18 column
was subjected to the same treat-
ment, no degradation was noted at
2000 mL and the column lost 10%
efficiency at 3000 mL.
For practitioners, a good criterion
for column stability under a given
pH is the ability to maintain stability
for ≥500 injections. This allows for
method development, as well as sub-
sequent use of the column with the
established method. We evaluated
the stability of a high-pH-stable SPP
C18 column with a gradient using
ammonium bicarbonate at pH 10 and
acetonitrile. A mixture of acidic, neu-
tral, and basic compounds was used
to probe a variety of possible ionic
and loss of hydrophobic interactions
caused by column degradation. As
can be seen in Figure 2a, the reten-
tion time of all compounds remained
stable throughout the 2000-injection
run with the exception of nortryp-
tyline. This compound, with a pKa
very close to the pH of the mobile
phase, moved slowly to longer reten-
tion times.
A second commercia lly available
column, packed with totally porous
particles designed for elevated pH
stability, was subjected to the same
experimental conditions. Most of the
analytes remained at the same reten-
tion time throughout the 2000 injec-
tions. Nortryptyline moved rapidly
to later elution times. Within 500
injections, nortryptyline began to
be coeluted with the next compound,
neutra l hexanophenone. The nor-
tryptyline peak continued to migrate
through this peak and was totally
coeluted by injection 2000. This
experiment revealed less degradation
of the high-pH-stable SPP C18 col-
umn than the other column. Note
that for both this and the previous
experiment with the high-pH-stable
SPP C18 column, the sample via l
solution was remade several times
during the lifetime study so that rela-
tive peak heights differed somewhat
throughout the study.
Efficiency of a High-pH-
Stable SPP C18 Column
A van Deemter study was done to
ensure that the surface modification
to make the high-pH-stable SPP C18
particles did not negatively impact
the eff iciency of the SPP particles.
To do this, we conducted f low stud-
ies on a high-pH-stable SPP C18
300 2
2
2
3
BasesAcids
Time (min)
3
3
4
5 6
4
4
5
5
6
68
8
7
7
7
8
3.532.51.50.50 1
1
2
3.532.51.50.50 1 2
3.532.51.50.50 1 2
10 mM HCO2NH
4 (pH 3)
10 mM NH4C
2H
3O
2 (pH 4.8)
10 mM NH4HCO
3 (pH 10)
1
1
250200150100
500
300
Ab
sorb
an
ce (
mA
U)
250200150100
500
300250200150100
500
Figure 4: Selectivity control by altering pH. Column: 50 mm × 4.6 mm, 2.7-µm HPH SPP-C18; mobile-phase A: 10 mM ammonium formate (pH 3), ammonium acetate (pH 4.8), or ammonium bicarbonate (pH 10.0) in water; mobile-phase B: acetonitrile, gradient: 10–90% B in 5 min, hold 2 min at 90%; flow rate: 2 mL/min; detection: UV absorbance at 254 nm; temperature: 30 °C. Peaks: 1 = pro-cainamide, 2 = caffeine, 3 = acetyl salicylic acid, 4 = hexanophenone degradant, 5 = dipyrimadole, 6 = diltiazem, 7 = diflunisal, 8 = hexanophenone.
APRIL 2015 Recent Developments in Hplc anD UHplc 35www.chromatographyonline.com
column and a si lica SPP C18 col-
umn. The van Deemter curves are
shown in Figure 3. It is clear that the
two columns have very similar eff i-
ciency throughout the range of f low
rate studied with similar minimum
reduced plate height at the optimum
f low rate. Therefore, the kinetic per-
formance of the high-pH-stable SPP
C18 column is similar to the silica
SPP C18 column. All performance
features of the superf icially porous
particles are retained on the high-
pH-stable SPP C18, while the high-
pH stability is substantially improved.
Effect of Mobile-
Phase pH on Selectivity
With a SPP particle stable in high pH
mobile phases, we studied the effect
of pH on the selectivity of ionizable
analytes. Figure 2 depicts how the
elution order of a mixture consist-
ing of acidic, basic, and neutral com-
pounds changes as pH of the mobile
phase is changed. In this work, a
generic gradient was used with the
organic modif ier (acetonitrile) con-
centration changing from 10% to
90% over 4 min at 2 mL/min. Chro-
matograms at pH 3 (ammonium for-
mate), pH 4.8 (ammonium acetate),
and pH 10 (ammonium bicarbonate)
are shown. These are MS-compatible
buffers. The buffers were prepared by
dissolving suff icient ammonium for-
mate, ammonium acetate, or ammo-
nium bicarbonate in water to produce
10 mM solutions. The solutions were
adjusted to the desired pH with the
appropriate concentrated acid (for-
mic acid or acetic acid) or concen-
trated base (ammonium hydroxide).
The sample mixture included acids
(acetyl salicylic acid and dif lunisal),
bases (procainamide, dipyrimadole,
and dilt iazem), and neutra l com-
pounds (hexanophenone and impu-
rity, and valerophenone). Caffeine
was included in this work but its pKa
is outside of the range of pH studied,
so its ionization state does not change.
The three chromatograms in Figure
2 use the same organic gradient and
column so that hexanophenone (neu-
tral) and caffeine remain at the same
elution time. They are not affected
by the change in pH. As the mobile-
phase pH is increased from pH 3
to pH 4.8, the acidic compounds
become deprotonated (charged) and
their retention time decreases. This is
depicted by the red arrows in Figure
4. As the pH is increased further, the
retention times of the bases increase,
as shown with the blue arrows. The
peak elution order changes dramati-
cally as does the spacing. In all three
chromatograms the peak shape is
excellent. In this series of experi-
ments, the retention times of the
compounds were more evenly spaced
using the pH 10 buffer than either of
the other buffers.
Another way to look at selectivity is
by plotting retention time using two
dif ferent mobile-phase pH condi-
tions for a large group of acids, bases,
and neutral compounds. A list of the
compounds is provided in Table I. In
this case, 117 compounds were run
36 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
Table I: Compounds used in retention correlation
Sample Name Sample Name Sample Name Sample Name
1,2-Dimethoxybenzene Atenolol Esterone Procaine
1,2-Dinitrobenzene Atorvastatin Ethinylestradiol Progesterone
1,2,3-Trimethoxybenzene Beta estradiol Ethyl-4-hydroxybenzoate Promazine
1,2,4-Trimethoxybenzene Beclomethasone Fenprofen Propranolol
1,2,5-Trimethoxybenzene Benzocaine Fluoxetine Protriptyline
1,3-Dimethoxybenzene Benzoic acid Furazolidone Pyrimethamine
1,3-Dinitrobenzene Benzophenone Hesperidin Quinine
1,4-Dinitrobenzene Benzyl alcohol Hydrocortisone Resorcinol
2,3-Dimethylphenol Betamethasone Irganox 1330 Salicytic acid
2,4-Dichlorophenol Biphenyl (DMSO) Ketoprofen Salicylic acid
2,4-Dimethyl benzoic acid Butacaine Labetalol Sulfachloropyridazine
2,5-Dihydroxyl benzoic acid Butyl benzene m-Nitrophenol Sulfadiazine
2,5-Dimethyl phenol Butyl paraben Mefamic acid Sulfadimethoxine
2-Hydroxyhippuric acid Butylated hydroxy anisole Naldolol Sulfamerazine
2-Napthalene sulfonic acid Butylated hydroxy toluene Naproxen Sulfamethiazine
3,4-Dimethoxybenzoic acid Butyrophenone Nargingenin Sulfamethiazole
3-Nitrophenol Caffeine Nisoldipin Sulfamethoxazole
4-Hydrobenzaldehyde Catechol Norethindrone acetate Sulfamethoxypyridazine
4-Hydroxybenzoic acid Chloramphenicol Nortryptyline Sulfamonomethoxine
4-Nitrophenol Corticosterone p-Cresol Sulfaquinoxaline
5-Hydroxy-isophthalic acid Desimpramine p-Nitrophenol Sulfathiazole
8-Hydroxyquinoline Dexamethasone Pentachlorophenol Sulindac
Acebutolol Diclofenac Phenacetin Testosterone
Acetylsalicylic acid Diethyl phthalate Phenantranene Tetracaine
Alprenolol Difunisal Pindolol Tolemetin
Amitriptyline Diisopropyl phthalate Piperidine Triamcinalone
Andro Dioctyl phthalate Piroxicam Trimipramine
Antipyrin Dipropyl phthalate Pravastatin Ultranox 276
APAP Doxepim Prednisone Uracil
Valerophenone
using the high-pH-stable SPP C18
column with gradients of methanol
at pH 3 and 10 and acetonitrile at pH
3 and 10. The generic gradient was
0.42 mL/min, starting at 5% organic
and increasing to 95% organic over
4 min, followed by a hold at 95%
organic for 2 min. This methodology
was applied and discussed in previous
work where two highly similar col-
umns (similar phase chemistries on a
silica SPP and silica TPP) were com-
pared under similar chromatographic
conditions (8). The correlation coef-
f icient of retention times is a mea-
sure of the difference in selectivity
under two different pH conditions. A
highly correlated plot would indicate
that the chromatographic separations
are very similar. On the other hand,
a very low correlation value (close to
0.5 or lower) indicates a more orthog-
onal or dissimilar separation.
As can be seen in Figure 5a, the
overall correlation is quite low with
a correlation coefficient of 0.49. This
low correlation indicates that most of
APRIL 2015 Recent Developments in Hplc anD UHplc 37www.chromatographyonline.com
the compounds were retained differently in the two mobile-
phase pHs. The group contains basic compounds that are
charged at pH 3. As they become deprotonated when the
pH is increased to 10, the retention time increases. Like-
wise, the acidic compounds, which are not charged at low
pH, become deprotonated (charged) as the pH is increased
and lose retention. It is easy to see a subgroup of com-
pounds that line up perfectly with a slope of 1. These are
neutrals or compounds that do not change ionization state
and their retention times are not affected by the pH of the
mobile phase, as expected. A second comparison is also
shown in Figure 5b, using low and high pH gradients with
acetonitrile as the organic modifier. In this case, the cor-
relation coefficient was slightly smaller than that in metha-
nol, but still indicates very different selectivities for acids
and bases at different pHs (9–11).
Improved LC–MS Sensitivity
for Basic Compounds at High pH
In another experiment, LC–MS of several bases was com-
pared at high and low pH using a generic gradient in posi-
tive ion mode electrospray ionization. Normally one expects
Figure 5: Selectivity comparison at low and high pH with (a) methanol and (b) acetonitrile as mobile-phase B. Col-umn: 50 mm × 2.1 mm, 2.7-µm HPH SPP-C18; mobile phase A: 10 mM ammonium formate (pH 3) or 10 mM ammonium bicarbonate (pH 10) in water; mobile-phase B: methanol or acetonitrile; gradient: 5–95% B in 4 min, hold at 95% for 2 min; flow rate: 0.42 mL/min; detection: UV absorbance at 220 nm; temperature: 30 °C.
7(a)
6
5
4
3
2
1
00 1 2 3
Retention time pH 3 methanol
Re
ten
tio
n t
ime
pH
10
me
tha
no
l
R2 = 0.49
4 5 6 7
7(b)
6
5
4
3
2
1
00 1 2 3
Retention time pH 3 acetonitrile
Re
ten
tio
n t
ime
pH
10
ace
ton
itri
le
R2 = 0.40
4 5 6 7
that the ionization state of analyte molecules is dependent
on the pH of the mobile phase, and that the ionization
efficiency in LC–MS with electrospray ionization in posi-
tive ion mode (ESI+) will be dramatically lowered in high-
pH mobile phases since the compounds become neutral.
However, many researchers investigating different types
of samples (including proteins, peptides, and amino acids)
have observed either insensitivity to an increase of mobile-
phase pH or even increases in sensitivity (12–17). High-pH
mobile phases do not suppress the ionization of basic com-
pounds in ESI+. Positive ions are formed abundantly and
analyte responses are often better in high pH compared
to acidic mobile phases. This finding is significant as it
extends the applicability of generic elution methods to the
analysis of polar basic compounds that were previously dif-
ficult to retain.
To test this finding, three bases with pKa values ranging
from 8.0 to 9.3 were chromatographed on a high-pH-stable
SPP C18 column at pH 3 (0.1% formic acid) and pH 10
(10 mM ammonium bicarbonate) with acetonitrile as the
organic modifier (Figures 6a–6c). The lower traces in each
figure show the samples analyzed at low pH and the upper
traces show the samples analyzed at high pH. In all three
cases, the analytes were less retained at pH 3 and the peaks
tailed. In contrast, at pH 10 (upper traces) the analytes were
more retained, had better peak shape, and were twice as tall.
At pH 10, the analytes were eluted in a mobile phase having
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38 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
a higher organic content. In general,
ionization in the more volatile organic
phase is more eff icient, leading to
higher signal intensity and, indeed, the
peak areas were also significantly larger
for the pH 10 compared to the pH 3
chromatograms. These results show
that the use of high-pH mobile phases
for the analysis of basic compounds
offers a good alternative to using low-
pH mobile phases in ESI+ LC–MS.
Conclusions
The chemical stability of surface mod-
if ied superficially porous particles is
evaluated by conducting column life-
time tests under different high-pH
buffers and high temperature condi-
tions. We determined that the surface
modif ication substantially improves
the high-pH stability of SPP while
preserving the performance features
of SPP columns. We showed that a
high-pH-stable SPP C18 column
could be used for extended periods
(over 2000 injections) with high-pH
mobile phases such as pH 10 ammo-
nium bicarbonate buffer. Therefore,
chromatographers can now explore a
wider range of pH in method devel-
opment using SPP technology, which
is being increasingly adopted because
of its high eff iciency and speed.
Control of pH can be used to adjust
selectivity without sacrif icing column
lifetime at elevated pH. This work
showed that by keeping a gradient
constant and altering pH, the elution
order of a group of eight acid, base,
and neutral compounds could be dra-
matically changed. Chromatographic
resolution was improved. In a second
experiment, the correlation coeff i-
cient of retention times in a generic
gradient was determined between
pH 3 and pH 10. Using R2 as a mea-
sure of orthogonality, we found that
the two conditions offered different
selectivity for acids and bases. There-
fore, using pH as a method develop-
ment tool is very effective, especially
when the sample contains ionizable
compounds.
We also investigated positive ion
electrospray MS of several basic com-
pounds using gradient reversed-phase
LC at high and low pH. The peak
shapes of basic compounds improved
Figure 6: Comparison of LC–MS of three basic compounds in positive ion electro-spray at low and high pH: (a) procainamide, (b) lidocaine, and (c) diltiazem. Column: 100 mm × 2.1 mm, 2.7-µm HPH SPP-C18; mobile-phase A: 0.1% formic acid (pH 2.8) or 10 mM ammonium bicarbonate (pH 10) in water; mobile-phase B: acetonitrile; gradient: 10–90% B in 10 min, hold at 90% 2 min; fow rate: 0.5 mL/min; system: single-quadrupole LC–MS; temperature: 30 °C.
1,000,000
0
2,000,000
3,000,000
4,000,000
5,000,000
1,000,000
02 4 6 8 10
2 4 6 8 10
Time (min)
0.1 % Formic acid–acetonitrile
10 mM Ammonium bicarbonate–acetonitrile
(pH 2.8)
(pH 10)
Area = 2.1 X 107
Area = 1.2 X 107
2,000,000
3,000,000
4,000,000
5,000,000
(a)
10 mM Ammonium bicarbonateÐ
acetonitrile (pH 10)
0.1 % Formic acidÐacetonitrile
(pH 2.8)Area = 3.9 X 106
Area = 5.2 X 106
6.1
33
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
0
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
0
2 4 6 8 10
2 4 6 8 10Time (min)
(b)
1,000,000
(c)
8,000,000
6,000,000
4,000,000
2,000,000
0
1,000,000
8,000,000
6,000,000
4,000,000
2,000,000
0
2 4 6 8 10
2 4 6 8 10
Area = 2.7 X 107
0.1 % Formic acid–acetonitrile(pH 2.8)
10 mM Ammonium bicarbonate–acetonitrile (pH 10)
Area = 2.9 X 107
6.4
97
4.1
51
Time (min)
APRIL 2015 Recent Developments in Hplc anD UHplc 39www.chromatographyonline.com
and retention times increased with the
high pH eluents. We also observed a
signal increase as measured by the
peak area and sensitivity increase as
measured by peak height. The magni-
tude of the signal increase was not the
same in all cases and was likely to be
compound dependent. In no case was
a signal decrease observed for bases at
elevated pH.
References
(1) X. Wang, W.E. Barber, and W.J. Long, J.
Chromatogr. A 1228, 72–88 (2012).
(2) F. Gritti, A. Cavazzini, N. Marchetti,
and G. Guiochon, J. Chromatogr. A 1157,
289–303 (2007).
(3) S. Fekete, D. Guillarme, and M.W. Dong,
LCGC North Am. 32(6), 420–433 (2014).
(4) C. Ye, G. Terf loth, Y. Li, and A. Kord, J.
Pharm. Biomed. Anal. 50, 426–431 (2009).
(5) A.M. Faria, E. Tonhi, K.E. Collins, and
C.H. Collins, J. Sep. Sci. 30, 1844–1851
(2007).
(6) J.J. Kirkland, M.A. van Straten, and
H.A. Claessens, J. Chromatogr. A 797,
111–120 (1998).
(7) G.W. Tindall and R.L. Perry, J. Chro-
matogr A 988, 309–312 (2003).
(8) Transfer of Methods between Poroshell
120 EC-C18 and ZORBAX Eclipse Plus
C18 Columns, Agilent Technologies, Inc.
Technical Report 5990-6588EN (2011).
(9) L .R. Snyder, J.J. Kirk land, and J.W.
Dolan, Introduction to Modern Liquid
Chromatography, 3rd Ed. ( John Wiley &
Sons, Hoboken, New Jersey, 2010), p. 29.
(10) K. Croes, A. Steffens, D. Marchand, and
L. Snyder, J. Chromatogr. A 1098, 123–
130 (2005).
(11) W. Long and A. Mack, Agilent Tech-
nologies, Inc. Application Note 5990-
4711EN, (2009).
(12) R. Chirita-Tampu, C. West, L. Foug-
ere, and C. Elfakir, LCGC Europe 26(3),
128–140 (2013).
(13) H.P. Nguyen and K.A. Schug, J. Sep. Sci.
31(9), 1465–1480 (2008).
(14) S. Zhou and K.D. Cook, J. Am. Soc. Mass
Spectrom. 11 961–966 (2000).
(15) R.D. Ricker, Agilent Technologies, Inc.
Application Note 5989-0683EN (2004).
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G. Goldberg, and P. Goodley, J. Am. Soc.
Mass Spectrom. 6, 1221–1225 (1995).
(17) C.R. Mallet, Z. Lu, and J.R. Mazzeo,
Rapid Commun. Mass Spectrom. 18,
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William J. Long, Anne E. Mack, Xiaoli Wang, and William E. Barber are with Agilent
Technologies, Inc., in Wilmington,
Delaware. Direct correspondence
to: [email protected] ◾
For more information on this topic,
please visit
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Karyn M. Usher, Steven W. Hansen, Jennifer S. Amoo, Allison P. Bernstein, and Mary Ellen P. McNally
Precision of Internal Standard and External Standard Methods in High Performance Liquid Chromatography
Internal standard methods are used to improve the precision and
accuracy of results where volume errors are difficult to predict and
control. A systematic approach has been used to compare internal and
external standard methods in high performance liquid chromatography
(HPLC). The precision was determined at several different injection
volumes for HPLC and ultrahigh-pressure liquid chromatography
(UHPLC), with two analyte and internal standard combinations.
Precision using three methods of adding the internal standard to the
analyte before final dilution was examined. The internal standard
method outperformed external standard methods in all instances.
A systematic approach was used
to compare interna l stan-
dard (IS) and external stan-
dard (ESTD) methods used in high
performance liquid chromatography
(HPLC). The experiments described
were specif ically designed to exam-
ine the precision of the IS method as
compared to the ESTD method using
the last two generations of HPLC and
ultrahigh-pressure liquid chromatog-
raphy (UHPLC) systems. Two meth-
ods of introducing the IS were com-
pared; these methods involved either
weighing the amount of IS added as
a solid or an internal standard solu-
tion of known concentration. Along
with two types of instruments, HPLC
and UHPLC, we used three analytes
at different concentrations and injec-
tion volumes. A review of the literature
revealed a limited number of papers
that discussed the use of the internal
standard in HPLC. None of the ref-
erences used the approaches described
herein to evaluate the effect of using
an internal standard compared to the
external standard approach.
In an external standard calibration
method, the absolute analyte response
is plotted against the analyte concen-
tration to create the calibration curve.
An external standard method will not
provide acceptable results when con-
siderable volume errors are expected
because of sample preparation or
injection-to-injection variation. An IS
method, which is a method where a
carefully chosen compound different
from the analyte of interest is added
uniformly to every standard and sam-
ple, gives improved precision results in
quantitative chromatographic experi-
ments. The internal standard calibra-
tion curves plot the ratio of the ana-
lyte response to the internal standard
response (response factor) against the
ratio of the analyte amount to the
internal standard amount. The resul-
tant calibration curve is applied to the
ratio of the response of the analyte to
the response of the internal standard
in the samples and the amount of ana-
lyte present is determined.
Several approaches have been used
to determine the amount of internal
standard that should be used in pre-
paring the standards and the samples,
but none have illustrated definitive
results (1–4). For example, Haefelfin-
APRIL 2015 Recent Developments in Hplc anD UHplc 41www.chromatographyonline.com
ger (1) reports that the IS peak height
or area must be similar to that of the
analyte of interest, but does not pres-
ent supporting data. Araujo and col-
leagues (2) show that experimental
design strategies can be used to deter-
mine the optimal amount of internal
standard used while Altria and Fabre
(3) show that the IS should be used in
the highest possible concentration.
Calculation of the response factor
assumes that the detector gives a linear
response for both the analyte and the
internal standard over the entire range
of the experiment. Since this is not
always the case, it is essential to under-
stand the behavior of the response fac-
tor as the concentration or amount
of analyte and internal standard are
varied. Knowing the behavior of the
response factor allows one to set limits
on the useful range of the chosen ana-
lyte or internal standard concentration
combinations.
The internal standard method is used
to improve the precision and accuracy
of results where volume errors are dif-
ficult to predict and control. Examples
of types of errors that are minimized
by the use of an internal standard are
those caused by evaporation of sol-
vents, injection errors, and complex
sample preparation involving transfers,
extractions, and dilutions. An internal
standard must be chosen properly and
a known amount added carefully to
both sample and standard solutions to
minimize error and be utilized to its
full advantage. The resulting internal
standard peak should be well resolved
from other components in the sample
and properly integrated. If all of these
conditions are not met, the use of an
internal standard may actually increase
the variability of the results. One
report suggests that whenever detec-
tor noise or integration errors are the
dominant sources of error, the use of
an internal standard will likely make
the results of the experiment worse (5).
A paper published by P. Haefelfin-
ger in the Journal of Chromatography
in 1981 (1) discussed some limitations
of the internal standard technique in
HPLC. Using the law of propagation of
errors, the paper showed conditions that
need to be met for the internal standard
procedure to improve results. In addi-
tion to the mathematical illustration,
Haefelfinger detailed practical exam-
ples where either internal or external
standard methods were advantageous.
The Journal of the Pharmaceutical
Society of Japan published a study in
Table I: Chromatographic conditions used for the analysis of indoxacarb. The HPLC method is an official DuPont technical assay method and the UHPLC method is a method developed for these experiments.
Indoxacarb* Chromato-graphic Conditions
HPLC UHPLC
Chromatographic columnZorbax SB-C8
250 mm × 3.0 mm, 5 µmZorbax SB-C8
75 mm × 4.6 mm, 3.5 µm
Mobile phase A 38% water 38% water
Mobile phase B 62% acetonitrile 62% acetonitrile
Flow rate 0.65 mL/min 2.0 mL/min
Column temperature 45 °C 45 °C
Injection volume 0.2–10 µL 0.2–5 µL
Wavelength 280 nm (bandwidth = 4 nm) 280 nm (bandwidth = 4 nm)
Reference wavelength 380 nm (bandwidth = 80 nm) 380 nm (bandwidth = 80 nm)
*Pure active enantiomer
Table II: Chromatographic conditions used for the analysis of diuron. The HPLC method is an official DuPont technical assay method and the UHPLC method is a method developed for these experiments.
Diuron (14740) Chro-matographic Conditions
HPLC UHPLC
Chromatographic columnZorbax XDB-C8
150 mm × 4.6 mm, 3.5 µm Zorbax XDB-C8
75 mm × 4.6 mm, 3.5 µm
Mobile phase A70% water (pH = 3.0 adj.
with H3PO4) 70% water (pH = 3.0 adj.
with H3PO4)
Mobile phase B 30% acetonitrile 30% acetonitrile
Flow rate 1.5 mL/min 1.5 mL/min
Column temperature 40 °C 40 °C
Injection volume 0.2–10 µL 0.2–2 µL
Wavelength 254 nm (bandwidth = 4 nm) 254 nm (bandwidth = 4 nm)
Reference wavelength 350 nm (bandwidth = 100 nm) 350 nm (bandwidth = 100 nm)
(c)
(d)
(a)
(b)
0.2
1.2
1.0
0.8
0.6
0.4
0.2
0.0
5.0
4.0
3.0
2.0
1.0
0.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0.5 1.0 2.0 4.0 5.0
Injection volume0.2
3.0
2.5
2.0
1.5
1.0
0.5
0.00.5 2.0 4.0 10.0
Injection volume
ESTD volume ESTD weight IS solution
HPLCUHPLC
HPLCUHPLC
0.2 0.5 1 2
Injection volume
0.2 0.5 1 2 10
Injection volume
Figure 1: Comparison of external and internal calibration methods: (a) indoxacarb with UHPLC, (b) diuron with UHPLC, (c) indoxacarb with HPLC, (d) diuron with HPLC. Each bar represents eight injections.
42 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
2003 (6) that found that the inter-
nal standard method did not offer an
improvement in precision with the
then current autosampler technology.
Interestingly, they also found that if
the peak of the internal standard was
small, the relative standard deviation
(RSD) was actually larger than the
RSD for the external standard method
(6). The limitation of this study was
that only one injection volume (10 µL)
was used to establish the conclusions.
In our work, a systematic approach
has been used to compare the inter-
nal to the external standard method
using two analytes and two internal
standards. The precision resulting
from both an internal and external
standard method were determined at
several injection volumes and on two
different instruments. Three methods
of adding the IS to the analyte before
final dilution have been compared. In
the first, a solid internal standard was
weighed directly into the glassware
containing the sample before dilution
with solvent. In the second, a solution
of a known concentration of the IS
was prepared and a known volume of
this solution was added to the sample
prior to dilution. In the third, the
IS was added in the same manner as
the second method, but the internal
standard solution was weighed and
the weight, not the volume, was used
in the IS calculations. We examined
the effect of weight of analyte and
internal standard on the precision of
the results. Initially, the weights of
the analyte were varied versus a con-
stant IS concentration, and then the
concentration of the internal standard
was varied versus a constant weight of
the analyte.
Standard deviation was chosen to
monitor precision. All possible errors
are ref lected in the standard deviations
of the final measurements, including
each step in the sample preparation,
sample transfer, and sample introduc-
tion into the HPLC or UHPLC sys-
tem, as well as the HPLC or UHPLC
Table III: Operating conditions for technical assay methods for experiments comparing the method of addition of the internal standard
Technical Assay
ColumnMobile-Phase A
Mobile-Phase BFlow Rate (mL/min)
Temp. (ºC)
Inj. Vol. (µL)
λ (nm) Reference
Indoxacarb*Zorbax SB-C8 Solvent Saver
25 cm × 3.0 mm, 5 µm62% acetoni-
trile38% water 0.65 45 4 280 380
Indoxacarb† Chiralcel OD 25 cm × 4.6 mm
85% hexane and 15%
isopropanol
50% isopropa-nol–50% hexane (post run fush)
1 40 5 310 450
FamoxadoneZorbax Rx C18
15 cm × 4.6 mm, 5 µm48% acetoni-
trile52% water 2.0 40 10 260 400
DiuronPartisil 5 RAC II ODS3
10 cm × 4.6 mm32% acetoni-
trile68% water 2 40 5 254 450
*Pure active enantiomer †75:25 racemic mixture of active and inactive enantiomers
Table IV: Regression results and correlation coefficients for injector linearity tests
Compound Instrument Slope y-intercept R2
Diuron UHPLC 3913.5 310.71 1.0000
3-Methyl-1,1-diphenylurea UHPLC 1763.4 93.166 1.0000
Indoxacarb HPLC 333.46 0.9806 1.0000
p-Terphenyl HPLC 477.48 2.1863 1.0000
Injection volume
Avera
ge s
tan
dard
devia
tio
n
DuPont technical assay
Doubleconcentration
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.00 2 4 6 8 10
Figure 2: Comparison of results obtained for the DuPont technical assay method when injections at two different volumes were made.
APRIL 2015 Recent Developments in Hplc anD UHplc 43www.chromatographyonline.com
analyses themselves. Both external and
internal standard calibration methods
were used to calculate the percent
recoveries for comparison.
Experimental
Chemicals
The mobile phases were binary mix-
tures of acetonitrile and water (pH
adjusted with phosphoric acid). The
water was purified house water (EMD
Millipore Corp.) and the acetoni-
trile and phosphoric acid (EM Sci-
ence) were HPLC grade. Diuron and
indoxacarb standards were obtained
from DuPont Crop Protection. The
internal standards were p-terphenyl
(Aldrich Chemicals) and 3-methyl-1,1-
diphenylurea (Aldrich Chemicals). All
solutions were prepared as needed or
stored in the refrigerator.
Sample Preparation
For the comparison of calibration
methods, the official DuPont techni-
cal assay methods for indoxacarb and
diuron were adapted for use. All stan-
dards and samples were prepared in
acetonitrile. The indoxacarb standards
ranged in concentration from 0.15 to
0.7 mg/mL; samples were prepared at
a concentration of 0.5 mg/mL. The
internal standard was p-terphenyl at
a concentration of 0.08 mg/mL. The
diuron standards ranged in concentra-
tion from 0.75 to 1.25 mg/mL; sam-
ples were prepared at a concentration
of 1 mg/mL. The internal standard
was 3-methyl-1,1-diphenylurea at a
concentration of 1 mg/mL. Precision
data was calculated based on eight
individually prepared samples with
duplicate injections of each sample.
For the comparison of the method
of addition of the internal standard
experiments, three DuPont enforce-
ment methods for technical assay of
indoxacarb, famoxadone, and diuron
were used. Precision data was calcu-
lated based on eight individually pre-
pared samples with duplicate injec-
tions of each sample.
Instrumentation and
Chromatographic Conditions
Agilent 1100 and 1290 Infinity HPLC
systems (Agilent Technologies) were
used, each consisting of a binary pump,
an autosampler, a thermostated column
compartment, and a diode-array detector.
Instrument control and data collection
were performed using ChemStation soft-
ware. Chromatographic conditions are
given in Tables I, II, and III. The techni-
cal methods were adapted as needed; for
example, a method specifies the injection
volume, and we collected data using sev-
eral injection volumes for each compound.
Calibration Methods
Internal Standard Versus
External Standard Calibrations
A set of samples was prepared in such a
way that results could be calculated for
both the internal and external standard
methods. All samples were prepared
using class A volumetric glassware. Ini-
tially, the analyte was weighed directly
into the volumetric f lask. Next, the
internal standard was weighed into the
same f lask and acetonitrile was added
to dissolve the solids. The f lask was
then diluted to the mark and the mass
of the final solution was recorded. This
step allowed the results to be calculated
using the external standard method in
two ways, by using the nominal vol-
ume of the volumetric f lask and also
by using the mass of the solution to
calculate the concentrations. In both of
these cases, the internal standard added
was not included in the calculations.
These two methods will be denoted as
“ESTD nominal volume” and “ESTD
weight,” respectively. The internal
standard method, where the weighed
volume of the internal standard solu-
tion was recorded, will be denoted as
“IS solution.” Because the samples were
prepared in this manner, the results for
the three methods were calculated using
the same data files. The difference in
the calculated standard deviations in
this way is attributed to the calibration
method, and is independent of any dif-
ferences in sample preparation.
Comparison of Methods
of Addition of the Internal Standard
Two sets of samples were prepared for
each compound analyzed. The first set of
samples were prepared by weighing the
solid analyte and then weighing the solid
IS into the sample container and dilut-
ing. The second set of samples were pre-
pared by weighing the solid analyte into
the sample container and then adding
a specified volume of internal standard
solution, which was subsequently also
weighed. Standard deviations were cal-
culated for these two internal standard
introduction methods.
Results and Discussion
To determine if instruments were func-
tioning properly, eight replicate injections
of one prepared sample for each analyte
Table V: The nominal injection volumes, and exact masses and volumes of IS and analyte along with the resulting response factors
CompoundInjection Volume
(µL)
Avg. Mass (g)Avg. IS Volume
(solution) (mL)
Avg. Peak Areas Response
FactorIS Solid IS solution Analyte IS
Indoxacarb* 4.0 0.055 0.008 15.5 6000 4000 1.50
Indoxacarb* 4.0 0.050 0.010 15.3 3687 3627 1.02
Indoxacarb† 5.0 0.100 0.012 7.9 7100 1500 4.73
Famoxadone 10.0 0.125 0.040 7.9 4100 4300 0.95
Diuron 2.0 0.100 0.100 7.8 4230 1830 2.31
*Pure active enantiomer †75:25 racemic mixture of active and inactive enantiomers
Table VI: Comparison of results using different methods for the addition of the internal standard
Compound
Standard Deviation
Solid IS
Weighed IS
IS by volume
Indoxacarb* 3.592 0.391 0.293
Indoxacarb* 1.408 0.368 ‡
Indoxacarb† 2.041 0.190 0.172
Famoxadone 1.410 0.110 0.172
Diuron 0.444 0.162 ‡
*Pure active enantiomer† 75:25 racemic mixture of active and inactive enantiomers
‡ Dispensers were used rather than volu-metric pipettes, so this value could not be accurately calculated.
44 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
and internal standard were injected into
each instrument at different injection vol-
umes. The chromatographic conditions
are shown in Tables I and II. The injector
linearity was tested for both analytes and
both internal standards and the results
are given in Table IV. The range tested
for the standard HPLC and the UHPLC
instruments were 0.2–10.0 µL and 0.2–
5.0 µL, respectively. The injection pre-
cision at each flow rate was compared
to the manufacturer specifications, the
instruments performed at or better than
the manufacturer’s specifications.
There are other important factors to
consider when optimizing chromato-
graphic methods, some of which are car-
ryover, column back pressure, and wave-
length (7). Our experiments controlled
these parameters.
Comparison of Calibration Methods
In general, there was not a large difference
in the calculated standard deviations for
the two external standard methods. Any
differences seen did not suggest a trend,
and appear to be random. An expected
trend when using both external standard
methods was that standard deviations
became larger with decreased injection
volume.
The results calculated using the inter-
nal standard calibration method always
demonstrated improved precision over
the results calculated using an external
standard calibration. See Figure 1 for
precision results for diuron and indoxa-
carb using HPLC and UHPLC instru-
ments. The graphs in Figure 1 show that
at larger injection volumes the precision
for the IS method appears constant, but
at lower injection volumes the standard
deviation increases drastically. This phe-
nomenon does not occur at the same
injection volume for both compounds,
nor does it occur at the same injection
volume for either compound using HPLC
or UHPLC.
Logically, overall peak areas are smaller
with smaller injection volumes and loss of
precision is caused by integration errors.
Larger integration errors occur with smaller
areas being integrated and lead to larger
standard deviations calculated for the
percent error. To determine if this effect
of volume injected was the cause for the
increase in RSD for low peak areas, sam-
ples of diuron were prepared at twice the
concentration level of the original experi-
ment and two different volumes were
injected. If the loss of precision was solely
because of the smaller size of the peak, then
the standard deviation calculated using the
higher concentration samples should be
smaller than the standard deviation calcu-
lated for the original samples. This was not
the case; Figure 2 shows that the standard
deviations calculated when peaks were two
times as large as the original were not sig-
nificantly different from the original stan-
dard deviation. Again, the loss of precision
was not explained by the smaller absolute
size of the peak.
Figure 3 shows the peak areas corre-
sponding to different injection volumes for
diuron and indoxacarb standards and their
corresponding internal standards. With
diuron, the internal standard method did
not produce acceptable results at injec-
tion volumes lower than 1 µL; the internal
standard peak area was smaller than the
analyte peak area at all injection volumes.
The horizontal lines drawn in Figure 3
correspond to the peak area of the internal
standard, 3-methyl-1,1-diphenylurea, in
the diuron solutions. If the peak size was
completely responsible for loss of precision
at small injection volumes, then any results
calculated using peak areas below this
line at any injection volume should show
similar loss of precision. Correspondingly,
for indoxacarb, a similar loss of precision
would have been seen at all the chosen
injection volumes. Indoxacarb was not
consistent with this hypothesis. The loss
of precision is not completely explained by
the absolute size of the peak.
Peak Area Ratios
To further investigate this precision loss
when smaller injection volumes (0.2, 0.5,
and 1 µL) were used, two separate samples
of diuron and indoxacarb, each with IS,
were injected eight times using the con-
ditions described in Tables I and II. The
resulting peak area ratios (analyte peak
area/internal standard peak area) were
plotted against the injection number as
shown in Figure 4. At these smaller injec-
tion volumes, the responses are less precise
than at the larger injection volumes. The
exact injection volume where this is seen
varies from compound to compound, but
generally occurred at injection volumes
Table VII: Calculated standard devia-tions for IS added by two methods when analyte weight is varied
Analyte Weight (mg)
Standard Deviation
IS (Weighed Solid)
IS (Weighed Solution)
25 0.691 0.368
75 0.149 0.142
100 0.131 0.086
125 0.25 0.203
175 0.121 0.083
Table VIII: Calculated standard devia-tions for IS added by two methods and resulting in varying final con-centrations of IS while the analyte weight is kept constant
IS Weight (mg)
Standard Deviation
IS (Weighed Solid)
IS (Weighed Solution)
25 0.795 0.253
75 0.247 0.297
100 0.131 0.086
125 0.197 0.149
175 0.182 0.287
Peak a
rea
Peak a
rea
18,000
16,000
14,000
12,000
10,000
8000
3000
Diuron peak
Indoxacarb peak
Indoxacarb IS peakDiuron IS peak
Injection volume (µL) Injection volume (µL)
2500
2000
1500
1000
500
0
6000
4000
2000
0
0 1 2 3 4 5 0 1 2 3 4 5
(a) (b)
Figure 3: Graphs of peak area versus injection volume for (a) diuron and (b) indoxa-carb. The solid line corresponds to the peak area for the IS in the diuron method.
APRIL 2015 Recent Developments in Hplc anD UHplc 45www.chromatographyonline.com
smaller than 2 µL. Figures 1 and 2 show
that on average, the peak area ratio is
changing as the injection volume changes
and is greater at smaller injection volumes.
Thus, confirming a calibration curve pre-
pared using one injection volume should
not be used with data resulting from a
different injection volume. The difference
in area ratio over the range of injection
volumes appears small, but is significant.
For the diuron analysis using UHPLC,
the percent recoveries calculated using
the highest and lowest calculated peak
area ratios shown in Figure 4 (0.2 µL and
5.0 µL, respectively), resulted in a differ-
ence of 0.86% overall recovery. For the
diuron analysis using HPLC data, percent
recoveries determined using the highest
and lowest calculated peak area ratios
(0.2 µL and 10.0 µL, respectively), resulted
in an overall recovery difference of 4.28%.
Small differences in the area ratios at dif-
ferent injection volumes can have a large
impact on the calculated recoveries.
Figure 4 shows that the peak area ratios
used for the IS method do not remain con-
stant over the range of injection volumes
examined. Some peak area ratios varied
by as much as 0.05 units. This change as
the injection volume is changed can cause a
systematic error in the calculated recoveries
that results from the use of an IS calibration
curve. As previously discussed, the error in
percent recovery because of the changing
value of the peak area ratios over the range
of injection volumes used was as small as
0.86% for the UHPLC analysis and as
large as 4.28% for the HPLC analysis. This
topic warrants further investigation.
Comparison of the Methods
of Internal Standard Addition
Three methods of internal standard addi-
tion were compared. In the first method,
the internal standard was added directly
as a solid. In the second method, a solu-
tion of the internal standard was prepared,
added, and weighed into the analyte solu-
tion before final dilution. Calculations
were then performed using the weight of
the added solution. For the third method,
the internal standard preparation and
introduction were the same as the second
method; however, the calculations were
performed using the nominal volume
from the Class A volumetric pipette. Table
V gives the injection volumes used in the
chromatographic methods, the masses of
the analyte and IS used, the volume of the
IS used, the average peak areas for both
the analyte and the IS, and the resulting
response factors. Table VI shows the stan-
dard deviations that were calculated when
the IS was added by these three different
methods. An F-test showed a significant
difference in the resulting standard devia-
tions between the first method (weigh-
ing the IS as a solid) and the other two
methods (introducing a solution of the
IS). There were small differences in the
standard deviations using the two sepa-
rate methods of introducing the internal
standard as a solution and calculating via
either the volume or weight; however, no
specific trend was obvious.
When the IS was weighed as a solid,
the precision was almost a factor of three
and 13 times larger, for diuron and
famoxadone, respectively, than when
the IS was added as a weighed solution
(see Table VI). These results suggest the
precision could potentially be limited by
the accuracy of the balance. Supporting
this, whenever the weight of either the
analyte or IS was less than 100 mg, the
standard deviation was large, generally
1.4%; conversely, when the weight was
100 mg or higher, the standard devia-
tion was less than 0.5%. Nearly a three-
fold improvement in standard deviation
was obtained by increasing the weights
being used to at least 100 mg, or add-
ing another significant digit to the mass
measurement. Overall, the standard
deviation was significantly smaller when
the internal standard was added as a solu-
tion rather than as a solid, attributed to
the larger mass of solution versus solid
being weighed. To confirm this, the
measured weights of the analyte and the
IS were varied separately using the diu-
ron enforcement method. This method
was chosen because it exhibited the low-
est inherent standard deviation. Table
VII shows the results where the mass of
the analyte was varied from 25 mg to
175 mg while the IS amount was held
constant. Both methods of internal stan-
dard introduction were used; the constant
amount of solid and internal standard
solution weighed into the analyte solu-
tion was 100 mg, and 7.8 g, respectively.
Table VII shows the standard deviations
for the varied amount of analyte, from
75 to 175 mg. These calculated standard
deviations are all 0.25% or less for both
IS introduction methods. Decreasing
the analyte mass to 25 mg, the standard
deviation quadruples to 0.69% for solid
introduction and 0.37% for the weighed
(a)
Injection number
Are
a r
ati
o
0 2 4 6 8
0.2 µL1.46
1.45
1.45
1.44
1.44
1.43
0.5 µL
1 µL
2 µL
4 µL
5 µL
(b)
Injection number
Are
a r
ati
o
0 2 4 6 8
0.2 µL2.39
2.38
2.37
2.36
2.35
2.34
2.33
0.5 µL
1 µL
2 µL
4 µL
5 µL
Figure 4: Comparison of peak area ratios at different injection volumes for (a) in-doxacarb and (b) diuron.
46 Recent Developments in Hplc anD UHplc APRIL 2015 www.chromatographyonline.com
solution of internal standard. The stan-
dard deviations for the samples prepared
by adding the IS as a solution are always
lower than for those prepared by adding
the IS as a solid. Conversely, when the
mass of analyte was kept constant at 100
mg and the mass of the IS was varied,
similar results were obtained. Specifi-
cally, the calculated standard deviations
were less than 0.3% except when the IS
mass was 25 mg for the weighed solid
internal standard. For 25 mg of weighed
solid internal standard, the precision was
0.8%. These results are given in Table
VIII. Therefore, it can be concluded that
excellent precision in chromatographic
results is effected by the precision of the
balance, the weight of the internal stan-
dard, and the introduction method of
the internal standard.
Further analysis of the data disputes
some of the ideas regarding the internal
standard that were previously reported.
Haefelfinger (1) reported that the IS peak
area must be similar (response factor
close to 1) to that of the analyte of inter-
est. The data and results given in Tables
V and VI do not support this and do not
suggest any specific correlation between
the response factor and the standard
deviation. Altria and Fabre (3) state that
the IS should be used in the highest pos-
sible concentration. The results in Table
VIII elucidate the standard deviation for
some of the samples with lower concen-
trations of IS showing better precision
than some with higher concentrations
of IS. Our results illustrate that injection
volumes and the method of addition of
the internal standard are more impor-
tant than having a response factor close
to one or using high concentrations of IS.
Conclusions
When precision is an important factor,
the chromatographic instrument should
be tested before the start of any analy-
sis to ensure that it is working properly.
Injection-to-injection variation and the
injector linearity both have a pronounced
effect on precision at smaller injection
volumes, so it is important to confirm
that the instrument being used is capa-
ble of providing acceptable results at the
chosen injection volume. The internal
standard method corrects for different
sources of volume errors, including injec-
tion-to-injection variation, volume errors
in sample preparation, and accounts for
routine variations in the response of the
chromatographic system.
We have shown the internal standard
method outperformed external standard
methods in all experiments, regardless of
the analyte, choice of internal standard,
method of introduction of internal stan-
dard, and the injection volume. Even so,
at low injection volumes the resulting
precision, when using the internal stan-
dard method, was poor. For the com-
pounds used, this breakdown typically
occurred at injection volumes of less
than 2 µL and was dependent on the spe-
cific compound and IS being used, and
not the instrument. Loss of precision did
not coincide with a specific minimum
peak area, so poor precision cannot be
attributed to the smaller size of the peaks
at smaller injection volumes. The break-
down in precision was also not because
of larger injection variability at smaller
injection volumes. If that was the case,
the loss of precision would occur at the
same injection volume on each instru-
ment regardless of what compound was
being studied.
The results of this study show that
when poor precision occurs at injec-
tion volumes less than 2 µL, significant
improvement in results may be achieved
by simply increasing the injection vol-
ume without the need for developing a
new method. This is true whether an
external standard or an internal standard
method is being used.
With an internal standard method, the
precision of the experiment is affected by
how the internal standard is measured.
For solutions prepared to have the same
final concentration of analyte and IS,
there is a significant difference in the
precision when the internal standard is
added as a solid or a solution of known
concentration. For all the analyte and
IS combinations tested, the precision
was significantly better when a solution
of the IS was first prepared at a known
concentration then added to the analyte
before dilution.
Our chromatographic resultant preci-
sion was not limited by the precision of
the balance when the masses being used
were larger than 25 mg. There was no
direct correlation between the response
factors and the calculated standard devi-
ations. Our data also did not support the
common perception of an IS being used
in the highest concentration possible.
Overall, the results show that the inter-
nal standard method can significantly
improve the precision of a chromato-
graphic method. However, attention
must be paid to the injection volume and
the method by which the internal stan-
dard is added to the analyte. To achieve
better precision, increasing the injection
volume of the sample solution is effective.
Acknowledgments
The authors would like to acknowl-
edge Steve Platz for many contributions,
including being a safety mentor and
training on using the HPLC instrument.
We would also like to thank Jim Schmit-
tle, Peter Schtur, and Jennifer Llewelyn
for their support of this project.
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Steven W. Hansen, Jennifer S. Amoo, and Mary Ellen P. McNally are with DuPont Crop Protection at the Stine Haskell Research Center in
Newark, Delaware. Karyn M. Usher is an associate professor at Metropolitan State University, Minnesota. She contributed to this work as a visiting scientist at DuPont
Crop Protection. Allison P. Bernsteinis with DuPont Industrial Biosciences in Cedar Rapids, Iowa. Direct correspondence to: [email protected] ◾
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