Two-Dimensional Liquid Chromatography: A State of the Art Tutorial

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Two-Dimensional Liquid Chromatography: A State of the Art Tutorial Dwight R Stoll, and Peter W. Carr Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b03506 • Publication Date (Web): 28 Nov 2016 Downloaded from http://pubs.acs.org on December 1, 2016

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Analytical Chemistry

Two-Dimensional Liquid Chromatography: A State of the Art Tutorial Dwight R. Stoll1 and Peter W. Carr2

1 – Gustavus Adolphus College Department of Chemistry Saint Peter, MN, USA 2 – University of Minnesota Department of Chemistry Minneapolis, MN 55104, USA

*Address correspondence to [email protected]; 507-933-0699

ACS Paragon Plus Environment


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Description – In this tutorial we discuss the motivations for doing two-dimensional liquid

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chromatography (2D-LC), and describe the commonly used implementations of the method. We

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review important guiding principles for method development, discuss the state of the art in 2D-

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LC performance as measured by peak capacity, and describe example applications from

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different fields that we hope will inspire new users to adopt 2D-LC for their analytical problems.

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Biography

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Dwight Stoll is associate professor and co-chair of the department of chemistry at Gustavus

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Adolphus College where he teaches courses in quantitative and instrumental analysis. His

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research is focused on the development of 2D-LC for both targeted and untargeted analysis.

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Biography

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Peter Carr is professor in the department of chemistry at the University of Minnesota –Twin

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Cities. His research has involved electroanalytical, thermoanalytical chemistry and separation

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science. His group have been involved in the study of the retention in GC, LC and SFC, the

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development of novel stationary phase for LC and most recently fast LC and 2D-LC.

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Opening Art

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1. Introduction

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In this tutorial we aim to capture the state of the art of two-dimensional liquid chromatography

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(2D-LC) by highlighting key background that will help readers understand where 2D-LC

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methods fit in the analytical chemist’s toolbox. We then review some of the most fundamental

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principles of 2D-LC. Finally, we show by way of selected examples the ways in which 2D-LC is

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being used in practice to efficiently and effectively solve challenging analytical problems in a

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variety of fields. This tutorial is most certainly not a comprehensive review; rather it is an

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introduction for interested but unfamiliar readers. Those looking for more depth and breadth are

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encouraged to consult a number of recent reviews1–7 and books8,

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appropriate we have drawn attention throughout this article to particular reviews that are

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especially relevant to specific topics. Finally, most of the nomenclature and terminology used

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here that are specific to 2D-LC are nominally consistent with those prescribed by Marriott and


9

on 2D-LC. Where


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Schoenmakers. For more detailed explanations of some terms readers are advised to consult

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the most recent listing of terms, definitions, and nomenclature10.

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2. Motivations for more than one separation dimension

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Despite decades of development of liquid chromatography (LC), including recent technological

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advances (e.g., sub-two micron and core-shell particles, higher pressure and lower dispersion

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instrumentation) 1D-LC is often unable to quickly separate mixtures of interest. These failures

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generally involve two distinct types of problems: A) mixtures that are too complex in a general

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sense (e.g, the thousands of metabolites in biological samples) and thus outstrip the ability of

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1D-LC to entirely separate the mixture into distinct components (i.e. singlet peaks); and B)

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mixtures that are not necessarily complex per se, but contain several species of interest that

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are very difficult to resolve, either because there are just too many compounds to avoid

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overlap, or due to the presence of closely related compounds (e.g., enantiomers, structural

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isomers).

90 91

The Challenge of Complex Samples – Peak capacity is the metric most often used to define the

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limitations of 1D-LC in tackling type-A problems. Peak capacity is a theoretical construct that

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estimates the maximum number of peaks that can be fit, side-by-side at equal resolution

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(typically 1.0), within a given separation space11. Recent estimates for the maximum peak

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capacity that is achievable in 1D-LC of small molecules range from about 100 in analyses of ca.

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5-10 minutes to a few hundred in analyses of a few hours (assuming solvent gradient elution

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and RPLC). These numbers roughly double when discussing separations of peptides, in part

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because the extent of gradient peak compression is greater in this case, and inherently their

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greater sensitivity to a change in composition produces narrower peaks even if there were no 12, 13

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effect of on-column compression of the tailing side of the peak

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peak Overlap (STO) of Davis and Giddings14 allows estimation of the fraction of constituents in

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a sample that would be (on average) observed as chromatographically distinct (singlet) peaks

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for different combinations of sample complexity and peak capacities. Figure 1 shows the

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calculated results for sample complexities in the range of 5 to 1000 and peak capacities in the

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range of 100 (easily achieved by 1D-LC) to 3000 (only achievable in a reasonable time (< 2

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hour) by 2D-LC). We see that for a 50-component mixture, only about 50% of the compounds

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will be observed as distinct (i.e., resolved) peaks, whereas a peak capacity of 3000 increases

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the fraction of compounds observable as singlet peaks to about 95%. This surely is a valuable


. The Statistical Theory of

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increase, but the difference becomes more profound as the sample complexity increases as

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shown in Fig. 1.

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112 113 114

Figure 1. Percentage of sample consituents that are resolveable as chromatographically distinct peaks

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(‘singlets’, with a minimum resolution of 1.0) as a function of the number of compounds in a sample and

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different separation peak capacities. Effective peak capacities of 100 and 200 are easily achieveable

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within 15 minutes using modern particle and instrument technologies. A peak capacity of 400 is more

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difficult to reach for small molecules, but can be reached within an hour for peptides. An effective peak

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capacity of 3000 is not accessible by 1D-LC in a practically reasonable time, but can be readily achieved

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by 2D-LC in one to two hours. Singlet peak numbers were calculated assuming the same concentrations

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for all components, and using Eq. 21 from Davis and Giddings .

14

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The Challenge of Difficult-to-Resolve Mixtures – This issue is familiar to chromatographers in

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many application areas. When only a limited time is available to resolve an apparently ‘simple’

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mixture, we often find that the analysis time is controlled by the resolution of one or a few

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stubborn pairs of compounds which resist improvement despite changes to the easily

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manipulated separation variables such as eluent composition, stationary phase type or column

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temperature. Changes in the stationary phase type can often effect greater changes in elution

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pattern, but improvements in one critical pair frequently result in the lessening in the separation

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of another pair. The benefits of adjusting stationary phase differences can be enhanced

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somewhat through column coupling and selectivity tuning15. Ultimately though, we do not find

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ourselves much further ahead after changing the phase chemistry. Indeed, this issue is the

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driving force behind hundreds of papers devoted to replacing Edisonian trial and error with

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sophisticated methods to model retention and selectivity as a function of the method variables



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leading to the algorithmically directed optimization of the separation variables16. In spite of their

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sophistication, such model driven optimization approaches are also limited by low

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methodological peak capacities. The bottom line is that as chromatograms become increasing

138

crowded, the chance of encountering an area of refractory peak overlap increases dramatically.

139 140

When experimenting with different stationary phase chemistries we can often envision a phase

141

that will resolve most of the sample components leaving a few unresolved components and then

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“magically” using a different phase chemistry that we know would ‘finish the job’ by resolving

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only the pairs of problematic peaks unresolved on the first column, We are now witnessing the

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emergence of commercial instrumentation, software, and a theoretical framework that allows us

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to realize this ‘magic’ in practice – this is precisely the type B problem that 2D-LC can solve,

146

both effectively and efficiently.

147 148

Figure 2 captures these ideas in the form of chromatograms, Panels A and B are simulated

149

chromatograms for 15-minute gradient separations of a 20-component mixture, where each

150

separation has a peak capacity of 200. The selectivities of the two phases are assumed to be

151

moderately correlated (see panel D), as is expected for two quite different reversed-phase

152

columns17. In spite of the modest correlation, there are some pairs of compounds which clearly

153

co-elute on one phase, but are easily separated by the second phase (e.g., the compounds

154

represented by the green points). In panels A and B areas of serious peak overlap (i.e.,

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resolution less than 1.5) are indicated by asterisks at the tops of the peaks. Consistent with our

156

experience with real samples, we see that the regions of the chromatogram where overlaps

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occur are very different in the two cases. Now, one thought-experiment that is commonly

158

discussed is – what would happen if we simply coupled these two columns together, in series,

159

so that their complementary selectivities can be leveraged to more fully resolve the sample?

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The results of these thought experiments are easily realized through simulation in this case, as

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shown in panel C. Here we see, again consistent with our experience, that serial coupling of

162

columns does resolve some of the problematic overlaps, but in the end the poor resolution is

163

simply shifted to a different part of the chromatogram. The reason that this approach is only

164

moderately helpful is that it is fundamentally limited by its peak capacity – because the

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chromatogram is relatively crowded, the chance of encountering overlap is very high. Coupling

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columns does little to improve peak capacity, especially if the total analysis time is not

167

increased.

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Inspection of panel A shows that Column 1 does a nice job of separating 16 of the 20

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components but there are two areas of overlap denoted by an asterisk (*) in the figure. Each co-

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elution consists of two overlapping compounds (see the red and green points in panel D). For

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each of these pairs, the retentions of the overlapping compounds are very similar on Column 1,

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but rather different on Column 2. So, we do the thought experiment involving pulling the first pair

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of overlapped compounds from the outlet of Column 1 as a mixture and injecting them into

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Column 2 where they can be separated in a matter of seconds. Here we assume that the

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analysis time for each injection into Column 2 is 60 seconds, and that Column 2 has a peak

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capacity of 50 for each of these analyses. When this separation is finished, we immediately

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inject the second mixture into Column 2 (green compounds), and this separation is also finished

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within a minute. In this way we very effectively and efficiently fully resolve this mixture that could

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not otherwise be resolved by 1D chromatography.

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problem is no longer imaginary; we now have the ability to do such 2D-LC separations using

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commercially available instrumentation, supported by sophisticated control and data analysis

183

software, resulting in separations that are fast, sensitive, reliable, and robust.

The proposed solution to this type of

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186 187

Figure 2. Simulated separations by 1D- and 2D-LC that demonstrate the power and value of 2D-LC for

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difficult-to-resolve mixtures, as compared to simple serial coupling of columns with different selectivities.



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Panel A shows the separation of a hypothetical 20-component mixture with given stationary phase

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chemistry and a peak capacity of 200. Panel B shows the separation of the same sample, but with

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different stationary phase chemistry. Panel C shows the separation that would result from serial coupling

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the columns in (A) and (B). These three are all 1D separations. In contrast the panels on the right show

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what happens if the same columns used in C are used in a 2D separation. The relationship between the

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retention times of the 20 compounds on the two columns is shown in Panel D. Panels E and F show the

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1

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sample; in this case the mixture is fully resolved in the same analysis time.

2

D and D separations that result from a simulated multiple heartcutting 2D-LC separation of the same

197 198

3. Different Implementations of 2D-LC Can Be Used to Address Different Types of

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Analytical Challenges

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The essential concept in 2D-LC is that one or perhaps many fractions of the effluent from the 1D

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column are transferred to (i.e., injected into) a 2D column; ideally the task of the 2D column is to

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separate all the unresolved analytes present in each fraction of the 1D effluent based on the

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differences in selectivity of the two dimensions. A diagram of the hardware commonly used for

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online comprehensive 2D-LC separations is shown in Fig. 3. This diagram emphasizes the

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importance of the valve, often called a modulator, which interfaces the 1D and 2D columns. The

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valve shown here has a symmetrical 8-port, 2-position design. Many other valve configurations

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have been described in the literature – the most comprehensive discussion of these options

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have been given by Schure and Cohen18, and Francois, Sandra, and Sandra19.

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Figure 3. Diagram of a typical 2D-LC instrument highlighting the centrality of the valve between the D

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detector and the D column that captures fractions of D effluent and injects them into the D column. The

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red arrow indicates that the change in valve position enables switching the role of each sampling loop

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between collection of D effluent and injection into the D column.

1

2

1

1

2

2

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Here we discuss four physically different ways that this 2D separation process is most often

217

done in practice; others which are less commonly used, are described elsewhere20, 21. Three of

218

these approaches are shown in Fig. 4; their pluses and minuses, and typical applications are

219

given in Table 1. This tutorial focuses on 2D separations carried out online, and in time (not in

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space, as in 2D Thin Layer Chromatography or 2D Gel Electrophoresis). Less common

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approaches including 3D and in space separations are described elsewhere21–25.

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The simplest, by a wide margin, and earliest form of a 2D-LC method to be used extensively is

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the single heartcutting approach, denoted as LC-LC. As the name suggests, LC-LC involves the

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collection of a single fraction of 1D effluent and its subsequent injection into a 2D column for

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further separation. This is most commonly carried out using a valve equipped with a length of

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tubing having a volume that is sufficient to accommodate the 1D effluent fraction of interest. This

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is a simple and easy implementation of 2D-LC but it is rather limited in terms of its scope of

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application and the number of target unresolved analytes that can be addressed in a given

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analysis. Historically, LC-LC has most commonly been used for the quantitation of a small

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number of target compounds in a rather complex matrix. The pioneering work of Majors and

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coworkers on the determination of biologically active small molecules in matrices such as urine

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is a good example of such an application26. Currently, LC-LC is being applied to a wide variety

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of problems (see Section 6).

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Comprehensive 2D-LC the polar opposite of LC-LC is denoted here as LC×LC. In most cases

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the primary objective of LC×LC is generally to gain as much information as possible about the

238

sample in a single 2D chromatogram. For example, in applications such as metabolomics27 or

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proteomics28 the objective is ideally to separate the analyte mixture completely thus simplifying

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the detector’s job; in such applications the detector is usually a mass spectrometer. In other

241

cases, the sample may not be so complex per se, but the most valuable information might be

242

the knowledge that all of the components of a particular sample are chromatographically

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resolved. This type of information is acquired in LC×LC by collecting discrete fractions of the 1D

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effluent at regular intervals (perhaps one fraction every 15 to 30 s), and then these fractions are

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transferred one at a time to a 2D column. This collection and transfer process (referred to as

246

sampling, or modulation) typically begins early in the 2D-LC analysis, and continues for most of

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the analysis time (see Fig. 4B). In comparison to LC-LC, LC×LC is capable of providing

248

information about a much larger number of analytes in a sample. The 2D chromatograms from

249

such experiments can reveal peak patterns akin to those seen in GC×GC where groupings of



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specific analyte functionalities (e.g. alkanes, aldehydes, degree of unsaturation etc.) along

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vectors or arcs can be extraordinarily helpful for identifying unknowns or confirming compound

252

identity29. This additional information comes at the cost of increased instrument complexity and

253

often results in the loss of some information from the 1D separation due to undersampling (see

254

Section 4.1). Nevertheless, when peak capacity is used as the metric of separation

255

performance, it has been shown that the peak capacity of LC×LC exceeds that of 1D-LC

256

starting below 5-10 min, and increases thereafter30–32.

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Between the extrema of LC-LC and LC×LC several groups have explored intermediate and

259

hybrid implementations that blend concepts from both. Two such hybrids are discussed here;

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namely, multiple heartcutting (mLC-LC) and selective comprehensive 2D-LC (sLC×LC). In

261

principle, mLC-LC is simply an extension of LC-LC in that single fractions from several 1D peaks

262

are transferred one at a time to the second dimension for further separation. This extends the

263

scope of applicability of the heartcutting approach, because more analytes can be targeted in a

264

single chromatogram33, 34. Figure 2E/F implies that two adjacent but different regions of the 1D

265

chromatogram are targeted to enable the full resolution of the sample by ‘finishing the job’ with

266

the 2D column. In practice, however, what makes mLC-LC especially powerful is the ability to

267

simultaneously collect a fraction from one 1D peak while separating the constituents of

268

another35,

269

parallel significantly improves the flexibility of LC-LC.

36

. That is, instrumentation that enables these two processes to be executed in

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The sLCxLC implementation is fundamentally quite different from mLC-LC, even though similar

272

instrument hardware can be used for both. sLC×LC is selective in that only specific regions of

273

the 1D chromatogram are targeted for further separation. On the other hand, it is comprehensive

274

in Giddings’ meaning of “comprehensive” in that the resolution of the specific analytes taken

275

from the 1D column is not diminished as a result of doing the sampling of the 1D separation. In

276

the current literature the loss of resolution during the sampling process is termed undersampling

277

(see Section 4.1). The figure illustrating sLC×LC (Figure 4C) shows that the 1D column effluent

278

from 6.3 to 6.7 minutes was collected as six discrete, 4-second increments. At the end of the

279

sampling period, each fraction is injected into the 2D column. In this example each 2D analysis

280

time is 15 s. One major benefit of the sLCxLC approach is that the separation contributed by the

281

1

282

the two peaks eluting at about 6.38 and 6.55 minutes in the first dimension, and at 7.5 seconds

283

in the second dimension. If the sampling time were much longer at 15 s or more, as is typically

D process can be maintained no matter how narrow are the 1D peaks. This is exemplified by


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the case in LC×LC, these two analytes zones would be re-mixed during the fraction collection

285

and transfer processes, and thus would not be re-separated by the second dimension. A second

286

significant advantage of sLC×LC over simple heartcutting is that it enables precise and accurate

287

quantitation along with high resolution separation. In the case of heartcutting methods, the only

288

way to ensure highly precise and accurate quantitation is to transfer a fraction volume that is

289

much larger than the peak volume of the target analyte. This in turn makes the subsequent 2D

290

separations more crowded compared to when smaller fractions are used. The alternative to a

291

large fraction volume is to use a much smaller fraction centered on the middle of the target

292

analyte peak – a true ‘heartcut’ – however, in this case even very slight shifts in retention of the

293

target analyte can seriously compromise quantitative precision35, 37. This is why one must use a

294

transfer volume that is larger than the peak volume to avoid losing analyte from the 1D

295

separation.

296 297

At this point it is important to note that all of the implementations of 2D-LC described here can

298

be carried out in both offline and online modes. In the offline mode fractions of 1D effluent are

299

first collected e.g. in vials or micro wellplates external to the instrument. Then, at some

300

convenient time later, the collected fractions are sequentially injected into a 2D column. The

301

beauty of this approach is that very high speed 2D separations are not as essential as in online

302

LC×LC. Furthermore, it is conceivable that a very powerful offline 2D-LC separation could be

303

carried out in two steps using a single, conventional 1D-LC instrument. Indeed, theoretically the

304

highest possible 2D-LC peak capacities can be achieved in the offline mode38 although at the

305

cost of significantly increased analysis time. In spite of these potential advantages, the vast

306

majority of 2D-LC work over the past five years has been focused on the online mode wherein

307

1

308

Although this requires more sophisticated instrumentation, the resulting methods can be highly

309

automated using state-of-the-art commercial instruments that are robust and precise.

310

Maintaining 1D effluent fractions within the instrument minimizes sample contamination and

311

losses, both of which are especially important when working with complex samples.

D effluent fractions are taken and transferred almost immediately to the second dimension.

312



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313 314

Figure 4. Visual comparison of different implementations of 2D-LC. Panel A shows the case of LC-LC

315

(heart cutting 2D-LC) where in this case only a single fraction is injected into the D column. Note that in

316

multiple heart cutting (mLC-LC, not shown) more than one region of the 1D effluent would be injected

317

onto the D column. Panel B shows the case of LC×LC (comprehensive 2D-LC) where the entire D

318

effluent is sequentially injected. Panel C shows the case of sLC×LC (selective comprehensive 2D-LC)

319

where selected segments of the D effluent are injected comprehensively on to the D column .

2

2

1

1

2

320 321

Table 1. Comparison of key attributes of the major online implementations of 2D-LC. Number of Implementation

Target

Advantages

Disadvantages

Typical Application

Compounds Targeted analysis in Single Heartcut (LC-LC)

+

Simple; Powerful for

Limited to a few

complex matrix (e.g.,

highly targeted work

target compounds

drug metabolite in serum)

More complex

Multiple Heartcut

++

(mLC-LC)

(sLC×LC)

instrumentation;

target compounds

Quantitation can be tricky

Breaks link between

Selective Comprehensive

Amenable to more

+++

Quantitation of moderately complex mixture (e.g., mixture of achiral/chiral molecules) Quantitation of many

sampling time and 2D

More complex

compounds in

analysis time,

instrumentation

complex mixture,

providing more


targeted analysis

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flexibility; Quantitation can be more robust

Slow speed of

(LC×LC)Full Comprehensive

++++

Most efficient way to

second dimension

obtain full view of

separation

sample composition -

significantly limits

can see several

contribution of first

hundred peaks in

dimension

reasonable analysis

separation to overall

time

resolution due to

Sample profiling/fingerprinting (e.g., metabolomics), discovery (untargeted) type analysis

undersampling

322 323

4. Best Practices for Highly Effective 2D-LC Separations

324

When developing 2D-LC methods one encounters a number of key decisions which have no

325

analog in 1D-LC. This has prompted the systematic study of 2D-LC method development

326

resulting in a body of literature that serves to effectively guide such work. Given that most

327

aspects of 2D-LC are more costly and complex than their counterparts in 1D-LC, we would like

328

to make the most of the resources invested in these methods. LC-LC methodology is relatively

329

well established, and excellent examples of highly effective methods are easily found. In

330

contrast mLC-LC and sLCxLC are much newer, and extensive method development guidance is

331

not yet available. Thus, in this section we focus on best practices for the development of LC×LC

332

methods. To the extent that mLC-LC and sLC×LC methods involve some of the features of

333

LC×LC methods, some of the concepts discussed below will naturally be highly applicable to

334

these other implementations.

335

4.1 The 1D Undersampling Problem

336

“Undersampling” results in loss of resolution of analytes achieved in the 1D separation due to re-

337

mixing of those analytes during the sampling process (e.g., in the sampling loop). This is one of

338

the most important concepts that must be appreciated to develop high quality 2D-LC methods.

339

From the early conceptual work of Giddings39 and through the pioneering work of Murphy,

340

Schure, and Foley (M-S-F)40 the community has developed a sense for how frequently 1D

341

effluent should be sampled into the 2D separation for us to say that that the 1D separation has



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Page 14 of 34

342

been sampled sufficiently rapidly. With this as a benchmark, we then say that any 1D separation

343

that is sampled less frequently than it ought to be is undersampled, and that the negative

344

consequences that arise from this are due to undersampling the 1D separation. Giddings stated

345

that under ideal circumstances the peak capacity of a LC×LC method will be the product of the

346

peak capacities of the two 1D separations that contribute to the 2D separation41. These ideal

347

circumstances include the idea that none of the resolution gained by the 1D separation is lost in

348

the process of collecting fractions of 1D effluent and transferring them to the 2D column39. In

349

practice this can never be completely achieved, but there are now guidelines for minimizing

350

such losses, and means to quantitatively account for the losses when they do occur. When the

351

time over which a single fraction of 1D effluent is collected is wider than the intrinsic width of the

352

adjacent 1D peaks prior to sampling there will be significant re-mixing of even those analytes

353

that were well resolved by the 1D column. Figure 5, which represents a reconstructed 1D

354

chromatogram, indicates the seriousness of these losses. In each case the same mixture of 100

355

randomly distributed components was studied. Figure 5A, in which sampling is quite fast, shows

356

only 51 peaks whereas Fig. 5B, which is at the M-S-F recommended rate of 4 samples per

357

8σ peak width (note – the more conventionally used peak width at half-height (w1/2) is equivalent

358

to 2.35σ) shows only 37 peaks. Upon an additional two-fold decrease in the sampling rate (see

359

Fig. 5C) the peak count decreases to a mere 23. Clearly the 1D separation is being seriously

360

undersampled and much of its resolving power (peak capacity) wasted.

361 1

1

362

Figure 5. Reconstructed D chromatograms that show the effect of undersampling on effective D peak

363

capacity. For a hypothetical sample containing 100 randomly spaced compounds, sampling at a rate of 5

364

samples per σ (ts = 0.2 σ) yields a chromatogram with 51 peaks. Increasing the sampling time to 2 σ

365

(Panel B) or 4 σ (Panel C) yields 37 or 23 peaks, respectively.

1

1

1

1

366


Page 15 of 34

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367

Since the seminal work of Murphy, Schure, and Foley on this problem, several groups have

368

developed more quantitative approaches42–45. In collaboration with Davis we used Monte-Carlo

369

simulations to establish a relationship between the normalized sampling time (i.e., sampling

370

time (ts) relative to the native 1D peak width) and the extent of peak broadening caused by

371

undersampling. This yields an average 1D broadening factor, , which can then be used to

372

calculate a corrected 1D peak capacity that quantitatively accounts for the pernicious effect of

373

undersampling.

t  < β >= 1 + 0.21 1 s   σ

374

1 1

375

nc,corrected =

2

nc

(1)

(2)

376 377

In our view, estimates of the overall 2D peak capacity must include the reduced 1D peak

378

capacity resulting from undersampling43. This is especially true when one seeks to compare the

379

separation power of 1D-LC to LC×LC. Moreover, with this framework in hand, we are in position

380

to rationally approach other important method development, for example how much time should

381

be allotted for each 2D separation, because in the case of online LC×LC separations this is

382

directly linked to the sampling time.

383 384

4.2 Usage of the 2D Separation Space

385

In conventional 1D chromatography it is considered a best practice to use as much of the

386

available separation space (i.e., nominally, the analysis time) for separation of the mixture at

387

hand, and minimize empty space in the chromatogram. Working toward this goal typically

388

involves adjusting the elution conditions such that weakly retained compounds elute near the

389

dead time, strongly retained compounds elute before the end of the analysis, and compounds

390

eluting in the middle are spread out rather than clustered together in narrow regions. In principle

391

these goals also apply in 2D separations, but achieving them is often considerably more difficult.

392

From the point of view of method development, we typically aim to use different separation

393

modes in the two dimensions of a 2D separation such that the analytes in a mixture will

394

distribute themselves differently in the separation spaces of the two dimensions.

395



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Page 16 of 34

396

A useful framework for thinking about the sample and separation modes is Giddings’s concept

397

of sample dimensionality46. Briefly, the idea is to consider the number and type of chemical

398

differences (dimensions) present in a mixture of analytes and then choose two separation

399

modes that are matched to these differences. This idea is best made clear by way of an

400

example. Consider the separation of a mixture of peptides resulting from the enzymatic

401

digestion of proteins. These peptides differ principally in their lipophilicity and charge at a

402

particular pH. The obvious choices for the two LC separation modes are: 1) ion-exchange LC

403

(charge); and 2) reversed-phase (RP) LC (lipophilicity). Once these two modes are chosen one

404

then optimizes the elution conditions in each dimension to arrive at a 2D separation that

405

maximally utilizes the available separation space (See Fig. 6).

406 407

Figure 6. SCX×RPLC separation of peptides from digestion of the monoclonal antibody Herceptin.

408

Adapted from ref. 47.

409 410

Fortunately, there are some analyte mixtures having dimensions of chemical variation that align

411

well with separation modes that are highly compatible as is the case with peptides. Solutes in

412

other mixtures are sufficiently variable in at least two chemical dimensions to lend themselves to

413

2D separation; however, the corresponding separation modes may not be highly compatible.

414

Notable examples among these are the separation of surfactants48–50, polymers7, and some

415

classes of biomolecules51,

416

demonstrated they entail the coupling of two separation modes that require serious

417

compromises in other aspects of performance, such as detection sensitivity (see Section 4.3),

52

. Although very nice separations of such mixtures have been

418 419

Whereas the examples discussed above use most of the 2D separation space (often well above

420

80%), many combinations of separation modes that are very attractive tend to produce 2D

421

separations that do not come close to maximizing usage of the separation space. Quantifying

422

the extent to which the 2D separation space is well used has been a major focus of research

423

over the past decade. Space occupancy metrics range widely in conceptual sophistication and

424

ease of application from simple ‘bin counting’ strategies53, 54 to ecological home-range theory55


Page 17 of 34

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425

and fractal mathematics56. Many of these approaches were recently reviewed by Schure and

426

Davis57. One interesting approach that is quite new was not included in the comparison was the

427

Asterisk Equations metric of Camenzuli and Schoenmakers58. We refer interested readers to

428

Schure and Davis’s work that considered the strengths and weaknesses of these approaches,

429

recognizing that there still is no single approach that is stands out; indeed, they have suggested

430

that a combination of metrics may be the most informative57. Although we do not discuss any of

431

the approaches in detail here, understanding their strengths and weaknesses is quite important,

432

especially for those engaged in developing and optimizing LC×LC methods. Finally, it is

433

important to note here that dynamic adjustment of 2D elution conditions during the course of a

434

2D-LC separation can significantly improve the usage of the 2D separation space for a given

435

pairing of stationary phases59, 60.

436 437

4.3 Detection Sensitivity of 2D-LC Methods

438

All chromatographic methods lead to dilution of the analyte as a result of the entropically driven

439

dispersion of the analyte zone along the column. Because there are two chromatographic steps

440

involved in 2D-LC, dilution is a significantly bigger problem than in 1D-LC. It can be can be

441

ameliorated to some degree using a variety of strategies, but generally speaking it is one of the

442

many compromises we must manage in developing 2D-LC methods. The extent of dilution limits

443

the detection sensitivity of the method. It is evident that the dilution problem is compounded in

444

2D-LC because the analyte zone eluted from the 1D column is further diluted during the 2D

445

separation before being presented to the 2D detector. The seriousness of this problem was

446

discussed in detail by Schure61. Indeed, poor detection sensitivity has historically been a major

447

perceived disadvantage of 2D methods in general, and rightly so in the case of sample limited

448

applications and applications where detection sensitivity is among the more important

449

performance metrics.

450 451

In Schure’s study he made reasonable assumptions about the volume of 1D effluent that could

452

be injected into the 2D column. But this variable – nominally the ratio of volume of 1D effluent

453

injected to the volume of 2D column (more specifically, the volume normalized to the column

454

efficiency) - is a strong determinant of detection sensitivity in 2D-LC. In most situations the

455

maximum volume of 1D effluent that can be injected while yielding acceptable performance of

456

the 2D separation depends strongly on the retention of the analytes in the 2D column in two

457

different eluents: 1) the 2D mobile phase itself; and 2) the 1D effluent. Thinking about the 1D



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Page 18 of 34

458

solvent acting as the 2D eluent is important because once the injected volume of 1D effluent

459

becomes significant relative to the dead volume of the 2D column, the 1D effluent in essence

460

becomes the 2D mobile phase at least for a fraction of the retention time. Two cases must be

461

discerned here: In Case A, the analyte is more strongly retained by the 2D column in the 1D

462

effluent relative to the 2D mobile phase, consequently a relatively large volume of 1D effluent

463

can be injected without compromising the performance of the 2D separation; in Case B, the

464

analyte is less retained in the 1D effluent relative to the 2D mobile phase, consequently only a

465

very little of the

466

compromised by the extra-column broadening at the 2D inlet – this situation rapidly leads to

467

volume overload conditions62,

468

peptides as described above - i.e., IEX followed by RPLC. Here fractions of 1D effluent that are

469

typically entirely aqueous are injected into a reversed-phase column and thus retention of the

470

peptides at the 2D column inlet is very high in the primarily aqueous eluents used in IEX.

471

Volumes of 1D effluent even exceeding the dead volume of the 2D column itself can sometimes

472

be injected without compromising the performance of the 2D separation. Under these conditions

473

there is extensive compression of the analyte band at the column inlet (i.e., the band is

474

focused), which enables us to overcome the volume overload problem. An illustrative example

475

of Case B is coupling of normal phase separation to a reversed-phase separation (see for

476

example ref. 51). In this case analyte retention is very low in the 2D column in the presence of

477

the 1D effluent that is primarily a low polarity organic solvent. This in turn forces the injection of

478

very small volumes of 1D effluent into relatively large 2D columns, and consequently poor

479

detection sensitivity. Sometimes separation modes such as NP- and RP-LC are described as

480

being incompatible. In our view this view is really driven by the need for detection sensitivity – if

481

sensitivity were not a big issue then mode compatibility would be easier to achieve compared to

482

the case where large volumes of 1D effluent must be transferred to the 2D column to provide a

483

detectable amount of analyte.

1

D effluent can be injected before the

2

D separation performance is

63

. The classic example of Case A is the 2D-LC separation of

484 485

Recently we have seen an increase in attention to detection sensitivity in 2D-LC and the

486

development of innovative approaches to improve the compatibility of separation modes

487

perceived as being incompatible, or only moderately compatible. Indeed, a number of papers

488

on the optimization of LC×LC have paid much more attention to the extent of analyte dilution

489

than seen in older work64, 65, 50. This is developing into a body of literature that is too broad and

490

deep to adequately summarize here. Some approaches that have been used to address

491

detection sensitivity and mode compatibility include: 1) online dilution of the 1D eluent stream


Page 19 of 34

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492

with ‘weak solvent’ to focus the analyte zone at the 2D column inlet66,

62

493

modulation to focus the analyte zone prior to its introduction into the 2D column67, 68; 3) use of

494

solid phase trapping media (e.g., pre-columns)66, 69, 50; 4) partial evaporation of the 1D effluent

495

prior to introduction to the 2D column70, 71; and 5) solvent exchange to dramatically change the

496

properties of the analyte matrix from the 1D effluent to some other more desirable solvent72.

497

Among these, the solvent exchange concept of the Schoenmakers group and some of the

498

temperature modulation approaches of Groskreutz and Weber73 are the most recent innovations

499

and show great promise, however they are still in pioneering stages of development. Currently a

500

good strategy is to dilute the 1D effluent with a ‘weak solvent’ prior to injection of the mixture into

501

the 2D column because this combines effectiveness with ease of implementation. Following the

502

initial demonstration of this strategy by Oda and coworkers66 several groups have described

503

LC×LC work with either RPLC or HILIC in the second dimension74, 50, 62. When the 1D effluent is

504

diluted between the exit of the 1D column and the sampling valve, only a simple, low pressure

505

isocratic pump is required because the mixing of the 1D effluent and diluent is done at low

506

pressure, and the composition of the diluent is typically held constant throughout a 2D-LC

507

analysis62. Most examples involve the use of water as the diluent, and focused on improving the

508

peak shape in the 2D column and sensitivity at the 2D detector.

; 2) temperature

509 510

Given that changes in ionization state can have a tremendous effect on selectivity in RP

511

separations53, 75, there is considerable interest in 2D-LC separations using eluents buffered at

512

different pHs in the first and second dimensions76, 77, 47. In our recent work we were concerned

513

not only with the composition of the organic solvent/water mixture, but also the secondary

514

effects of the mismatch in pH levels different enough to cause changes in the ionization state of

515

ionogenic analytes in the two dimensions of a 2D-LC system. We found that the effects of pH

516

mismatch can be even more serious than a mismatch in solvent composition, but the pH

517

problem is easily solved using the dilution strategy and judicious choice of a buffered diluent78.

518 519

5. LC×LC Performance Benchmarks that Reflect the State of the Art

520

When will LC×LC do a better job than 1D-LC? This is a question that all those new to 2D-LC

521

should ask. Using best practices for optimizing LC×LC methods, the Carr, and Heinisch groups

522

carefully compared the effective peak capacities of 1D-LC and LC×LC separations of small non-

523

peptide (Carr) and peptide (Heinisch) mixtures, respectively, using both theoretical calculations

524

and experimental separations. Although the undersampling concept and its implications were



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Page 20 of 34

525

discussed in the preceding section, optimizing the tradeoff between longer 2D analysis times

526

that favor higher 2D peak capacities and the corresponding diminution of 1D peak capacity that

527

results from undersampling is not intuitive. This has been discussed in detail in previous

528

papers79, 3 – we strongly encourage interested readers to look into these issues very carefully.

529

Initial work by the Carr group on separations of extracts of low molecular weight compounds

530

from corn seed showed that LC×LC provided higher peak capacities than did 1D-LC when

531

analysis times exceeded 5-10 min., when a fixed 2D analysis time of 21 s was used32. In a

532

follow-up study where they systematically varied the 2D analysis time, they found that the

533

LCxLC methods were clearly superior to the 1D-LC analysis, provided that the 2D analysis time

534

exceeded 12 s, for all total analysis times exceeding about 5-7 min as measured by both

535

calculated effective peak capacities and the actual number of peaks observed in experimental

536

separations of the corn seed extract30. Figure 7 from their work shows that the numbers of

537

peaks observed in LC×LC separations were maximized with 2D analysis times between 12 and

538

21 s.

539 540

Figure 7. Dependence of the number of peaks observed in LCxLC separations of corn seed extract on

541

the 2D-LC analysis time and the 2D cycle time. 2D Cycle times are: 40 (◊), 21, (○), 12 (∆), and 6 (□) sec.

542

The numbers of peaks observed in 1D-LC separations with the same analysis times are indicated by the

543

filled diamonds. Adapted from ref. 30. The largest number of peaks was observed with the D cycle time

544

is 21 s.

2

545 546

Similar work on peptide separations by the Heinisch group65 gave the results shown in Fig. 8. In

547

this graph the red points indicate experimental peak capacities for 1D-LC separations of

548

peptides taken from the literature, and the blue points indicate experimental peak capacities for

549

online LC×LC separations of peptides by the Heinisch group. If we extrapolate the blue line

550

back to smaller peak capacities we see that the blue line and red curve intersect at an analysis


Page 21 of 34

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551

time of about 40 min. This indicates that 1D-LC should be superior at times shorter than 40 min.

552

and LC×LC should be superior at times longer than 40 min. This crossover time is a bit longer

553

than expected based on previous work with small molecules. However, the dependence of the

554

LC×LC peak capacity on analysis time must trend toward zero at shorter times, thus

555

extrapolation of the line shown leads to an overestimation of the crossover time. A more

556

accurate estimate of this point will require further experimental work in the range of analysis

557

time between 10 and 60 min. Nevertheless, the conclusions of this work are qualitatively

558

consistent with the primary conclusion of the Carr group – that online LC×LC remains superior

559

to 1D-LC at analysis times below 30 min, and that implementation of online LC×LC should not

560

be restricted to applications involving only the most complex samples and the longest analysis

561

times. This conclusion alone should support significant research and development in the area of

562

online LC×LC for the foreseeable future.

563 564

Figure 8. Comparison of effective peak capacities obtained in separations of peptides by 1D-RPLC (open

565

circles) and LC×LC with RP separation in both dimensions (filled circles). Adapted from ref. 65.

566 567

6. Example Applications from Selected Fields

568

The variety of areas where 2D-LC has been used is far too broad to be comprehensively

569

reviewed here. We refer readers interested in specific application areas to recent reviews of 2D-

570

LC in biochemical analysis80, small molecule pharmaceutical analysis6, large molecule

571

pharmaceutical analysis1, analysis of Traditional Chinese Medicines (TCMs)2, and polymer

572

analysis5, 7. Although there is great potential to apply 2D-LC in metabolomics, this area has not

573

developed at this point in time81. In this section we focus on recent applications of 2D-LC that



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Page 22 of 34

574

either demonstrate the state of the art with respect to separation of a particular sample type, or

575

a novel application of 2D-LC to an analytical challenge that had not been addressed in the past.

576

6.1 Peptide Fingerprinting

577

2D-LC has been used very successfully in proteomics for about two decades. These are

578

typically comprehensive type separations, although a variant specific to peptide analysis

579

referred to as MUDPIT82 has been widely used with mass spectrometry as the most common

580

detector. In this context the 2D-LC techniques are mainly investigative tools, focused on

581

untargeted analysis, where the mass spectrometer is relied on for the bulk of the information for

582

identification of peptides, and thus optimization of the 2D-LC separation itself is not a priority.

583

However, with the explosive growth in biopharmaceuticals there has been an increasing need

584

for 2D-LC methods coupled to optical detection (e.g., UV absorbance or fluorescence) that are

585

lower in cost, robust, and quantitatively more precise, with sufficient peak capacity to enable

586

quantification of enzymatic digests of large proteins such as monoclonal antibodies or perhaps

587

mixtures of bio-therapeutic molecules. Sandra and coworkers47 have shown what can be done

588

with current commercial 2D-LC instrumentation to address these needs. Figure 9 shows a

589

LC×LC separation of peptides produced from a tryptic digest of the monoclonal antibody

590

Herceptin. The total analysis time was only 36 min. In this work they demonstrated that the

591

method was sufficiently robust and repeatable that it could be used to tease out very subtle

592

differences between tryptic digests of the Herceptin originator and a candidate biosimilar

593

molecule. This type of methodology undoubtedly has a very bright future.

594 595

Figure 9. LC×LC separation of tryptic peptides from Herceptin. Reversed-phase columns were used in

596

both dimensions, and detection was by absorption of UV light at 214 nm. Reproduced with permission

597

from ref. 47.


Page 23 of 34

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598

6.2 Lipidomics

599

There has been steady growth of applications of 2D-LC in the challenging area of lipidomics3.

600

Recent work has focused on innovations in implementation of 2D-LC, and practical application

601

problems. For example, the Holčapek group has demonstrated the effective use of HILIC

602

separation as the second dimension of 2D separations30 which is rather uncommon. These

603

methods almost exclusively involve the use of quadrupole/time-of-flight (QTOF) mass

604

spectrometric detection to increase selectivity, enable quantitation, and help identify unknown

605

analytes. Sample matrices have ranged from specific tissues targeted in disease biomarker

606

studies to studies aimed at more thoroughly understanding the molecular composition of those

607

tissues. In some cases data have been reported for hundreds of different lipids found by 2D-LC.

608

The recent study of Ouyang and coworkers34 showed the power of modern mLC-LC technology

609

for the characterization of low molecular weight heparins. Heparin is a complex mixture of

610

sulfated O-linked polysaccharides that vary in both the degree of polymerization and monomer

611

composition. Figure 10 from this work shows a result of a mLC-LC separation of a heparin

612

mixture involving a 1D SEC separation of molecules that differ in the degree of polymerization

613

followed by a 2D separation using an ion-pairing RP separation. Each one of the six heartcuts

614

collected from the 1D separation yielded at least 11 easily detected but different polysaccharide

615

species separated by the 2D column. This example shows how hybrid 2D-LC methodologies can

616

be used to enhance the resolving power of LC separation focused on a very specific part of the

617

sample.



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Page 24 of 34

618 619

Figure 10. Multiple heartcutting 2D-LC analysis of low molecular weight heparins. Panel A at left shows

620

the D size-exclusion chromatogram, as well as the regions (grey rectangles) where heartcuts of the

621

major peaks were made and transferred to the D RP column. The corresponding D chromatograms for

622

separations of these fractions are shown in Panel B. Reprinted from ref. 34. Copyright 2015 American

623

Chemical Society.

1

2

2

624 625

6.3 Surfactants and Polymers

626

Aside from proteomics, the other leading application area for 2D-LC over the past two decades

627

has been analyses for surfactants and polymers. The different types of online LC×LC used for

628

polymer analysis, as compared to other methods of polymer separation, were reviewed by

629

Schoenmakers and coworkers83. Recent developments in this area include the use of new

630

stationary phase technologies and higher column operating pressures to decrease overall

631

analysis time by improving the performance of both the 1D and 2D separations84.

632

Since the pioneering work of Murphy, Schure, and Foley demonstrating LC×LC separations of

633

alcohol ethoxylate surfactants49, improvements in the separation of surfactants have benefitted


Page 25 of 34

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634

tremendously from advances in commercially available instrumentation and innovation in the

635

implementation of online 2D separations. For example, the Schmitz group has demonstrated the

636

coupling of online LC×LC and QTOF-MS detection for the separation and identification of more

637

than 100 surfactants varying in chain length and end group functionality (e.g., betaines,

638

sulfonates)48. These separations involved the use of HILIC separations in the first dimension

639

followed by RP separations in the second dimension, and were optimized to enable facile

640

coupling to MS detection without seriously compromising the performance of the 2D separation.

641

Most recently, Gargano, Schoenmakers, and coworkers showed that the use of trapping

642

cartridges in place of open sample loops enables both a decrease in overall analysis time, and

643

improvement in

644

tristryrylphenol ethoxylate phosphate surfactants is shown in Fig. 11. Here again the 1D

645

separation is carried out under HILIC conditions, while a RP separation is used in the second

646

dimension. The use of small (5 mm x 2.1 mm i.d.) trapping cartridges in place of open loops in

647

the valve interface allows the use of higher than normal 1D flow rates to minimize the overall

648

analysis time. Furthermore, sensitivity at the

649

transferred from the 1D column are focused by the trap cartridge before entering the 2D

650

analytical column.

2

D detection sensitivity50.

One of their online LC×LC separations of

2

D detector is improved because analytes

651 652

Figure. 11. LC×LC separation of phosphate tristyrylphenyl ethoxylates using HILIC in the first dimension

653

and RP in the second dimension. Adapted from ref. 50.

654

6.4 Pharmaceuticals

655

With the continued increases in the complexity of pharmaceutical products there are more

656

opportunities to leverage the power of 2D-LC to effectively and efficiently solve analytical



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Page 26 of 34

657

challenges that are otherwise very difficult to address using 1D-LC6. These more complex

658

samples include products containing multiple Active Pharmaceutical Ingredients (APIs) in a

659

single drug product, APIs with multiple chiral centers, and drug products that contain both small

660

and large molecules (e.g. protein drug formulations with surfactant excipients). These present

661

challenges that are difficult if not impossible to solve using single 1D-LC methods. On the other

662

hand, complementary 1D-LC methods can be combined in a single 2D-LC method, dramatically

663

reducing the overall analysis time required to obtain the same information, and reducing

664

demands on instrumentation and operator costs. A instructive example of this is shown in Fig.

665

12 where achiral and chiral separations are combined in a single mLC-LC separation of warfarin

666

and hydroxywarfarin isomers85. This figure shows that neither the achiral nor the chiral

667

separation alone resolve the mixture. However, when the same separation modes are combined

668

in a multiple heartcutting 2D-LC separation, the selectivity of the achiral reversed-phase

669

separation used in the second dimension is highly complementary to the chiral separation used

670

in the first dimension, and provides enough selectivity to quickly resolve those components of

671

the sample that remain unresolved after passing through the 1D column.

672 673

Figure 12. 2D-LC separation of warfarin and hydroxylated isomers. The first dimension involves a chiral

674

stationary phase, and the D separation is achiral. This is a multiple heartcutting application where most

675

of the analytes are resolved by the first dimension, and the second dimension is used to finish the job.

676

Adapted from ref. 85.

2


Page 27 of 34

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677

7. The Future

678

In the past ten years we have witnessed a transition from the use of home-built 2D-LC

679

instruments devoted to the development of the technology and basic research in the field to the

680

dominance of commercially available 2D-LC systems, either off-the-shelf, or with minimal

681

modifications. This is an exciting development in the field, because it puts researchers in a

682

position to focus on using 2D-LC to solve real analytical problems and distribute the resulting

683

methods for broad implementation. Obviously 2D-LC will continue to preside in application

684

areas where it has dominated in the past including proteomics and for certain types of polymer

685

analysis. We also expect to see growth in the use of 2D-LC in metabolomics and for other types

686

of very complex samples, including Traditional Chinese Medicines. All of these applications

687

demand the high peak capacities provided by LC×LC. Currently, however, the most rapid

688

growth in the use of 2D-LC involves the hybrid methodologies, such as multiple heartcutting,

689

and fast LC×LC applied to the analysis of moderately complex mixtures. These applications are

690

being facilitated by continued improvements in the performance and robustness of the

691

instrument components, as well as the ease-of-use of software needed for control of the 2D-LC

692

instrument hardware, and analysis of the large datafiles that result from this type of work.

693

At this time a critical question is whether or not 2D-LC methods will be adopted for use in quality

694

assurance and quality control environments where ease-of-use and robustness of the

695

instrumentation and methods are paramount. In the biopharmaceutical application space it

696

appears that adoption of 2D-LC in QA/QC may now be starting86. If 2D-LC is found to be

697

sufficiently valuable for specific analyses in these environments, then this will undoubtedly

698

accelerate the even wider adoption of the methodology and promote further development of the

699

technique.

700

In spite of recent progress, much more research is needed over the next several years to realize

701

the full potential of 2D-LC as a powerful, yet flexible and accessible analytical methodology.

702

Here we highlight a few key areas where innovation is likely to have the greatest impact.

703

Data Analysis – While algorithms for treating 1D chromatograms have been developed and

704

refined over the past decade, such algorithms for processing 2D chromatograms are much

705

younger and will benefit from further development and refinement. This is especially the case

706

when using mass spectrometric detection, where algorithms are particularly important and

707

effective treatment of the data by manual means is practically impossible.



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Page 28 of 34

708

Enabling Coupling of Complementary Separation Modes – As has been forcefully argued by

709

Schoenmakers and coworkers87, 50, the wider adoption of 2D-LC for routine analyses will require

710

the more effective coupling of highly complementary (i.e., orthogonal) separation modes that

711

allow the greater use of the available 2D separation space. In sections 4.2 and 4.3 we argued

712

that in many cases the ability to couple highly complementary separations is strongly dependent

713

on the demand for high detection sensitivity. If high sensitivity is needed, this currently forces us

714

to couple separation modes that are inherently compatible, such as ion-exchange and RP

715

separations. Coupling complementary RP separations is very attractive for a variety of reasons4,

716

88

717

space on average89. Significant increases in the fractional usage of the separation space will

718

require innovations that enable better coupling of separation modes that historically have been

719

considered as only marginally compatible. Nevertheless, the impact of such innovation would be

720

far reaching - this could lead to the development of a set of universal analytical methods that

721

solve a wide variety of analytical problems by leveraging the high resolving power of 2D-LC with

722

minimal method development. This in turn would relax the demand for users with high level

723

expertise to use 2D-LC effectively.

724

Development of a Base of Expertise – In the current era of ‘doing more with less’, even in R&D

725

laboratories, one must ask how we as a community will develop the expertise needed to fully

726

realize the potential benefits of multi-dimensional separations. As training budgets are slashed

727

and the numbers of educated analytical chemists are reduced we are seeing an erosion in the

728

base of chromatographic expertise across the globe90, even for 1D chromatography. While the

729

solutions to these problems are not obvious to us, it is clear that without users trained in the

730

fundamentals of 2D chromatography even the most sophisticated instruments will be limited in

731

their application to solve real problems.

, but these separations typically enable usage of at best only about 60% of the 2D separation

732 733

Acknowledgements

734

We would like to thank Joe Davis for the contribution of Figure 5, and Gabriel Mazzi Leme for

735

helpful suggestions during the preparation of the manuscript. DS was supported by a Teacher-

736

Scholar Award from the Camille and Henry Dreyfus Foundation.

737 738

References


Page 29 of 34

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


739 (1)

Stoll, D.; Danforth, J.; Zhang, K.; Beck, A. J. Chromatogr. B. 2016, 51–60.

740 (2)

Li, Z.; Chen, K.; Guo, M.; Tang, D. J. Sep. Sci. 2016, 39, 21–37.

741 (3)

Stoll, D. R. Bioanalysis. 2015, 7, 3125–3142.

742 (4)

Li, D.; Jakob, C.; Schmitz, O. Anal. Bioanal. Chem. 2014, 407, 153–167.

743 (5)

Kilz, P.; Radke, W. Anal. Bioanal. Chem. 2015, 407, 193–215.

744 (6)

Zhang, K.; Wang, J.; Tsang, M.; Wigman, L.; Chetwyn, N. Am. Pharm. Rev. 2013.

745 (7)

Schoenmakers, P.; Aarnoutse, P. Anal. Chem. 2014, 86, 6172–6179.

746 (8) 747

Mondello, L., Ed. Comprehensive Chromatography in Combination with Mass Spectrometry, 1st ed.; Wiley; 2011.

748 (9) 749 750

Cohen, S. A.; Schure, M. R., Eds. Multidimensional liquid chromatography: theory and applications in industrial chemistry and the life sciences, Wiley-Interscience: Hoboken, N.J; 2008.

751 (10)

Marriott, P. J.; Schoenmakers, P. J.; Wu, Z. LCGC Eur. 2012, 266, 268, 270, 272–275.

752 (11)

Giddings, J. C. Anal Chem. 1967, 39, 1027–1028.

753 (12) 754

Snyder, L. R.; Kirkland, J. J.; Dolan, J. W. In Introduction to modern liquid chromatography; Wiley: Hoboken, N.J, 2010; p. 591.

755 (13) 756

Snyder, L. R.; Kirkland, J. J.; Dolan, J. W. In Introduction to modern liquid chromatography; Wiley: Hoboken, N.J, 2010; pp. 430–434.

757 (14)

Davis, J. M.; Giddings, J. C. Anal. Chem. 1983, 55, 418–424.

758 (15)

Mao, Y.; Carr, P. W. Anal. Chem. 2000, 72, 110–118.

759 (16) 760


761 (17) 762 763

Pellett, J.; Lukulay, P.; Mao, Y.; Bowen, W.; Reed, R.; Ma, M.; Munger, R. C.; Dolan, J. W.; Wrisley, L.; Medwid, K.; Toltl, N. P.; Chan, C. C.; Skibic, M.; Biswas, K.; Wells, K. A.; Snyder, L. R. J. Chromatogr. A. 2006, 1101, 122–135.

764 (18) 765 766

Schure, M.; Cohen, S. A., Eds. In Multidimensional liquid chromatography: theory and applications in industrial chemistry and the life sciences; Wiley-Interscience: Hoboken, N.J, 2008; pp. 91–126.

767 (19) 768

Francois, I.; Sandra, K.; Sandra, P. In Comprehensive Chromatography in Combination with Mass Spectrometry; Wiley, 2011; pp. 281–330.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

769 (20)

Kalili, K. M.; de Villiers, A. J. Chromatogr. A. 2013, 1289, 58–68.

770 (21) 771

Guiochon, G.; Marchetti, N.; Mriziq, K.; Shalliker, R. J. Chromatogr. A. 2008, 1189, 109– 168.

772 (22) 773

Simpkins, S. W.; Bedard, J. W.; Groskreutz, S. R.; Swenson, M. M.; Liskutin, T. E.; Stoll, D. R. J. Chromatogr. A. 2010, 1217, 7648–7660.

774 (23)

Moore, A. W.; Jorgenson, J. W. Anal. Chem. 1995, 67, 3456–3463.

775 (24) 776

Davydova, E.; Schoenmakers, P. J.; Vivó-Truyols, G. J. Chromatogr. A. 2013, 1271, 137– 143.

777 (25) 778

Wouters, B.; De Vos, J.; Desmet, G.; Terryn, H.; Schoenmakers, P. J.; Eeltink, S. J. Sep. Sci. 2015, 38, 1123–1129.

779 (26)

Apffel, J. A.; Alfredson, T. V.; Majors, R. E. J. Chromatogr. A. 1981, 206, 43–57.

780 (27)

Kuehnbaum, N. L.; Britz-McKibbin, P. Chem. Rev. 2013, 113, 2437–2468.

781 (28)

Wu, Q.; Yuan, H.; Zhang, L.; Zhang, Y. Anal. Chim. Acta. 2012, 731, 1–10.

782 (29)

Adahchour, M.; Beens, J.; Brinkman, U. A. T. J. Chromatogr. A. 2008, 1186, 67–108.

783 (30)

Huang, Y.; Gu, H.; Filgueira, M.; Carr, P. W. J. Chromatogr. A. 2011, 1218, 2984–2994.

784 (31)

Potts, L. W.; Carr, P. W. J. Chromatogr. A. 2013, 1310, 37–44.

785 (32)

Stoll, D. R.; Wang, X.; Carr, P. W. Anal. Chem. 2008, 80, 268–278.

786 (33)

Zhang, K.; Li, Y.; Tsang, M.; Chetwyn, N. P. J. Sep. Sci. 2013, 36, 2986–2992.

787 (34) 788

Ouyang, Y.; Zeng, Y.; Rong, Y.; Song, Y.; Shi, L.; Chen, B.; Yang, X.; Xu, N.; Linhardt, R. J.; Zhang, Z. Anal. Chem. 2015, 87, 8957–8963.

789 (35)

Pursch, M.; Buckenmaier, S. Anal. Chem. 2015, 87, 5310–5317.

790 (36) 791

Larson, E. D.; Groskreutz, S. R.; Harmes, D. C.; Gibbs-Hall, I.; Trudo, S. P.; Allen, R. C.; Rutan, S. C.; Stoll, D. R. Anal. Bioanal. Chem. 2013, 405, 4639–4653.

792 (37)

Davis, J. M.; Stoll, D. R. J. Chromatogr. A. 2014, 1360, 128–142.

793 (38)

Horváth, K.; Fairchild, J. N.; Guiochon, G. J. Chromatogr. A. 2009, 1216, 2511–2518.

794 (39)

Giddings, J. C. J. High Resolut. Chromatogr. 1987, 10, 319–323.

795 (40)

Murphy, R. E.; Schure, M. R.; Foley, J. P. Anal. Chem. 1998, 70, 1585–1594.

796 (41)

Giddings, J. C. Anal. Chem. 1984, 56, 1258A–1270A.


Page 30 of 34

Page 31 of 34

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


797 (42)


798 (43)

Davis, J. M.; Stoll, D. R.; Carr, P. W. Anal. Chem. 2008, 80, 461–473.

799 (44)

Seeley, J. J. Chromatogr. A. 2002, 962, 21–27.

800 (45) 801

Horie, K.; Kimura, H.; Ikegami, T.; Iwatsuka, A.; Saad, N.; Fiehn, O.; Tanaka, N. Anal. Chem. 2007, 79, 3764–3770.

802 (46)

Giddings, J. C. J. Chromatogr. A. 1995, 703, 3–15.

803 (47) 804

Vanhoenacker, G.; Vandenheede, I.; David, F.; Sandra, P.; Sandra, K. Anal. Bioanal. Chem. 2015, 407, 355–366.

805 (48) 806

Elsner, V.; Laun, S.; Melchior, D.; Köhler, M.; Schmitz, O. J. J. Chromatogr. A. 2012, 1268, 22–28.

807 (49)


808 (50) 809

Gargano, A. F. G.; Duffin, M.; Navarro, P.; Schoenmakers, P. J. Anal. Chem. 2016, 88, 1785–1793.

810 (51) 811

Dugo, P.; Favoino, O.; Luppino, R.; Dugo, G.; Mondello, L. Anal. Chem. 2004, 76, 2525– 2530.

812 (52)

Kalili, K. M.; Vestner, J.; Stander, M. A.; de Villiers, A. Anal. Chem. 2013, 85, 9107–9115.

813 (53)

Gilar, M.; Olivova, P.; Daly, A. E.; Gebler, J. C. Anal. Chem. 2005, 77, 6426–6434.

814 (54)

Davis, J. M.; Stoll, D. R.; Carr, P. W. Anal. Chem. 2008, 80, 8122–8134.

815 (55)

Rutan, S. C.; Davis, J. M.; Carr, P. W. J. Chromatogr. A. 2011, 1255, 267–276.

816 (56)

Schure, M. R.; Davis, J. M. J. Chromatogr. A. 2011, 1218, 9297–9306.

817 (57)

Schure, M. R.; Davis, J. M. J. Chromatogr. A. 2015, 1414, 60–76.

818 (58)

Camenzuli, M.; Schoenmakers, P. J. Anal. Chim. Acta. 2014, 838, 93–101.

819 (59)

Bedani, F.; Kok, W. T.; Janssen, H.-G. Anal. Chim. Acta. 2009, 654, 77–84.

820 (60)

Jandera, P.; Hájek, T.; Česla, P. J. Sep. Sci. 2010, 33, 1382–1397.

821 (61)

Schure, M. R. Anal. Chem. 1999, 71, 1645–1657.

822 (62) 823

Stoll, D. R.; Talus, E. S.; Harmes, D. C.; Zhang, K. Anal. Bioanal. Chem. 2014, 407, 265– 277.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

824 (63) 825

Jeong, L. N.; Sajulga, R.; Forte, S. G.; Stoll, D. R.; Rutan, S. C. J. Chromatogr. A. 2016, 1457, 41–49.

826 (64)

Vivó-Truyols, G.; van der Wal, S.; Schoenmakers, P. J. Anal. Chem. 2010, 82, 8525–8536.

827 (65)

Sarrut, M.; D’Attoma, A.; Heinisch, S. J. Chromatogr. A. 2015, 1421, 48–59.

828 (66) 829

Oda, Y.; Asakawa, N.; Kajima, T.; Yoshida, Y.; Sato, T. J. Chromatogr. A. 1991, 541, 411– 418.

830 (67)

Sweeney, A.; Shalliker, R. J. Chromatogr. A. 2002, 968, 41–52.

831 (68) 832

Verstraeten, M.; Pursch, M.; Eckerle, P.; Luong, J.; Desmet, G. Anal. Chem. 2011, 83, 7053– 7060.

833 (69) 834

Venkatramani, C. J.; Al-Sayah, M.; Li, G.; Goel, M.; Girotti, J.; Zang, L.; Wigman, L.; Yehl, P.; Chetwyn, N. Talanta. 2016, 148, 548–555.

835 (70)

Ding, K.; Xu, Y.; Wang, H.; Duan, C.; Guan, Y. J. Chromatogr. A. 2010, 1217, 5477–5483.

836 (71)

Tian, H.; Xu, J.; Xu, Y.; Guan, Y. J. Chromatogr. A. 2006, 1137, 42–48.

837 (72) 838

van de Ven, H. C.; Gargano, A. F. G.; van der Wal, S.; Schoenmakers, P. J. J. Chromatogr. A. 2016, 1427, 90–95.

839 (73)

Groskreutz, S. R.; Weber, Stephen G. J. Chromatogr. A. 2014, 1354, 65–74.

840 (74)

Li, D.; Dück, R.; Schmitz, O. J. J. Chromatogr. A. 2014, 1358, 128–135.

841 (75) 842


843 (76)

Gilar, M.; Olivova, P.; Daly, A. E.; Gebler, J. C. J. Sep. Sci. 2005, 28, 1694–1703.

844 (77) 845

François, I.; Cabooter, D.; Sandra, K.; Lynen, F.; Desmet, G.; Sandra, P. J. Sep. Sci. 2009, 32, 1137–1144.

846 (78)

Stoll, D. R.; O’Neill, K.; Harmes, D. C. J. Chromatogr. A. 2015, 1383, 25–34.

847 (79)

Bedani, F.; Schoenmakers, P. J.; Janssen, H.-G. J. Sep. Sci. 2012, 35, 1697–1711.

848 (80)

de Villiers, A.; Venter, P.; Pasch, H. J. Chromatogr. A. 2016, 1430, 16–78.

849 (81) 850

Willmann, L.; Erbes, T.; Krieger, S.; Trafkowski, J.; Rodamer, M.; Kammerer, B. Anal. Bioanal. Chem. 2015, 407, 3555–3566.

851 (82)

Wolters, D. A.; Washburn, M. P.; Yates, J. R. Anal. Chem. 2001, 73, 5683–5690.

852 (83)

Uliyanchenko, E.; van der Wal, S.; Schoenmakers, P. J. Polym. Chem. 2012, 3, 2313.


Page 32 of 34

Page 33 of 34

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


853 (84) 854

Uliyanchenko, E.; Cools, P. J. C. H.; van der Wal, S.; Schoenmakers, P. J. Anal. Chem. 2012, 84, 7802–7809.

855 (85)

Regalado, E. L.; Schariter, J. A.; Welch, C. J. J. Chromatogr. A. 2014, 1363, 200–206.

856 (86) 857

Largy, E.; Catrain, A.; Van Vyncht, G.; Delobel, A. Curr. Trends Mass Spectrom. 2016, 14, 29–35.

858 (87)

Pirok, B. W. J.; Knip, J.; van Bommel, M. R.; Schoenmakers, P. J. J. Chromatogr. A. 2016.

859 (88) 860

Stoll, D. R.; Li, X.; Wang, X.; Carr, P. W.; Porter, S. E. G.; Rutan, S. C. J. Chromatogr. A. 2007, 1168, 3–43.

861 (89) 862

Allen, R. C.; Barnes, B. B.; Haidar Ahmad, I. A.; Filgueira, M. R.; Carr, P. W. J. Chromatogr. A. 2014, 1361, 169–177.

863 (90) 864 865

Regalado, E. L.; Kozlowski, M. C.; Curto, J. M.; Ritter, T.; Campbell, M. G.; Mazzotti, A. R.; Hamper, B. C.; Spilling, C. D.; Mannino, M. P.; Wan, L.; Yu, J.-Q.; Liu, J.; Welch, C. J. Org. Biomol. Chem. 2014, 12, 2161.

866 867



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254x190mm (96 x 96 DPI)


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Two-Dimensional Liquid Chromatography: A State of the Art Tutorial

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