The 16th Desty Memorial Lecture for Innovation In Separation Science

 will take place in its established home of the Royal Institution of Great Britain on 

The Royal Institution is used for this gathering, as this was the building that Denis Desty enjoyed above all others. He, like other great scientists, enjoyed the dissemination of science to the widest possible audience and was inspired by the Royal Institution of Great Britain and how for the past two hundred years the institution has been at the centre of scientific research and the popularization of science in England. Within its walls, some of the major scientific discoveries of the last two centuries have been made. These include the discovery of sodium and potassium by Humphry Davy, electromagnetic induction by Michael Faraday, why the sky is blue by John Tyndall, the liquefaction of hydrogen by James Dewar, the structure of benzene by Kathleen Lonsdale under William Henry Bragg and the first enzyme to have its structure determined by David Chilton Phillips under William Lawrence Bragg. 

Denis was a passionate communicator and took every opportunity possible to pass on his knowledge and enthusiasm for science. He presented his famous 'Flames are Fun' lecture at the Royal Institution in December 1989, and so fulfilled a much-cherished ambition by standing in the same 'sacred' place as one of his heroes, Michael Faraday. 

This year the meeting is dedicated to Raymond Peter William Scott, better known as Ray Scott, who died on 12 February this year aged 86. Ray published over 200 original papers on separation technology. He invented the flame thermocouple detector, the forerunner of the flame ionization detector, pioneered the development of high efficiency packed columns and with A.T. James developed the moving wire detector for liquid chromatography. In 1988 was supposed to retire, but in effect he was working and motivating students until his death. He authored 14 books, all on separation technology, and received numerous awards for his work in chromatography. He — together with his friend Denis Desty — was a founding member of the Chromatography Discussion Group. 

This year lectures will be given in honour of Ray by Paul Haddad (University of Tasmania); Ron Majors (Agilent) Pat Sandra (Research Institute for Chromatography) Chris Pohl (Dionex); Kevin Wyndham (Waters); and Jeremy Glennon (University of Cork). 

The Royal Institution will open for registration and coffee at 9:30 am with the lectures starting at 10:30 am until 4:30 pm 

 are free, but as the Royal Institutions main lecture theatre can only hold 250 people tickets will be allocated on a first booked allocation.The latest update on the lecture can be found at 

 To obtain tickets and for further information contact: Peter Myers, Department of Chemistry, University of Liverpool, Liverpool L69 7ZQ, UK. Tel: +44 151 795 2386, E-mail: 

Clarion Congress Hotel Prague, Prague, Czech Republic

 Institute of Chemical Technology, Czech Republic and RIKILT — Institute of Food Safety, The Netherlands 

CE Method Development and Validation Course

Oud-Sint-Jan' Conference Center, Bruges, Belgium

 Royal Flemish Chemical Society and Royal Society of Chemstry

36th International Symposium on Capillary Chromatography (Riva 2012) and 9th GC

 Luigi Mondello, Chromaleont, University of Messina, Italy 

Send any event news to Alasdair Matheson at 

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Properly informed column selection greatly simplifies the process of method development and provides greater flexibility in instrument settings for comprehensive two-dimensional gas chromatography (GC

GC) with fluidic modulation. In the present investigation a long (20 m) narrow-bore (0.10 mm i.d.) column was used in the first separation dimension. In this way, the separation column itself provided sufficient pressure-drop to alleviate flow disturbance in the first dimension column caused by actuating the modulator valve. The use of a narrow-bore column in the first dimension is highly beneficial because it is also more suited to lower volumetric flow-rates and therefore permits use of a longer modulation period without causing sample loop breakthrough. Enantioselective separation of spearmint essential oil was performed to demonstrate performance of a fluidic modulation system. 

Environmental monitoring in remote areas is of great interest and we have been working to determine the suitability of comprehensive two-dimensional gas chromatography (GC×GC) for this task. Conventional GC×GC instrumentation, which relies on thermal modulation (1), is not ideally suited for use in remote field laboratories, thus alternative modulation approaches have been investigated. One of these approaches is based on fluidic modulation, which was introduced by Seeley and co-workers in 2006 (2). The basic architecture of this fluidic modulation approach has been used in the design of the Agilent CFT Modulator (Agilent Technologies, Santa Clara, California, USA) (3). It is worth noting that the specific dimensions of the channels in the CFT device are not necessarily identical to those described by Seeley et al., but the fundamental approach is consistent. The monolithic structure of the CFT modulator and its use of leak-free SilTite ferrules (SGE Analytical Science, Ringwood, Australia) offer several advantages over homemade fluidic modulators. Notwithstanding, many investigators have found fluidic modulation using this device to be less than satisfactory and the limited number of publications using the technology may be partially ascribed to the difficulty in determining rugged modulation conditions.There are a few key considerations to optimizing GC×GC instrument settings for fluidic modulation. Some of these considerations are unique to the fluidic modulation and others are more generally applicable to GC×GC. Starting with the general considerations, a wide body of literature indicates that it is highly desirable to maintain a suitable modulation ratio (4). There is a rule of thumb [which has sound theoretical and practical underpinnings (5)] that suggests there should be four modulation slices across each first dimension peak. This rule of thumb ensures that peak capacity of the first dimension separation is not too greatly diminished by the modulation process. It is also highly desirable to minimize the extent of wraparound (6). Thus the elution window in the second dimension should not significantly exceed the modulation period. When the modulation period is exceeded there can be detrimental effects on resolution in the second separation dimension. There is often a practical compromise of each of these criteria, but the best GC×GC results typically come from carefully optimized systems that adhere strictly to both considerations. Stationary phase selection is a key consideration for all GC×GC approaches. Such considerations are addressed in detail elsewhere (7).  

Among the important specific considerations for fluidic modulation, the critical consideration is that proper pneumatic conditions are applied in order to:   

ensure stop-flow modulation (at point X in Figure 1).

provide sufficient time to sweep the modulator sample loop (Figure 1)

prevent breakthrough from the sample loop during the modulation cycle.  

Figure 1: Plan of a fluidic modulator, showing the sample loop (L), 3-way switching valve (V), connecting tubing and the connecting points of the first (Col 1) and second (Col 2) dimension columns.  

In addition, a large volumetric flow ratio (column 2:column 1) has to be applied to assist peak-compression-in-time, which reduces the injection bandwidth into the second dimension column. Typically this flow ratio needs to be 10:1 or higher (8).  

Maintaining appropriate pneumatic conditions, whilst satisfying the general considerations described above can be troublesome. An example drawn from the literature of fatty acid methyl esters analysis using fluidic modulation is shown in Figure 2 (9). In this example the instrument set-up comprised a first dimension separation column that had dimensions 30 m × 0.25 mm coupled to a second dimension separation column with dimensions 2 m × 0.25 mm. The film thickness of each column was 0.25 μm. The authors employed a column ensemble in which the first dimension column was coated with a 70% cyanopropyl polysilphenylene-siloxane stationary phase and the second dimension column was coated with a 5% polysilarylene/95% polydimethylsiloxane copolymer stationary phase. The most striking feature of this chromatogram is how the broad second dimension peaks sometimes fill the entire 

-axis. The peak capacity of the second dimension is less than 1 in some places. The observed low performance may be a result of modulator breakthrough, incomplete flushing or a combination of both. These undesirable effects can be eliminated by informed column choice, along with appropriate instrument settings.  

Figure 2: GCÃGCâFID 2D chromatogram of the standard mixture of 45 FAMEs (Reference 9, with permission). 

The primary argument of the present article is that 

properly informed column choice greatly simplifies the process of method development

 and gives greater flexibility in instrument settings for fluidic modulation. Previously, Harvey et al. showed that is was possible to increase the modulation period to at least 9 s without adverse chromatographic affects (8) using a homemade fluidic modulation device. In the present investigation, the principles reported in earlier studies (8,10) have been applied with a CFT fluidic modulator. Enantioselective analysis of essential oils offers a good illustrative example of the benefit of multidimensional separations.  

There are two options for performing enantioselective GC×GC separations. First, it is possible to follow the path laid by the myriad heart-cut 

-MDGC applications for essential oils analysis (11) and use an achiral first dimension column coupled to an enantioselective stationary phase column in the second dimension. However, practical implementation of this approach is obstructed by the need for rapid second-dimension separations (12). The preferred approach is to use an enantioselective stationary phase column in the first dimension and follow this separation with one performed using an achiral stationary phase in the second dimension (13). The results from enantioselective GC×GC analysis of spearmint essential oil are presented here to highlight suitability of a fluidic modulation system for this dedicated application. 

Enantioselective GC×GC analysis of spearmint essential oil was performed using an Agilent 7890A GC×GC instrument with CFT modulator and flame ionization detector (Agilent Technologies). The first dimension column was a 20 m × 0.10 mm i.d. capillary coated with a thin film (0.1 μm) of diethyl-t-butylsilyl β cyclodextrin in PS-086 stationary phase (Mega, Legnana, Milan, Italy). The first dimension column was connected to the CFT device using a SilTite ferrule (SGE Analytical Science, Victoria, Australia). The second dimension column was a 5 m × 0.25 mm i.d. capillary coated with a thin film (0.15 μm) of polyethylene glycol stationary phase (Agilent Technologies). The second column was connected to the CFT device using a SilTite ferrule. Carrier gas (H

) was supplied at a flow-rate of 0.4 mL/min (constant flow) in the first dimension from the split/splitless injector and 20 mL/min (constant flow) in the second dimension using the auxiliary pressure controller. The detector temperature was 280 °C and the injector was 230 °C. The injection volume was 1.0 μL throughout and a split ratio of 20:1 was employed for all analyses.  

For qualitative comparison purposes, GC×GC analyses were also performed using a Shimadzu GC×GC system consisting of two independent GC2010 gas chromatographs, and a QP2010 Plus quadrupole mass spectrometer (Shimadzu, Kyoto, Japan). Data were acquired using the GCMS solution software (Shimadzu). The two GC ovens were linked through a heated (280 °C) transfer line. The primary GC (GC1) was equipped with an AOC-20i auto-injector and a split-splitless injector (280 °C). The first dimension column was a 25 m × 0.25 mm i.d. capillary coated with a thin film (0.25 μm) of diethyl-t-butylsilyl β cyclodextrin in PS-086 stationary phase (Mega). The second dimension column was a 1 m × 0.05 mm i.d. capillary coated with a thin film (0.25 μm) of polyethylene glycol stationary phase (Supelco). A modulator loop was formed using a 2 m × 0.25 mm i.d. uncoated column that was first passed through the heated transfer line between the two GC instruments. A dual-stage loop-type modulator (under license from Zoex Corporation, Houston, Texas, USA) was used for GC×GC analyses. The modulation period was 4 s and the duration of the hot pulse (325 °C) was 375 ms. Helium carrier gas was used at a constant flow-rate of 0.5 mL/min. 

Harvey and co-workers showed by modelling the flow of carrier gas in a fluidic modulator that there is a distinct advantage of using a restrictor immediately before the sample loop (8). It is a critical performance criterion that the flow from the first dimension column is "stopped", otherwise modulation will be ineffective and the two separation columns will not be properly decoupled to permit GC×GC separation. However it is widely recognized that stop-flow is not a realistic expectation when the modulator valve is actuated. Instead, the direction of flow is reversed briefly upon valve actuation and the subsequent raising of the first dimension column outlet pressure. If the first dimension column has a low resistance to flow, then the direction of flow is affected along a significant length of the column. By using a restrictor column, with high resistance to flow, flow modelling showed that perturbation of flow in the first dimension separation column is limited to within the restrictor column. Practical implementation agreed with predicted enhanced modulator effectiveness (8).  

Figure 3: Experimental H/u curve justifies use of low first dimension flow rate. Plate height (H) was measured for n-C12 at 140 Â°C using calculated volumetric flow rates between 0.07 mL/min and 0.5 mL/min (H2). 

In the present investigation the restrictor column (along with the corresponding connection in the GC×GC column ensemble) was eliminated and a long (20 m) narrow-bore (0.10 mm i.d.) column was used in the first separation dimension. In this way, the separation column itself provides sufficient pressure-drop to reduce flow disturbance in the first dimension and restrict the perturbation to a short length of the column. Using narrow-bore columns in the first dimension provides further benefit because their optimal performance is achieved at lower volumetric flow-rates (compared with wider-bore capillaries) and therefore permit use of a longer modulation period without causing sample loop breakthrough. To this end, it is interesting to determine how low the volumetric flow-rate can be without causing significant longitudinal diffusion and subsequent increase in plate height. The optimal carrier gas flow-rate is easily determined using the teachings of Blumberg and Klee (14) and a number of flow calculation software options are readily available for determining optimal pneumatic conditions in GC. Blumberg and Klee discuss two optimal pneumatic conditions, namely the efficiency optimized flow (EOF) and the speed optimized flow (SOF), which is higher than the EOF. In the present investigation the authors were interested in establishing a threshold lower than the EOF. Although using a sub-optimal flow-rate is generally considered foolish, for the specific case of fluidic modulation GC×GC, this compromise may be worthwhile if it improves the ruggedness of the instrument settings. It is a common belief that even a small departure from the default instrument settings for the CFT device can lead to sub-optimal modulation. Thus a series of injections were performed using an Agilent 6850 GC instrument (Agilent Technologies) to determine plate height (H) at different volumetric flow-rates for a 20 m × 0.10 mm i.d. Rtx-5 (0.10 μm d

) column (Restek, Bellefonte, Pennsylvania, USA). Carrier gas (H

) was provided via the split/splitless injector. The detector temperature was 280 °C and the injector was 230 °C. Plate height was measured for 

-C12 at 140 °C (k ~ 3) using calculated volumetric flow-rates between 0.07 mL/min and 0.5 mL/min (H

) corresponding to a linear velocity range spanning 

 32 cm/s using the 20 m column. The mean results (n = 3) are summarized in Figure 3. The 

/u curve is remarkably flat between 0.2–0.5 mL/min (H

) so using flow-rates as low as 0.2 mL/min in a GC×GC setup is justifiable. Low first dimension flow-rates are further justified, as the injection bandwidth (

) into the second dimension column is a function of the modulation period (

) and the flow ratio according to equation 1. Thus using a low first dimension column flow-rate may lead to improved observed performance in the second separation dimension by minimizing extra-column broadening in the second dimension separation column (10).   

F are the first- and second-dimension volumetric flow-rates respectively. 

The dimensions of the internal sample loop in the CFT modulator are unknown, so optimization of instrument settings was performed by iterative approaches in the present investigation.  

Figure 4: Two-dimensional separation space for the GCÃGC separation of spearmint essential oil using fluidic modulation. Refer to Table 1 for peak identities. 

Essential oil analysis is made difficult by the wide dynamic range of the essential oil components. Spearmint essential oil is comprised of mono- and sesquiterpene hydrocarbons as well as mono- and sesquiterpene alcohols. Thus the sample components span a relatively wide volatility range and exhibit substantially different retention characteristics; consequently a relatively long modulation period is required to obtain a meaningful separation. In the present investigation, meaningful separation is achieved by extending the second dimension separation window to 3 s. While it could be argued that increasing the oven temperature would compress the second dimension elution window, this leads to a substantial loss of resolution in the second dimension column and should be avoided if possible. Figure 4 illustrates the GC×GC separation space from the fluidic modulation GC×GC system and the corresponding chromatogram from a thermal modulation GC×GC experiment is shown in Figure 5.   

Although the two-dimensional peak capacity from the thermal modulation experiment is notably greater than that achieved by fluidic modulation, both results are highly satisfactory. A detailed comparison of the two approaches is beyond the scope of this discussion and the authors have not made any attempt to closely match the retention times in each system, but this comparison does permit one to draw an important conclusion; that appropriate column selection brings fluidic modulation into genuine contention as an alternative to thermal modulation GC×GC. A 3 s separation window provides adequate space with minimal wrap-around for separation of the terpenoid compounds present in the spearmint essential oil sample and the present column ensemble and flow arrangement easily permits a 3 s modulation period. 

Figure 5: Two-dimensional separation space for the GCÃGC separation of spearmint essential oil using thermal modulation. Refer to Table 1 for peak identities. 

Identification of the sample components was performed by GC×GC–MS and confirmed by injection of authentic reference standards; the identities of the separated components are reported in Table 1. Thirty-five terpenoid compounds were positively identified in the two-dimensional separation space. Extensive characterization was not attempted, although several other sample components were well resolved. Among the separated components, the individual optical isomers, including β-pinene, limonene, sabinene and terpinen-4-ol were resolved, both from one-another and from interfering sample components.  

Authentic reference standards of sufficient purity to perform quantitative analysis were available for three of these chiral compounds. Triplicate analyses were performed to determine retention time repeatability of using the fluidic modulation GC×GC approach, and to determine enantiomeric ratio of the resolved pairs. Retention time precision was outstanding; in fact  the percentage relative standard deviaition (%RSD) for second dimension retention time was not greater than 0.45% for any of the target peaks in either separation dimension. Mean second dimension times (n = 3), and 95% confidence interval for (+)-β-pinene, (–)-limonene and (+)-terpinen-4-ol were: 0.815 ± 0.000 s, 0.849 ± 0.001 s and 1.250 ± 0.003 s respectively. Mean second dimension times (n = 3), and 95% confidence interval for (–)-β-pinene, (+)-limonene and (–)-terpinen-4-ol were: 0.810 ± 0.001 s, 0.825 ± 0.000 s and 1.277 ± 0.007 s respectively. Mean first dimension times (n = 3), determined from the retention time of the tallest modulation slice for (+)-β-pinene, (–)-limonene and (+)-terpinen-4-ol were: 5.75 min, 8.10 min and 14.30 min respectively. For (–)-β-pinene, (+)-limonene and (–)-terpinen-4-ol, the recorded first dimension retention times were: 5.90 min, 8.50 min and 14.55 min respectively. These results demonstrate the outstanding run-to-run repeatability using fluidic modulation, with the peak maxima being almost perfectly overlaid. Repeatability of quantitative analysis was also highly satisfactory. The mean results (n = 3) of enantiomeric ratio determination for these three pairs of enantiomers are summarized in Table 2.  

Excellent repeatability of the quantitative determination of enantiomeric ratio for these three pairs of optical isomers highlights the modulation performance. Without proper modulation the results would be compromized. In particular, unpredictable modulator breakthrough has been avoided by appropriate first dimension column selection. It would be impossible to realise this level of repeatability if sub-optimal modulation were employed. Carveol, (peak 23, Figure 4) is characterized by an obvious streaky appearance in the second dimension, however, this behaviour is also apparent in the separation using the cryogenic modulator (Figure 5) so it is postulated that this observation is not caused by fluidic modulation. In addition an extended tail of the corresponding peak is only observed in the cryogenic system. Marriott and co-workers (15), along with Beens et al. (16) have previously highlighted similar behaviour with GC×GC systems, putting this observed behaviour down to injector effects. Haglund et al. (17) ascribed the peak tailing to a modulation-induced effect. In the present investigation it is apparent that the primary cause is indeed a result of applying the cryogen. 

Appropriate pneumatic conditions for fluidic modulation are readily achieved using long, narrow-bore columns in the first dimension of a comprehensive multidimensional GC column ensemble for fluidic modulation. By using long, narrow-bore columns operated at low volumetric flow-rates, favourable modulation period (without breakthrough) for complex multicomponent samples is readily achievable. Since narrow-bore columns provide high resistance to flow, their use also leads to effective stop-flow modulation and streaks in the two-dimensional separation space caused by ineffective modulation are easily avoided. Long columns (i.e., greater then 10 m) are best suited because they maintain optimal modulation ratio without having to resort to very short modulation period. Although narrow-bore columns have lower mass loadability than their wider-bore counterparts, the authors feel that the simplification of determining rugged pneumatic conditions and modulator timing parameters leading to the general benefits of GC×GC outweigh this negative characteristic. 

Associate Professor Shellie is the recipient of an Australian Research Council Australian Research Fellowship (ARF) (project number DP110104923). This research was supported under Australian Research Council's Discovery Projects funding scheme (project number DP0771893), Australian Antarctic Science Grant 2930 and the University of Tasmania Rising Stars Program. The authors wish to thank Professor Luigi Mondello and co-workers at University of Messina for assisting with cryogenic modulation analysis. 

 has been a member of ACROSS at University of Tasmania since 2005. He leads a research group that focuses on development and application of hyphenated techniques in chromatography to solve complex separation problems. 

 are PhD candidates at University of Tasmania. 

http://www.chem.agilent.com/en-US/Products/Instruments/gc/techniques/capillaryflowtechnologygcxgcflowmodulator/pages/default.aspx

4. W. Khummueng, J. Harynuk and P. Marriott, 

5. R.E. Murphy, M.R. Schure and J.P. Foley, 

6. P. Schoenmakers, P. Marriott and J. Beens, 

8. P.McA. Harvey, R.A. Shellie and P.R. Haddad, 

11. R.A. Shellie, Volatile components of plants, essential oils, and fragrances, in 

, L. Ramos (Ed) Elsevier (2009) pp. 189–213. 

Coupling Matters

Describes a novel approach for the enantioselective separation of spearmint oil incorporating a fluidic modulation system.

GCxGC with Fluidic Modulation on Enantioselective Oil Analysis

Headspace sampling for gas chromatography (HSGC) prevents nonvolatile residue accumulation in the inlet and column entrance while simplifying sample preparation. This instalment of "GC Connections" addresses some of the details of static HSGC theory and practice for conventional liquid-phase headspace samples, with the goal of better understanding and controlling the analytical process.

Many samples for gas chromatography (GC) contain significant amounts of non-analyte materials in the sample matrix. With direction injection, very strongly retained solutes and nonvolatile residual materials will remain in the GC system post-analysis and may accumulate to a degree that eventually interferes with ongoing separations. Typical symptoms of this situation include loss of peak area, peak tailing, formation of more-volatile breakdown products, increased column bleed and a greater number and size of ghost peaks. The introduction of large amounts of extraneous material may eventually compromise the instrumentation itself. Remedies include inlet liner replacement, trimming off the beginning of the column, installation and regular replacement of an uncoated precolumn, column bakeout, column solvent washing and column replacement. 

It is better to prevent such difficulties in the first place. In cases where contaminants are volatile enough to be eluted after the peaks of interest, column backflushing may remove the resides by purging the column with reversed carrier gas flow. A recent "GC Connections" instalment described the basics of column backflushing (1). Backflushing will not work when nonvolatile materials are present. The contaminating substances are permanently entrained inside the column and no amount of reverse carrier flow or increased column temperature will remove them. 

Classical wet sample preparation provides an obvious route to cleaner injections via derivatization, extraction, filtration and related techniques that preseparate analytes from contaminating sample matrix material. Chemically active procedures may involve hazardous materials, which detract from the usefulness of derivatization by imposing material safety and disposal requirements. In addition, recoveries and reproducibilities of a multistep procedure might not be as good as more direct methods that have fewer steps.  

Simpler methods for managing difficult sample matrices are sometimes better than extensive sample preparation. Direct sample injection accompanied by inlet liner replacement every few injections can turn out to be easier and less expensive than a complex sample preparation procedure. I have seen this many times. In one example, a laboratory technician once described to me a very satisfactory direct-injection analysis of whole blood carried out with single-use inlet liners. Of course, such an expedient does not lend itself well to automation, at least not without a liner-changing robotic arm.  

Headspace sampling (HS) keeps sample residues from entering the GC inlet by holding the entire sample matrix in a vial while transferring volatile components into the GC inlet and column. Nonvolatile contaminants remain behind in the headspace vial and do not accumulate in the inlet or the column. Chromatographers generally divide headspace sampling into two main subgenres: static and dynamic. These terms refer to how gaseous analytes are removed from the sample: either dynamically, by sweeping with inert gas; or statically, by allowing analytes to enter the gas phase driven only by thermal and chemical means. 

In static HSGC, the sample is sealed in a gas-tight enclosure — such as the standard 22-mL headspace vial used in many laboratories — and held under controlled temperature conditions. Volatile material from a condensed (liquid or solid) sample enters the headspace, the enclosed gas phase above the sample, of the vial. After a period of time a portion of the accumulated sample gas is transferred onward to the GC column. 

In equilibrium static HSGC, sufficient time is allowed for the concentrations of the gaseous components to become steady and reach equilibrium before sample extraction and transfer. For certain samples, such as polymers or solids, the equilibrium state may be difficult to attain. In such cases, multiple sample extraction steps may be used, followed either by multiple GC analyses, one per extraction step; or by accumulation of the products of each discrete extraction in a concentrating trap followed by desorption for a single GC analysis. 

In dynamic headspace sampling, sample is contained in a vessel through which gas can flow in a controlled manner. Inert gas, usually carrier gas, passes through or around the sample continuously during the sampling period. Volatile compounds released from the sample are swept into the gas stream, exit the sample container and subsequently are retained in an adsorptive trap.  

After a sufficient amount of sample has accumulated, the trap is heated to desorb the trapped volatiles onto the GC column. Dynamic headspace sampling is the basis for purge-and-trap analysis of volatiles in water. Volatiles emitted from difficult materials such as hard-disk media, for example, can be sampled by the technique as well with specialized sampling vessels.  

Static and dynamic HSGC are both versatile sampling techniques; many types of sample can be handled by either technique. Often the choice of headspace sampling technique is mandated by regulatory requirements. The analysis of volatiles in pharmaceutical intermediates and products, for example, is performed with static headspace sampling according to the 

United States Pharmacopeia National Formulary (USP–NF)

 General Chapter <467> on Organic Volatile Impurities/Residual Solvents, or with similar methods that exist in Europe and other areas of the world. In the United States, determination of low-solubility volatiles in drinking water is performed by dynamic headspace sampling as described in the United States Environmental Protection Agency (USEPA) Method 524.2 for purge-and-trap sampling and capillary GC analysis. 

A major difference between headspace and direct injection lies in the behavior of the volatile analytes. When a sample is injected directly into a GC inlet, essentially all of the sample material enters the inlet system. For the sake of discussion, we will ignore well known vaporizing inlet effects such as mass discrimination, thermolysis and adsorption.  

In static headspace sampling, the chemical system of the sample in the headspace vial directly affects the transfer of volatiles into the GC column. A clear understanding of this chemical system and its effects on the chromatographic results provides analysts with an opportunity to improve the quality of their analyses. 

At equilibrium, the chemical system inside a sealed static headspace vial can be characterized with a conventional theoretical treatment. Figure 1 illustrates such a system for a two-phase sample system and names its more important physico–chemical characteristics, such as the volumes of the liquid phase, 

, and the concentrations at equilibrium of individual analytes in the liquid phase, 

. Figure 1 shows conceptually the migration of solute molecules into and out of the liquid and gas phases. 

 Figure 1: Static headspace vial. Symbols are explained in the text. 

The gas-phase concentration of each analyte is the quantity measured by a GC analysis, not their concentrations in the liquid sample phase. We want to know what the analyte concentrations were in the sample phase before migration into the gas phase commenced. The headspace vial chemical system has two characteristics that determine the relationships between the original solute concentrations in the sample and their measured gas-phase concentrations.  

First, to determine the original analyte concentrations, 

, in the liquid phase before headspace sampling starts, we need to consider the partition or distribution coefficient at equilibrium, 

, which is the ratio of a compound's concentration in the liquid phase to that in the gaseous phase:  

The distribution coefficient is strongly influenced by the temperature and the chemical nature of the liquid phase in relation to the solutes. Generally, 

 will decrease as the temperature increases, signifying a rise in gas-phase concentrations. Conversely, 

 will increase for liquid-phase compositions in which analytes are more soluble. Good solubility control is essential. As we will see, both the temperature and the chemical composition of the sample strongly influence measured gas-phase analyte concentrations. 

Second, the ratio of the gaseous to liquid-phase volumes in the vial plays a secondary but crucial role in determining analyte concentrations in the two phases at equilibrium. This ratio is termed the phase ratio, β:  

With a bit of mathematical derivation, which I will omit for the sake of brevity (see 

 for a more complete treatment of headspace theory), it can be shown that the original solute concentration in the liquid phase is related to its concentration in the gas phase, the distribution coefficient and the phase ratio by this relationship, sometimes termed the headspace equation:  

 and β controls the gas and liquid phase concentrations, not either parameter separately.  

 and β via stringent temperature regulation and precise volume measurement, along with consistent sample preparation, are paramount to obtaining the best results. If the analytical conditions are well controlled, then 

 and β will remain essentially constant across a series of analyses. Calibration by standard addition or external standard methods using the same sample matrix system as the analytical samples is then easily performed. The 

 and β terms become part of the instrumental calibration coefficient for each analyte along with other factors such as the sample gas volume transferred to the column and the detector response itself. 

 and β influence how analytes' gas-phase concentrations are affected by temperature and sample volume, and by the sample phase composition. With a little knowledge about how the enclosed chemical system in a headspace vial works, chromatographers can understand and, if the situation permits, take control of these aspects of their headspace analyses. 

The equilibrium gas-phase concentration in the headspace, measured by the GC, can be expressed from equation 3 in this manner: 

 and β decreases, gas-phase concentrations increase, and peaks become correspondingly larger. 

 is a function of the temperature and the closed-system chemistry in the vial, and β is a function of the volumes of sample and gas in the vial. We'll examine how different situations for these factors affect both the sizes of peaks and their repeatability for a highly soluble analyte, ethanol, and a not-so-soluble analyte, 

The distribution coefficient of both analytes in water depends on temperature in a logarithmic relationship. Figure 2(a) graphs the distribution coefficient of ethanol in water as a function of temperature. The ethanol distribution coefficient is large, on the order of 200–1350 across a temperature range of 80–40 °C. Unlike ethanol, 

-hexane is relatively insoluble in water. Its distribution coefficient changes with temperature by about the same relative magnitude as for ethanol, as shown in Figure 2(b), but the absolute values only range from 0.01 to 0.15 across the same temperature range. 

For compounds with high solubility in the liquid phase, like ethanol in water, where 

 >> β, the distribution coefficient dominates gas-phase concentrations in the relationship of equation 4, so small changes in vial temperature can cause large changes in the gas-phase concentrations and consequently in the measured peak areas. Figure 3(a) graphs the changes in relative peak areas as temperatures increase for the ethanol–water system with constant liquid sample volume in the headspace vial. The relative ethanol areas increase 6.3-fold, going from 40 °C to 80 °C. For soluble compounds like ethanol, peak areas are very sensitive to even small temperature changes. A shift from 60 °C to 62 °C will increase the ethanol peak area by nearly 10%. 

Conversely, for low-solubility compounds like 

 << β, the influence of the distribution coefficient on gas-phase concentrations is small, and temperature shifts have little effect. The relative areas increase by about 1.3fold going from 40 °C to 80 °C, much less than for ethanol but still a healthy increment. For a 2 °C increase, though, the effect is negligible, at about 0.1%. 

The liquid sample volume, in the form of the phase ratio (equation 2), influences the gas-phase concentration strongly for compounds that are less soluble. In the case of 

 across a full range of sample volumes, so changes in the sample volume can be expected to strongly influence the gas-phase solute concentration. Figure 4(b) shows a relative 

-hexane area increase of 6.8fold when going from 5 mL to 15 mL of liquid sample at a constant 60  °C temperature. An incremental change in volume of 0.2 mL would increase peak areas by around 5%. 

 ≈ 500 at 60 °C, changes in the comparatively small phase ratio have essentially no influence on the gas-phase concentration. Figure 4(a) graphs a nearly straight line for relative ethanol areas across the entire 5–15 mL sample volume range, where the areas increase by only 0.5%. The effect of a 0.2-mL volume increment is negligible. 

Some samples may not deliver as much method sensitivity, in the form of sufficient lower limits of quantification (LOQ), as may be desired. Headspace system sensitivity is a function of solubilities as well as phase ratios. Assuming there is some latitude in the methodology, sensitivity can be increased by taking steps to reduce both 

With direct injection sampling techniques, larger sample sizes will produce larger peaks for all the compounds in equal proportion. It would seem intuitive that the same is true for headspace sampling, but in fact this is only partially true. Take a look at the relative areas for ethanol and 

-hexane shown in Figure 4. The data are for increasing volumes of the same concentration in water of each component, yet only the 

-hexane exhibits areas that increase with the sample volume.  

There is little net gain to be had from increasing the sample volume for highly soluble analytes, such as ethanol in water. With a very large distribution ratio, the smaller phase ratios that result from larger sample volumes will not influence the sum of 

 and β, and so areas will not increase. 

Keep in mind that headspace samplers have a limit for sample volume as imposed by the sampling needle's bottom-most position. It is imperative to avoid any possibility of the needle contacting the liquid sample phase, as this will contaminate the needle and cause sample carryover.  

Higher vial thermostating temperatures do have a strong influence on the distribution constant and can be used to advantage, with a limit. For soluble compounds such as ethanol in water, higher temperatures will produce higher sensitivities, but this is not so with low solubility compounds like 

-hexane where areas are largely independent of the temperature. 

A cautionary note is required here: the vapour pressure of water increases exponentially with temperature, as do the vapour pressures of other common solvents. If too-high vial thermostating temperatures are used, the risk of a vial explosion becomes a real possibility. For this reason, always use headspace vials with pressure-relieving septum caps, and avoid excessively high vial temperatures. Some samples may begin to decompose at higher temperatures with concomitant degradation of results. 

GC Connections

Addresses some of the details of static HSGC theory and practice for conventional liquid-phase headspace samples to better understand and control the analytical processes.

Headspace Sampling

Developing versatile, rapid and accurate analytical techniques for the detection and quantification of water in a variety of materials remains an important and ubiquitous analytical problem. This article describes an effective and sensitive ionic liquid (IL)-based capillary gas chromatography (GC) method with a thermal conductivity detector (TCD) to determine the water content in liquid samples. The open tubular capillary columns, coated with specific ILs developed in this study, increased the sensitivity and significantly increased the ruggedness of this technique. The lower limit of detection (LOD) of this method is ~2 ng water. Samples containing high levels of water are also readily analysed without pretreatment. Conversely, organic solvents can be measured in water by the same approach using either a TCD or a flame ionization detector (FID). Standardization was performed with National Institute of Standards and Technology (NIST) reference materials and the accuracy was compared with another independent method (Karl Fischer titration). The developed method is highly sensitive, fast, and is not affected by interferences and side reactions common with existing Karl Fischer Titration (KFT) methods.

The determination of water content in solvents and consumer products, including foods, pharmaceuticals and industrial materials is of great importance. Analytical testing for the presence and concentration of water is one of the most frequent, important and ubiquitous measurements made in modern industrial society. Thus a versatile, simple and efficient analytical technique for the accurate quantification of water is imperative. The essentially universal presence of water requires accurate, easy and sensitive techniques to quantify it. Various techniques such as gravimetry (1), Karl Fischer Titration [KFT] (2,3), gas chromatography (GC) (4–13), near infra red spectroscopy [NIRS] (4,14–16), solvatochromic sensing (17,19), fluorine nuclear magnetic resonance spectroscopy (F-NMRS) (18), isotope ratio mass spectrometry [IRMS] (19) and others have been reported in the literature, but only few methods are widely accepted and used.  

Currently, the most commonly used method for water analysis is the KFT, which was first reported in 1935 (2). In this titrametric method, I

 is reduced to HI in the presence of water (9). There are four components in the Karl Fischer reagent consisting of: iodine, sulphur dioxide, a suitable base (RN), (originally pyridine was used, but now imidazole is more common); and a suitable solvent (methanol, ethanol, diethylene glycol monomethyl ether, etc) (20).

The accepted mechanism of this two-step reaction is (20,21): 

 The end point is determined potentiometrically. Two types of KFT methods are used: coulometric titration and volumetric titration. The former is used to detect trace amounts of water, ranging from 10 µg to 99 µg (1 ppm – 5%), and it requires ~5 g or more of sample (22). Volumetric titration is used to detect higher water quantities greater than 1 mg (10 ppm – 100%) and the amount of sample required varies from 0.1 mg to 500 mg (23). Therefore, prior knowledge of the approximate amount of water present in the sample is required in choosing the correct KF method of analysis.  

Although this is a well established method, interference of side reactions (9), reagent instability (21), sample insolubility (24) and pH issues (4) prevent it from being accepted as a universal method. Variations on the basic KFT methodologies have been developed in an attempt to overcome these problems (3,9,24). However, many issues still remain, not the least of which is that the reagents degrade with time and there is residual water in all KFT reagents. Another applied method for water detection is based on GC. Early attempts using GC were mainly based on packed (molecular sieve) columns, involving both direct detection by a thermal conductivity detector (TCD) (7–9,11,13) and indirect detection (i.e., reacting water with calcium carbide to convert to acetylene) with a flame ionization detection (FID) (5). Peak asymmetry (4), poor sensitivity, poor efficiency, strong adsorption of water and many solvents by the stationary phase (7), overlapping of the water peak by other larger peaks, and the inability to detect higher amounts of water (4) limited its application in many cases. Attempts to eliminate peak asymmetry (4,25) using wide-diameter open tubular columns [OTCs] (6) and capillary columns (10) showed some improvement. Additionally, most conventional capillary column GC stationary phases are degraded by water.  

A truly useful, broadly effective capillary GC method for water should meet several criteria including the following:  

(1) Water should not alter or degrade the stationary phase, thereby altering retention times and peak shapes. 

(2) There must be a considerable difference in the retention of water and most/all organic solvents especially when the solvent peak is very large relative to the water peak.  

(3) The water peaks should show good efficiency and symmetry.  

(4) The water and solvent chromatogram should have sufficient separation space for an appropriate, baseline separated internal standard (IS). 	

In this study, we examine an IL-based capillary GC method with TCD for the direct determination of water content in liquid samples. The unique nature of ILs including: high thermal stabilities (26), variable polarities (27,28) and exceptional stability to water and oxygen make them excellent choices as stationary phases for this methodology. As will be shown, open tubular capillary (OTC) columns coated with specific IL stationary phases (developed for water analysis) can increase the sensitivity, while greatly enhancing the applicability and reliability of this technique. Furthermore, analysis times can be decreased to 6 min or even less than 3 min in many cases, and samples with virtually any concentration of water can be analysed. The efficacy of this approach is demonstrated with 50 different solvent samples.  

The analysis was performed using a 6890N gas chromatograph (Agilent Technologies Inc., Wilmington, Delaware, USA), equipped with a 7683B series autoinjector, TCD and Chemstation plus software (Rev. B.01.03). An Agilent Technologies 10 µL syringe (5181-1267), was used with the autosampler, while a 10 µL syringe (Hamilton, Reno, Nevada, USA) was used for all manual injections. The fused silica capillary columns were coated with IL stationary phases synthesized as previously reported (26,29). The columns were 30 m long, 0.25 mm internal diameter (i.d.) and 0.2 µm film thickness. KFT was performed using Aquastar V1B volumetric titrator (EM Science, a division of EM industries, Inc., Cherry Hill, New Jersey, USA). 

The water reference material: 8509, moisture in methanol (MeOH, 97 ± 13 ppm water) was obtained from the National Institute of Standards and Technology (NIST, Gaithersburg, Maryland, USA). The 4 Å molecular sieves, hydranal water standard 1.0, tetrahydrofuran (THF) and both the ISs, acetone and acetonitrile, were purchased from Sigma-Aldrich (St Louis, Missouri, USA). Aquastar combititrant 2 and Aquastar methanol were purchased from EMD chemicals (Gibbstowm, New Jersey, USA). The high purity water was obtained by filtering the deionized water with Synergy 185 (Millipore, Billeria, Massachusetts, USA). The testing solvents were from Sigma-Aldrich, Mallinckrodt, EMD, Fisher, Omni solvent and Acros organics (see Supporting Information for more details).  

The accurate quantification of water was achieved using one of two ISs, either acetone or acetonitrile. Two different ISs were available in case one co-eluted with the analyte solvent under the conditions of the experiment. ISs were dried to less than 10 mg/kg by storing over 30% w/v 3 Å molecular sieves for seven days prior to use. A typical sample preparation involved drying a 2 mL autosampler vial overnight at 130 °C followed by the addition of approximately 1 mL of solvent. The mass of the solvent was recorded using an analytical balance. 5.0 mg of IS was added prior to analysis.  

For all analyses, helium was used as a carrier gas at 1 mL/min. Inlet and detector temperatures were set at 250 °C. Splitless injections were made with a purge flow of 20 mL/min. Similar results are obtained using split mode with 20:1 split ratio. Oven temperatures varied from 40 °C to 120 °C (See Supplemental Table S1, which is available on the online version of the article on 

). For initial screening, the columns were conditioned at 120 °C for 2 h. The sample of interest was injected in the splitless mode (0.2–5 µL) to examine the separation between water and the bulk solvent. This preliminary experiment helped to determine which IS should be used. 

Water quantification was achieved by integration of the IS peak and the water peak. The concentration of IS in mg/kg was multiplied by the ratio of water peak to IS peak and the result was divided by the response factor (RF). The resulting number represents the concentration of water in the sample in mg/kg. Each solvent was prepared in triplicate and each individual sample was injected in triplicate for a total of n = 9 individual integrations for each solvent analysed.  

The limit of detection (LOD) and the limit of quantification (LOQ) were calculated according to the guidelines of the US Food and Drug Administration (FDA) (30,31), using the following equations: 

 where,σ = the standard deviation (SD) of the response and S = the slope of the calibration plot. 

 The σ is normally obtained from the SD of the blank sample (31). As it is impossible to obtain a sample without water, the first point of the calibration plot, where there is no added water is used as the blank sample and its SD was used as σ. The slope was obtained from the regression analysis of the plot; peak area ratio of water and IS versus the amount of water.

Figure 1 shows the structures of the three ILs that were used as stationary phases in this study. Generally, IL stationary phases containing trifluoromethylsulphonate (TfO

 ) anions resulted in more symmetric water peak shapes than those that contained PF

  or bis[(trifluoromethyl)sulphonyl]imide (NTf

 ), with the same cation (data not shown). In addition to the IL-based GC columns, a commercially available polyethylene glycol (PEG) column was also evaluated for comparison. 

Figure 2 shows the GC separations of small amounts of water impurities from two of the organic solvents that were analysed. Note that the water peak can be eluted before or after the large organic solvent peak, depending on the relative elution order of the two on the IL-based stationary phases [Figures 2(a–c)]. In most cases the "separation window" between the water and solvent peaks is sufficiently large [Figure 2(a)] that a thermal gradient can be used to further narrow the peak width of water and reduce analysis times [Figure 2(b)]. A comparison of the separation of water from methylene chloride on an IL column versus a commercial PEG type column (see Experimental) is shown in Figure 3. Note that the IL-based column [Figure 3(a)] produced better peak shapes and selectivity even though the separation conditions were optimized for the PEG column. In all cases (for all solvent samples) the IL-based separations were substantially better in terms of selectivity and efficiency. 

Table 1 compares the amount of water measured in ten solvents and a NIST methanol standard using four different capillary GC methods and the KFT. The samples were chosen so that the KFT analysis could be done without the use of special reagents (For example, as are needed to quantify water in aldehydes and ketones) (3). Also, most of these samples could be analysed on the commercial PEG column. As can be seen from the data, the IL-based columns usually produced the most precise and accurate results (as indicated from the relative standard deviations (RSDs) and NIST standard respectively, Table 1). It should be noted that no more than one microlitre of sample was used for any capillary GC determinations. Conversely, the KFTs used between 5–15 g of sample depending on the water content of the solvents (larger samples were required for samples containing the least water) (Table 1). Figure 4 shows a standard addition plot for the determination of water in SRM 8509. As can be seen, standard addition is a viable alternative to determine water content if a RF is not available. High levels of accuracy and precision are possible when using a calibrated syringe.

Table 1: Comparison of the ionic liquid GC results with the best results from the Karl Fischer Titration (KFT) and the use of a commercial PEG GC column. 

The LODs and LOQs for the IL columns were better than those found for the commercial PEG column, even when analysing samples and using conditions that are necessary for favourable separations on the PEG column. The limit of detection (LOD) of coulometric KFT is 10 µg, and it requires at least 5 g of sample. The IL-based GC method required only 0.2 µL of sample to obtain a much lower detection limit (~2.0 ng or ~5000× greater sensitivity).

Table 2 lists the water content of 50 different solvents as determined with the three IL columns evaluated in this study. Figure 5 indicates the number of these solvents that could be successfully analysed on each column. To be considered a successful separation, the water (analyte) peak had to be separated from both the solvent and at least one of the ISs (i.e., acetone or acetonitrile). All three IL columns could be used to quantify water in 38 out of the 50 solvents (Figure 5). The HAIM-PEG-TFO overall was the most successful as it could be used to quantify water in 47 of the solvent samples, including two samples that were not amenable to separation on the other tested columns.

  column was used to quantify water in 42 solvents, including pyridine and 1,2-dichlorobenzene, which were not possible using the other two columns that were investigated. The DMIM-PEG TfO

  column often gave the best separation window between the water peak and solvent peaks, compared with the other columns. Hence all the separations that are possible on this column can be done at even higher temperatures that those used in this report (Table 3) or using temperature gradients [Figure 2(b)] if desired. In most cases this means that many analyses times can be less than 3 min (results not shown).

As capillary columns containing IL stationary phases are effective in the measurement of small amounts of water in organic solvents, it would not be surprising if they also can be used to determine trace organic solvents in water. Such a determination is shown in Figure 6. Note that in Figure 6(a), TCD is used to show the elution of the water peak relative to trace organic solvents. In Figure 6(b) even lower concentrations of the organic contaminants are seen when using a FID. Of course, water cannot be seen with this detector. It should be noted that the injection of water samples is not recommended on ordinary commercial columns that are not based on ionic liquids. Virtually all traditional commercial columns show appreciable degradation and continuously changing chromatograms when analysing water samples. Analysing water for organic solvents tends to be much more damaging for these columns than analysing organic solvents for trace amounts of water. For example three successive commercial PEG columns had to be used for this study while the separations and conditions of all IL columns used remained unchanged throughout the study (after more than 1600 injections). 

A rapid, easy IL-based GC method has been developed for the quantification of water in extremely diverse solvent samples. LODs using this technique are superior when compared with KFT. Furthermore, the IL-GC methodology requires less sample and is free from other complications associated with KFT. The IL-GC method can be used regardless of the chemical nature of the solvent and produces no additional waste products. When compared to other GC methods using commercially available PEG columns, the IL-based columns possessed superior selectivity for water in all solvents tested. Furthermore, they show no degradation or chromatographic changes with time. Typical analysis times ranged from less than 3 min to 7 min. It is expected that this approach could greatly simplify the analysis of water in a variety of applications. The extension of this approach to gases and solid samples is under investigation and will be reported subsequently.  

This work was financially supported by the Robert A. Welch Foundation (Y-0026). We would like to thank Professor Zoltan A. Schelly; University of Texas at Arlington, for providing the KFT device. 

Describing an accurate analytical technique for the detection and quantification of water using IL-based capillary GC.

Rapid, Efficient Quantification of Water in Solvents and Solvents in Water Using an Ionic Liquid-based GC Column

With the popularity of medical shows on television, you'd think we'd all know how to act in a medical emergency. After all, we know what to do when we have an emergency with our liquid chromatography (LC) column, don't we? Or is it really an emergency? In this month's "LC Troubleshooting," we'll consider the process of column triage. When will the column survive on its own? When does it have recoverable injuries? And when is it beyond resuscitation? We'll concentrate on three primary symptoms of column failure: increased peak tailing, increased pressure and changed retention times. 

"Good Enough" May Be Trying to Tell You Something

A well-designed LC method should have a system suitability test that truly evaluates the ability of the method to perform. Usually the system suitability test includes a measure of peak tailing (tailing factor, TF, or asymmetry factor, 

, or retention-time window for the peak or peaks of interest. Often, resolution, 

, is included. I also suggest that system pressure should be noted on a daily basis. If your LC system doesn't record the pressure automatically, add an item to the run summary that is usually part of each method. Rarely is a change in pressure alone a predictor of poor data quality, but it is one of the early warning signs that the column may encounter problems.  

When one or more of the system suitability parameters fails to meet the pre-defined limits, something must be done to correct the problem, such as mixing a new batch of mobile phase or cleaning or replacing the column. However, if this is the only way system suitability results are used — as a pass–fail decision — you are not taking advantage of the information that is available. You may find system suitability failure comes as a surprise: One day everything is OK, then the next day it fails. This is rarely the case, however; instead, the system often gives hints of what is happening, if you pay close attention. I recommend making a control chart to follow the trend of each of the system-suitability parameters, and I would track pressure in the same way. The control chart is simply a plot of the value of the parameter over time or number of injections, with the acceptable limit of the parameter plotted as well. You can be fancy and add more traditional control-chart features, such as those described in reference 1, but that may be overkill for what you need for system suitability.  

I have created three control charts in Figure 1 to illustrate the point. These are data for a fictitious method over 30 batches of samples. In the top panel, the pressure at the beginning of the run is plotted (solid line) with a dashed line added at a 2500-psi boundary. Normally the method runs in the 1500–2000 psi range, and when it gets to ≈2500 psi it is time to change the frit in the in-line filter. This 2500-psi boundary is a "soft" limit, because data quality is seldom compromised if the pressure exceeds this value. The middle panel plots the tailing factor, with a system suitability requirement is that TF should be ≤1.6 (dashed line). With a new column, TF ≈ 1.4 is observed. The lower panel shows the retention time during system suitability with a normal value of ≈4.7 min and a requirement of 4.5 ≤ 

 ≤ 4.9. How do you react to symptoms that indicate your liquid chromatography column has major problems?  

 Figure 1: Example control charts to trend column performance. Pressure (top), tailing factor (middle) and retention (bottom) are plotted as solid lines over 30 runs with method limits shown as dashed lines. 

If we blindly use the system suitability data of Figure 1 to tell us whether the system is "good enough" to make it though the next batch of samples, we may be surprised when system suitability fails. Instead, think of how these data are trying to give us early warning signs. For example, you can see that variation in retention and tailing seem fairly random until approximately batch 20, when they begin trending toward the limits. It looks like the limits are reached for both these parameters after ≈25 batches. If column replacement reset the system suitability parameters to where they started, and similar trends were observed for additional columns, these data could be used to establish a preventive maintenance strategy. For example, proactive replacement of the column after 20 sample batches would avoid any problems created by system suitability failure, and excessive pressure would be avoided, too. My recommendation is that if you can anticipate when a part (the column in the present example) will fail, replacement of the part at 70–80% of its expected lifetime is a good strategy. You get most of the useful life out of the part and avoid any problems associated with a failure of that part. 

So what happens when system suitability fails? The three most common symptoms that something is not right with the column are increased pressure, increased tailing and a change in retention times, either individually or in combination. The causes of column problems are physical or chemical in nature. Let's look at each of these. 

Physical problems with the column are most commonly manifested as a build-up of particulate matter on the inlet frit of the column. This will cause increased pressure and often similar peak distortion of all the peaks in the chromatogram. For example, all peaks will tail excessively or may be split or doubled. When these symptoms are observed, you know that whatever happened occurred before the sample was separated. About a third of the time you can rescue a column exhibiting these symptoms by reversing it and back-flushing it. 

Simply remove the column, reverse it and route the new outlet end to waste (not to the detector). Flush the column with 15–20 mL of mobile phase, or better yet, with the strong solvent of the mobile phase (generally acetonitrile or methanol). The hope is that this will wash the particulate matter off the inlet frit and reduce the pressure back to acceptable levels. If the column is packed with 3.5- or 5-μm silica-based particles, you can leave the column reversed. Reconnect it to the detector and check system suitability again to see if it will pass now. Columns packed with particles ≤ 3 μm in diameter may use inlet frits that are too large to allow you to continue operation of the column in the reversed direction, so you should return the column to its original direction in such cases. It is a good idea to consult the column care-and-use instructions to see if there are any limitations on column reversal. If you are lucky, this procedure will revitalize the column and you'll be able to use it a bit longer. 

Chemical problems with the column usually show up as changes in retention for one or more peaks, as increased peak tailing or as a combination of retention changes and peak tailing. Strongly retained materials from the sample can build up on the column over time, causing a change in the column chemistry, and thus a change in the appearance of the peaks. Sometimes these materials can be removed by flushing the column with a strong solvent. Another cause of retention and tailing changes is that something has attacked the stationary phase or otherwise permanently changed the chemical surface of the column. In such cases, the column cannot be restored. It is not easy to distinguish between the two forms of failure, so the same treatment should be tried to see if it will help. Remove strongly retained material by flushing the column with 10–20 column volumes (15–20 mL) of the strong solvent of the mobile phase. If you are lucky, this will revive the column.  

If symptoms of physical or chemical problems with the column occur regularly before 500–1000 injections have been performed, you may be able to extend column life by improving the sample cleanup or adding column protection to the system. Because sample cleanup is more involved, I recommend starting with column protection. Every system should be operated with an in-line filter immediately downstream from the autosampler. For 3- or 5-μm columns, this filter contains an 0.5-μm porosity frit. This will trap particulate matter that would otherwise get caught on the 2.0- or 0.5-μm frit at the head of the column. When the pressure begins to rise, replace the frit. The frit in the in-line filter can be changed in a few minutes and is very inexpensive, especially when compared to the cost of the column. The use of a guard column is another option to help extend column life. The frit at the head of the guard column will trap debris that would otherwise block the column inlet frit, but even this can be avoided if you use the in-line filter in addition to the guard column. Guard columns have been shown to extend the life of the analytical column, but they may cost 20% of the cost of the analytical column, so the economics of guard column use may be marginal. If you use a guard column, you'll have to figure out when to replace the guard column. You should replace the guard column before it adversely affects the overall separation. As with the parameters of Figure 1, track the system performance when a guard column is in place. When system suitability begins to trend toward the limits, change the guard column and see if it fixes the problem. Most workers find that it is most convenient to replace the guard column on a scheduled basis — either after a certain number of injections or sample batches — or perhaps on a calendar basis. Additional sample preparation almost always will extend column life, but sample preparation is expensive and may not be appropriate for all sample types. 

At some point, the simple restorative measures of flushing or backflushing the column will not be successful. As mentioned above, these measures restore column performance only a third of the time. This means that two-thirds of the time they fail. What next? Some people like to flush with even stronger solvents, such as methylene chloride, to remove fats and waxes (be sure to flush the column before and afterwards with methanol or acetonitrile to ensure solvent miscibility). Other flushing strategies use acid, base or chaotropic agents to remove strongly retained material from the column. If you try any of these procedures, you should backflush the column so the strongly retained material that usually is located on the first few millimetres of the column can be washed directly to waste rather than farther into the column. However, I feel that heroic measures such as these are false economy. They rarely restore column function completely, and they are expensive and time-consuming.  

The column should be considered a consumable item, even though the price tag may make us think that it is a capital expense. Consider the cost of the column in relation to the overall cost of analysis. The overall cost of analysing a sample using UV detection often is in the range of $50/sample. Columns cost ≈$500 each. If the method conditions result in a relatively short column lifetime of 500 injections, that translates into $1/sample for the column, only 2% ($1/$50) of the cost of analysis. If you get >1000 samples through a column, the column is a trivial part of the overall cost of analysis. Any work to extend the column life beyond this may cost more than the additional benefit, because time is an expense. Even backflushing may not be worthwhile. You are better off using an in-line filter to catch unwanted particles from blocking the column and leave it at that. I have a friend that replaces the column with each 96-sample batch — the ≈$5/sample cost of the column is less than the cost of additional sample pretreatment that would extend the column life. It's all about economics. All columns will die eventually. 

The column always tries to tell us how it is doing. Listen to the system suitability results and see if you can find trends that can be used to your advantage. Perhaps you can only anticipate the column failure by a day or two, but you may be able to use the information to put together a preventive maintenance strategy that includes a regular flush with a strong solvent and the use of a guard column to help keep the column in service for months on end. As a minimum, I recommend using an in-line filter on every system and flushing the column with the strong solvent of the mobile phase at the end of each batch of samples. Control charts can be a powerful tool to help anticipate when problems will occur in the future. Above all, remember that the column is a consumable item that may not be worth trying to save after 500–1000 samples have been analysed. 

, is vice president of LC Resources, Walnut Creek, California, USA. he is also a member of 

 editorial advisory board. Direct correspondence about this column should go to "LC Troubleshooting", 

, 4A Bridgegate Pavillion, Chester Business Park, Wrexham Road, Chester CH4 9QH, UK, or e-mail the editor, Alasdair Matheson, at 

Understanding Variation. The Key to Managing Chaos

 (SPC Press, Inc., Knoxville, Tennessee, 1993). 

LC Troubleshooting

How do you react to symptoms that indicate your liquid chromatography column has major problems?

LCGC Europe-10-01-2011

Event News

GCxGC with Fluidic Modulation on Enantioselective Oil Analysis

Headspace Sampling

Rapid, Efficient Quantification of Water in Solvents and Solvents in Water Using an Ionic Liquid-based GC Column

Column Triage