For most installments of “LC Troubleshooting” over the past couple of years, I have focused each installment on a single topic or a group of closely related topics. I’ll continue with this approach in 2021, but, for this particular installment, I’ve decided to take a different approach and discuss a handful of apparently unrelated, but nevertheless useful, topics pertaining to LC troubleshooting. These include a theme observed in online high performance liquid chromatography (HPLC) discussion boards and my interactions with users in 2020, a refresh on the very old but very important topic of the chemical stability of reversed-phase columns, and a technical update on the hydrophobic subtraction model (HSM) of reversed-phase selectivity.

One “LC Troubleshooting” Theme from 2020: Degassers 

Degassing technology for HPLC has changed tremendously over the past three decades. My current students are amused to learn that in the “old days” we actually did things like strap a tank of helium to the bench and bubble helium into the mobile phase to remove other dissolved gases from the liquid (this is referred to as 

) prior to pumping it into an HPLC column. Degassing units are integral parts of most modern HPLC pumps, and are so reliable that I doubt most users give them much thought. And yet, looking at online discussion boards in 2020, it is clear that users are going to be dealing with problems due to older and aging degassers for a long time.

I’d like to highlight three things here, but first we need to understand how these older degassers work. A major step forward in degassing technology for HPLC was the development of “inline” or flow-through degassers. The basic idea is that the mobile phase is drawn from a bottle through a piece of polymeric tubing situated inside of a vacuum chamber. If the polymer is chosen that it is semipermeable to gases, but not liquids, then, as the liquid moves though this tubing, dissolved gases in the liquid are drawn through the wall of the tubing into the vacuum chamber before being exhausted to the atmosphere by the vacuum pump. Based on known permeability of the polymer for different gases, one can calculate the length of tubing needed to remove enough of the dissolved gas from the liquid before it exits the vacuum chamber to support reliable operating of the pumping system (generally speaking, HPLC pumps really do not like bubbles). Now, onto my points.

The first point I’d like to make is that although modern inline degassers are based on the same principle described above, the amount of tubing inside the degassing unit can vary dramatically between older and newer units. This is a place where a lot of people get tripped up. The amount of tubing inside the degasser becomes relevant as soon as you want to change the solvent running through a particular channel of the degasser and pump, or you want to know that you have completely replaced the liquid inside the degasser channel with “fresh” solvent. In older inline degassing units, the volume of tubing inside the degasser per channel is approximately 15 mL. This means that, when changing solvents, one should draw a minimum of two times that volume of the new solvent through the degasser before actually using that channel for chromatography, and closer to three or four times that volume if a small amount of the prior solvent could have a significant impact on subsequent analyses (for example, changing from triethylamine buffer and UV detection to formic acid solution and MS detection). This can be done either by gently pulling solvent through using a syringe connected to the outlet of the degasser, or by simply running the pump at a high flow rate (typically about 5 mL/min) for several minutes with the purge valve open.

Secondly, one of the weaknesses of older inline degassers is the tubing that connects the vacuum pump itself to the vacuum chamber associated with each of the solvent channels. This polymeric tubing ages over time, especially when exposed to vapors of solvents drawn out of the mobile phase into the vacuum chamber and vacuum pump. If the tubing cracks or breaks, there is no way the vacuum can be maintained, and the degasser will not work. The bad news is that this is likely to happen at some point in the life of these degassers, but the good news is that replacing this tubing can be a relatively simple fix that may keep the degasser chugging along for more years.

Thirdly, a reasonable question is “Does the degassing step affect the composition of my mobile phase, especially if the solvent sits in the degasser for an extended period of time?” Gross changes in the organic solvent:water ratio in a premixed mobile phase are unlikely. However, small changes in organic solvent:water ratio that could impact very sensitive applications, or changes in the concentrations of buffering components such as ammonia, can occur. In this case, the best way to eliminate these changes as a possible effect on a separation is to purge the degasser following a period where the flow has been turned off, so that any mobile phase that might have been compromised is removed and replaced with “fresh solvent.”

Newer style inline degassers tend to have internal volumes well under 1 mL. This means that they can be purged quickly, and that the volume in solvent lines connecting the bottle to the degasser is the more important volume to worry about when changing to a new solvent.

Refresh on the Topic of Chemical Stability of Reversed-Phase Columns

Since the emergence of silica-based stationary phases for reversed-phase LC in the early days of HPLC, the chemical stability of these phases has been a limitation, and researchers across the globe have worked to improve their stability and develop alternatives. In spite of significant advances in the development of stationary phases based on organic polymers and other metal oxides including alumina, titania, and zirconia, silica-based phases are still the dominant type of stationary phase for reversed-phase LC in use today by far. Stationary phases prepared by covalently bonding stationary phase ligands to the silica surface through siloxane (Si–O–Si) bonds have liabilities at both ends of the pH scale. On the acidic side, the stationary phase ligands themselves can be lost from the column as a result of acid catalyzed hydrolysis of the Si–O–Si bond between the silica particle itself and the ligand. On the alkaline end of the scale, the major liability is dissolution of the silica particle backbone (SiO

) itself. Historically, the conventional teaching has been that when using silica-based reversed-phase LC phases, one should stick to a pH range of 2–7. I see this emerge occasionally on discussion boards, and many bookshelves contain very good, but dated, books that carry this message. Mobile phases buffered below a pH of 2 will result in the slow loss of stationary phase ligands from the column, mobile phases buffered above pH 7 will cause dissolution of particles themselves, and both of these mechanisms can lead to changes in retention, selectivity, efficiency, and mechanical failure of the particle bed. Given that there are good chromatographic reasons to work in mobile phases buffered above pH 7 (for example, increased retention of aliphatic amines), understanding the factors affecting the stability of silica-based phases under these conditions, and development of novel materials to overcome this limitation, have been pursued with great interest over the past few decades. Two frequently cited articles on the topic of buffer and pH effects on silica-based phases above pH 7 are those from Jack Kirkland and co-workers; indeed, these two papers have been cited a remarkable 246 times (1,2).

On the acidic side of the pH scale, bulky side chains at the base of silanes used to derivatize silica particles for reversed-phase LC can be used to slow the rate of acid hydrolysis of the siloxane bond tethering the stationary phase ligand to the silica surface (3). These have become known as “sterically-protected” phases, and are quite popular because they enable separations in mobile phases buffered around pH 2 for extended periods of time, even at elevated temperatures. On the alkaline end of the pH spectrum, progress has been slower but still significant. Multiple approaches have been used to improve the stability of silica-based phases in mobile phases buffered above pH 7, including the use of multidentate silanes that provide more than one point of attachment of the stationary phase ligand to the silica surface (3), and changes to the silica particle material itself, such as silica-organic hybrid materials (4,5). Here too, reversed-phase LC stationary phases based on these technologies have become quite popular because they extend the range of pH above 7 that can reasonably be used without significant concerns about method robustness.

Just how far above pH 7 one can reliably work with these materials depends, of course, on other parameters to some degree (for example, buffer concentration and column temperature). However, at a minimum, these materials enable the use of mobile phases buffered around pH 10 (for example, dilute ammonia) for extended periods of time. Users should always follow the recommendations of manufacturers regarding conditions that are suitable for use of a particular column. Legacy stationary phases that are not made using these new approaches for silica-based phases still suffer the same limitations with respect to pH that they did 20 years ago. As a community, we can move on from the old advice to stay within the range of pH 2–7 to updated advice that says silica-based phases can be used well above pH 7 provided that we choose materials designed for this purpose.

Technical Update on the Hydrophobic Subtraction Model (HSM) of Reversed-Phase Selectivity

The hydrophobic subtraction model (HSM) of the selectivity of reversed-phase LC columns was developed in the early 2000s by Lloyd Snyder, John Dolan, and several other collaborators. The HSM assumes that selectivity in reversed-phase LC can be described in quantitative terms using five pairs of analyte–stationary phase descriptors that are associated with specific types of analyte-stationary phase interactions. These include: hydrophobic interactions (the main determinant of retention in reversed-phase LC), resistance to penetration of the stationary phase by bulky analytes, hydrogen bonding interactions (with analytes acting as hydrogen bond acceptors or donors), and electro- static interactions (typically discussed as cationic analytes interacting with anionic stationary phase sites). To date, about 750 commercially available columns have been characterized using the HSM, and the resulting data are publicly available for free through two different websites (https://apps.usp.org/app/USPNF/columnsDB.html and http://www.hplccolumns.org). The principles of the model, its development, and applications to practical problems have been discussed in 

 at multiple points over the past several years (6–9). One of the most important practical applications of the model—and the initial driver for the development of the model—is using the database of descriptors to find columns with very similar selectivities (“equivalent” for practical purposes) that could be used as a replacement for a column currently in use, or as a backup column in case problems with a column currently in use are encountered in the future. Most recently, I wrote a perspective for this “LC Troubleshooting” column sharing observations about the selectivities of commercial columns released over the past two years, which have been characterized using the HSM (10).

The type of question I’ve been asked most frequently about the HSM in recent years is focused on the extent to which HSM can be used to predict selectivity for a given analyte on a given column. Although the model was not originally developed with this purpose in mind, it certainly is tempting to think that the massive database of descriptors for 750 columns must have some use along these lines. A couple of years ago, my collaborators Sarah Rutan and Tony Taylor began a jour- ney to take a serious look at this question, and try to develop a quantitative sense for what is and is not possible with the HSM in this regard. As part of this effort, along with collaborators Josep Serret and Tina Dahlseid, we carried out a kind of retrospec- tive analysis and refinement of the HSM using all of the retention data collected over the past 18 years in the process of populating the HSM database with descriptors for commercially available columns. Whereas the HSM was initially developed in the early 2000s using data from only type B C18-silica columns, only about half of the columns currently in the database fit this description. The other half of the database is populated by diverse chemistries ranging from short chain alkyl phases to fluorophenyl phases, for example. The results of this retrospective analysis, and refinement of the model to build what we refer to as HSM2, have been published recently in the 

 (11). The principal finding of this study is that by considering selectivity data from many types of reversed- phase LC phases commercialized over the past 15 years, rather than just focusing on type B C18 phases to build the HSM, the predictive accuracy (that is, the ability to accurately predict selectivity on column using analyte descriptors measured using other columns, along with the database of column descriptors) of the model can be improved substantially. For example, we found that for the full data set of 8816 retention measurements (551 column x 16 analytes) the number of predictions with errors greater than 10% when using the original HSM was 235; when using the refined HSM2 for the same predictions, this number was reduced to just 25. To me, this result is very encouraging because it shows us that selectivity models like the HSM can be refined to accommodate diverse reversed-phase LC stationary phases. Moreover, further refinement of such models may yield predictive abilities that are useful in method development, albeit with a significant amount of effort to acquire the data required to refine and parameterize these models. Let’s see what the future holds!

(1) H.A. Claessens, M.A. van Straten, and J.J. Kirkland, 

, 259–270 (1996). https://doi.org/10.1016/0021-9673(95)00904-3.

(2) J.J. Kirkland, M.A. van Straten, and H.A. Claessens, 

, 3–19 (1995). https://doi.org/10.1016/0021-9673(94)00631-I.

(3) J.J. Kirkland, J.L. Glajch, and R.D. Farlee, 

, 2–11 (1989). https://doi.org/10.1021/ac00176a003.

, 5441–5450 (2004). https://doi.org/10.1021/ac049643d.

(5) Y.F. Cheng, T. Walter, Z. Lu, P. Iraneta, B. Alden, C. Gendreau, U. Neue, J. Grassi, J. Carmody, J. O’Gara, and R. Fisk, 

(6) J.W. Dolan, D.R. Stoll, and L.R. Snyder, 

(8) P. Carr, L. Snyder, J.W. Dolan, and R.E. Majors, 

(11) D.R. Stoll, T.A. Dahlseid, S.C. Rutan, T. Taylor, and J.M. Serret, 

 (2020) In Press. https://doi.org/10.1016/j.chroma.2020.461682.

 is the editor of “LC Troubleshooting.” Stoll is a professor and the co-chair of chemistry at Gustavus Adolphus College in St. Peter, Minnesota. His primary research focus is on the development of 2D-LC for both targeted and untargeted analyses. He has authored or coauthored more than 60 peer-reviewed publications and four book chapters in separation science and more than 100 conference presentations. He is also a member of LCGC’s editorial advisory board. Direct correspondence to: 

Articles

LC Troubleshooting

Sometimes our approach to troubleshooting specific problems has to change in response to changes in high performance liquid chromatography (HPLC) technology over time. In this installment, we discuss changes in technologies for mobile-phase degassing, silica-based stationary phases, and models for reversed-phase selectivity.

LC Troubleshooting Odds and Ends from 2020

Here are some great tips for optimizing liquid chromatography (LC)–electrospray ionization (ESI)–MS so that you achieve the best possible results every time. These tips and tricks have been collated by my colleagues to form a beginner’s guide to LC-ESI–MS, and as a primer for those who are already using the technique.

This is often a parameter that is set and never adjusted again. That may work the majority of the time, and can certainly be a good approach if a variety of users with a myriad of samples are using an instrument; however, it is not going to be ideal for all analytes. If you are setting a voltage for a walk-up and use an open-access instrument, it is a good idea to use lower electrospray voltages. However, taking time to adjust the sprayer voltage can lead to vast improvements in MS sensitivity.

The position of the sprayer is a parameter that can and should be optimized, but its optimal setting is likely to be one that is viable for providing high signal quality across a wide range of analytes. Analytes with varying surface activity (sensitivity constant 

) will exhibit different responses depending on the position of the sprayer relative to the sampling cone. Primarily, this is due to the time taken for the analyte to be liberated into the gas phase under the atmospheric pressure ionization (API) conditions (primarily the drying gas temperature and flow rate) that will differ for differing analytes depending upon their ability to migrate to the droplet surface, and be liberated into the gas phase as well as the eluent composition at time of elution. At lower concentrations, any change in the sprayer position will cause the relative response of analytes to change.

The formation of metal adduct ions (such as [M+Na]

)in positive ion mode is a common phenomenon that can result in only the metal adduct ion being present in the MS spectrum. Therefore, we need to be aware of, and remember to look for, these species. It can also be advantageous to try to avoid the formation of adducts altogether, as their formation can lead to unusable mass spectra.

These types of adducts can be avoided by using plastic instead of glass vials. The glass manufacturing process uses a variety of metal salts that can be leached from the glassware by aqueous solvents. However, the use of plastic vials can also lead to the presence of plasticizer peaks within spectra, although these tend to be less problematic, as they appear at fixed 

 values and can be discounted when interpreting spectra. Also, note that high pressure liquid chromatography (HPLC) solvents, such as acetonitrile, can often contain surprisingly high amounts of metal ions such as sodium—choose your solvent grade carefully!

For ESI, reversed-phase solvents (water, acetonitrile, methanol) are preferable, as they favor the formation and transfer of ions from the liquid to the gas phase. Normal-phase solvents (hexane, toluene, dichloromethane) cannot support ions in solution, and are, therefore, not suitable for use with ESI (they can, however, be used with atmospheric pressure chemical ionization [APCI]).

When optimizing ESI applications, the surface tension of the solvents should be considered. Solvents with low surface tension (such as methanol and isopropanol) allow for stable Taylor cone formation, and, hence, a stable and reproducible electrospray. The Rayleigh limit will be overcome at lower potential, and this will tend to lead, on average, to smaller droplets being produced, which aids in the ion formation process, and can lead to an increase in instrument sensitivity.

If a Little Bit Works, a Little Bit Less Will Probably Work Better!

While so much about modern API-MS has been developed to the point of “load and forget,” and, in most cases, this approach will enable us to generate a signal for many analytes, we sometimes forget that a certain degree of optimization will generate data that is far superior to that obtained under “generic” conditions.

This is an excerpt of a blog entry, “10 Great Tips for Electrospray Ionization LC–MS.” See the full blog entry on our website (www.chromatographyonline.com) for additional tips and more detailed explanations.

 is the Chief Science Officer of Arch Sciences Group and the Technical Director of CHROMacademy. Direct correspondence to: 

Here are some great tips for optimizing liquid chromatography (LC)–electrospray ionization (ESI)–MS to achieve the best possible results every time. This is a beginner’s guide to LC-ESI–MS.


Tips for Electrospray Ionization LC–MS

The phenomenon of retention loss observed for reversed-phase liquid chromatography (LC) columns used with near 100% aqueous mobile phases when stopping and resuming the flow has often wrongly been attributed to phase collapse of the bonded alkyl chains onto the silica surface. However, this phenomenon is now explained as a process of pore dewetting with the expulsion of water from the hydrophobic pore network. The driving force for this process is the instability of the water liquid/vapor biphasic system when water is confined in hydrophobic mesopores with diameters <50 nm. Water is forced to leave the mesopore space in porous reversed-phase LC materials by the pressure difference between the vapor and liquid phases (also known as 

). While the pore-dewetting phenomenon can occur with mobile phases containing <100% water, all experiments shown in this paper utilized a 100% aqueous mobile phase with flow rate interruptions as a worst-case scenario. We have accurately measured the effect on the kinetics of pore dewetting of various experimental variables, such as water pressure, temperature, the amount of dissolved gases in water, average pore size, the nature of the surface chemistry, and the surface coverage of the hydrophobic bonded groups. From these data, it is demonstrated why outlet column pressures kept above 50 bar, the use of degassed mobile phases, large mesopores (>20 nm), wide pore size distribution, the low surface coverage of the hydrophobic ligand (<2 μmol/ m

), phenyl-bonded or charged surface alkyl-bonded stationary phases, and enhanced molecular disorder of the tip of the bonded phase would minimize (or eliminate) the retention loss phenomenon with fully aqueous mobile phases after flow rate interruptions.

Reversed-phase liquid chromatography (LC) columns are primarily utilized to separate hydrophobic and moderately polar compounds. They may also be used to retain very polar compounds when using highly or near 100% aqueous mobile phases. A phenomenon observed by many high-pressure liquid chromatography (HPLC) practitioners is a dramatic retention volume or time loss after the column flow is stopped and resumed when using highly aqueous mobile phases with specific reversed-phase LC columns. Even though the utilization of reversed-phase LC columns at nearly 100% aqueous mobile phases is likely not a routine practice in most laboratories, such phenomena can become highly problematic for specific applications. While the easy-to-apply solutions listed in Table I already exist, they may involve changes to an established procedure that cannot be implemented without method revalidation.

The explanation for such retention losses has often invoked a so-called phase collapse of the hydrophobic bonded groups in contact with water (1). However, recent studies have demonstrated that the phenomenon is fundamentally explained by pore dewetting, where water confined in hydrophobic mesopores is no longer at thermodynamic equilibrium with its vapor when the flow is suddenly stopped, and the column returns to atmospheric pressure. The equilibrium water vapor pressure, P

, is given by the Laplace equation (2,3):

 depends on the receding contact angle of water on the hydrophobic surface (θ ~ 93

), the liquid/vapor surface tension of water (γ

 ~ 50 Å); therefore, it is typically around 10 to 20 bar. The pressure difference, 

, is the driving force for liquid water to be spontaneously extruded from the mesopore network. The receding process ends when the water has entirely left the pores to reach thermodynamic equilibrium. The kinetics of this process depends on several experimental parameters. These kinetics was accurately measured by a simple protocol based on recording the change in the zone retention factors of two compounds in pure water, one weakly retained (thiourea), the second more strongly retained (thymine), as a function of time after the flow was interrupted (4). From a theoretical viewpoint, these dewetting kinetics have been studied based on simulations for monosized mesopores in the absence of bottlenecks in the mesoporous structure and by assuming that the process is solely driven by the Laplace pressure difference (5,6). Accordingly, the characteristic time necessary for water to dewet the pores of typical silica-based reversed- phase LC materials should be extremely short (in the range of 10 μs to 0.1 s), depending on the mesopore and particle sizes. Pore dewetting is, then, in theory, much faster than the time needed for the chromatographic column to depressurize (usually 1 to 10 s, depending on particle size and column length [4]) after the flow is stopped. In practice, the observed kinetics of water dewetting are often much slower. It can last from minutes to several hours. The simulation models are an oversimplification of the real dewetting process, with the complexity of the pore network and surface structure not accounted for. In this article, we summarize the results of experiments designed to refine our understanding of the mechanism of pore dewetting and retention loss of reversed-phase LC columns.

The primary goal of this work is to shed light on the actual mechanism of pore dewetting from reversed-phase LC columns by directly measuring the impact of the most relevant experimental parameters (pressure, temperature, pore size, surface concentration of the bonded groups, and surface chemistry) on its kinetics. In addition, we hope to provide users with some suggested mitigation strategies when using reversed- phase LC columns with near 100% aqueous mobile phases under isocratic conditions.

Debunking the Common Belief of “Phase Collapse” 

Retention losses observed for alkyl-bonded reversed-phase LC columns using fully aqueous mobile phases have often been attributed to “phase collapse” of the bonded alkyl chains (1). This explanation has become a commonly accepted myth in the liquid chromatography community (7). According to this theory, in the presence of 100% aqueous mobile phases, the bonded alkyl chains adopt a compact or collapsed conformation, thus severely reducing the access of the analytes to the stationary phase. This, then, dramatically lowers the phase ratio and retention. However, if this explanation were correct, then the elution volume of the analytes would still be as large as the hold-up volume, 

, of the column (since the mobile phase would still have access to the internal mesopore volume). In fact, the elution volume of the analytes can be as small as the interparticle column volume 

), giving evidence that the mobile phase is no longer in contact with the internal surface area of the porous particles (2–4,8,9). For instance, the rapid diminution of the water volume present in the pores of 95 Å Symmetry-C

 particles is shown in Figure 1b as a function of time after the flow rate was stopped.

Additionally, calculations based on either Monte Carlo simulations (10) or molecular dynamics (11) have confirmed that the alkyl-bonded chains in contact with pure water do not fully fold or “collapse” onto themselves. Instead, due to steric hindrance, they remain in a partially extended conformation (see Figure 1a). Indeed, the average thickness of the C

-bonded layer (solid black curve) remains about 14 Å (vertical dashed orange delimitation segment) irrespective of the amount of water present in the mobile phase from either pure methanol or pure acetonitrile to pure water. Note that the dashed orange segment is located at half the thick- ness of the layer where the C

 chain density is continuously decreasing towards zero. This layer gets thinner as the water content in the mobile phase increases, but its center always remains at the same 

-position around 14 Å from the pore surface. The main effect of increasing the organic content in the mobile phase is to extend the tip of the C

 chains deeper into the bulk mobile phase. Phase collapse appears not to be the appropriate explanation for phase retention loss. The retention loss phenomenon was explained by Walter and associates (2,3) as the dewetting of water from the internal hydrophobic (C

) pore network. These results have been corroborated by other researchers (12–16). The dewetting process is driven by the instability of the liquid/ vapor water system (that is, by the Laplace pressure difference between the vapor and liquid phases after the water flow is suddenly stopped).

After the flow is stopped, and water has been expelled from the hydro- phobic mesoporous volume of a reversed-phase LC column, it is possible to force water back into the mesopores by applying pressure higher than the so-called intrusion pressure (12). Figure 2 illustrates the concept of intrusion and extrusion equilibrium pressures associated with the fraction of the pore volume occupied by water in 80 Å silica-C

 particles (a water porogram). The intrusion-extrusion of liquid water shows a hysteresis (that is, the pressure at which extrusion occurs is lower than that required for intrusion, as shown in Figure 2). This is due to the difference between the advancing and receding contact angles, as well as to the arrangement of the different size pores in the pore network (3,12). The equilibrium pressures were measured from the elution of thiourea by adding (intrusion) or removing (extrusion) a series of connected capillary restrictors at the column outlet at a low flow rate of either 0.10 or 0.05 mL/min (8). The presence of the capillary restrictors allows for the control of the average pressure in the column from atmospheric pressure to 375 bar (intrusion curve, black star plot) and from 375 bar to normal pressure (extrusion curve, red star plot). The intrusion pressure (at which liquid water occupies about 50% of the internal pore volume) is typically one order of magnitude higher than the extrusion pressure (where liquid water still occupies about 50% of the total pore volume). Therefore, in order to keep liquid water in at least 95% of the mesoporous volume, the first option would be to apply a water pressure as high as 300 bar everywhere in the column. This is not possible with standard instruments, because the outlet column pressure is rarely larger than 15 bar. The second option would be relying on designing an LC system that would keep the average column pressure above the extrusion pressure before and after flow rate interruption. This can be achieved by adding two 4-port 2-position valves (one downstream, the second upstream from the column), and by blocking one port of each valve. The details are shown in Figures 3a before and in Figure 3b after the flow is stopped. The two plugs allow the pressure to be maintained in the entire column volume.

All else being kept constant, based on the Laplace equation, increasing the average pore size of reversed-phase LC particles should decrease the intensity of the driving force for water extrusion, therefore slowing the expulsion of water from the mesopore volume. Experimental observations are in agreement with this theory (2,3,9,14–16). Figure 4 demonstrates this for columns packed with silica-C

 particles with different average pore sizes, increasing from 80 Å to 110 Å and 430 Å. The C18 surface concentrations for these three materials are all around 3.0 μmol/m

, respectively [9]). The data suggest that selecting a pore size larger than about 200 Å is sufficient to keep water in the internal volume of the particle. The reason is that the extrusion pressure becomes smaller than a few bars. By simple interpolation, after the flow was stopped for about 1 h, water would still occupy more than 99% of the mesopore volume for a material with an average pore size of 200 Å. Increasing the pore size is then a straightforward solution to the problem of retention loss of reversed-phase LC columns using 100% aqueous mobile phases. However, this comes at the expense of reduced retention, as the surface area decreases with increasing pore size. Since the most common reason for using a 100% aqueous mobile phase is to increase the retention of poorly retained analytes, using > 200 Å pore size stationary phases is not an ideal solution.

Pore Connectivity and Pore Size Distribution

Unexpectedly, the dewetting kinetics of water from the pores of silica-C

 particles is much faster than that from the pores of C

-bonded silica particles having about the same surface concentration of 3 μmol/m

. Different research groups have reported this in the past (3,14). This contrasts with the conclusion made in the previous section, because the average pore size of silica-C

 particles is about 15 Å larger than that of the silica-C

 particles. This riddle was solved by comparing the total number of connecting branches between all the mesopores present in C

-bonded layer occupies a larger volume than that of the C

-bonded layer on the surface of the same silica material, the connectivity between the pores is reduced by about 30% (8). Low-pore connectivity minimizes the chance for liquid water to be expelled from the entire volume, because 1) some pores can become isolated; and 2) the smallest pores (from which water dewets the fastest) may no longer be connected to other small pores to propagate the extrusion of water. The coalescence of the vapor bubbles is then stopped. The pore connectivity parameter is directly related to the intrusion-extrusion hysteresis discussed earlier (Figure 5b) for 80 Å silica-C

 materials). This hysteresis can be compared to that of the adsorption-desorption isotherms of nitrogen for the same porous material (Figure 5a). Pore-size distribution and thickness of the bonded layer have a different impact on pore connectivity. In conclusion, the retention loss can be significantly decreased for mesoporous materials having poorly interconnected pores or a wide pore size distribution.

HPLC column temperature significantly impacts the pore dewetting kinetics of water from reversed-phase LC columns. Figure 6 shows the dewetting kinetic data for the same column packed with 5 μm 100 Å silica-C

particles at temperatures increasing from 27 

C. First, it is essential to recall that the surface tension of water decreases, and the receding contact angle either decreases or remains constant with increasing temperature. Therefore, according to the Laplace equation, the driving force for water dewetting is expected to decrease, and the process should become slower as the temperature increases. 

However, the experimental data shown in Figure 6 demonstrates the opposite behavior. This means that the Laplace pressure does not solely control the kinetics of the expulsion of liquid water. A possible explanation for these observations is that the kinetics of dewetting is controlled by the nucleation rate of the first water vapor bubbles that form more rapidly as the temperature increases. In practice, the user should operate at the lowest possible temperature to minimize the retention loss of reversed-phase LC columns after flow interruption.

It was recently shown that the concentration of gases dissolved in the water mobile phase has a moderate impact on the dewetting kinetics of water from the mesopores of C

-silica particles (4). Water saturated with nitrogen was found to dewet nearly 50% faster relative to fully degassed mobile phase 15 min after the flow was stopped. The most plausible explanation is the liberation of nitrogen microbubbles that act as nucleation sites for the formation of the first water vapor bubbles. Since most LC systems have built-in degassers to reduce the dissolved gas content to low ppm levels, the user is relatively secure regarding the presence of gases in the mobile phase. If degassers are not integrated into the LC system, the mobile phase should be purged with helium gas, which has the smallest solubility in water (3.8 x 10

 M) among the most common gases (6.7 x 10

 M for nitrogen and oxygen, respectively).

The Surface Concentration of the Bonded Ligand

Figure 7 compares the dewetting curves of water from two different reversed-phase LC columns packed with the same silica particles bonded with two different surface concentrations of C

). Both materials were extensively endcapped to reduce the concentration of residual silanol groups. The effectiveness of this process was verified from the excellent peak symmetry of bases observed on these two columns (data not shown). Clearly, reducing the C

 surface concentration considerably slows down the dewetting process of water. One hour after the flow was stopped, 99% of the pore volume was still filled with water for a surface concentration of 1.5 μmol/m

 versus 83% for a surface concentration of 3.5 μmol/m

. The explanation for this observation is a diminution of the receding contact angle as supported by independent observations reported in the next sections. As revealed from molecular dynamics studies (9), decreasing the surface concentration increases the mobility of the C

 chains. It likely enables water molecules to penetrate easily and irreversibly between the alkyl chains. The dewetting process then becomes extremely slow. This is the reason why most C

 columns with minimum retention loss are characterized by intermediate C

 surface concentrations. This is also an excellent approach to increase the retention of poorly retained analytes because the dependence of retention on C

 surface concentration shows a broad maximum at ca. 2 μmol/m

Molecular Ordering of the Hydrophobic Layer

The presence on a surface of hydrophobic groups of different lengths has been shown to affect the water contact angles. Whitesides and associates demonstrated this for a series of self-assembled monolayers of alkanethiol chains (C

) on a planar gold surface (18). In this series, the molar fraction of C

 chains was increased stepwise from 0 to 1 (

-axis in Figure 8). It was found that the receding contact angle of the water (

-axis in Figure 8, open circles data) on these two-component monolayers was at a minimum (around 91

 mole fraction between 65 and 85%. The receding contact angles measured for the two one-component monolayers (100% C

, respectively. These experimental results suggest that increasing the molecular disorder (such as by mixing short and long-chain ligands) enables the trapping of water molecules irreversibly at the surface of the hydrophobic layer. In contrast, for shorter and denser C

-bonded monolayers on silica particles, water is nearly instantaneously and fully excluded from the pore volume. Mixed bonded ligands could be adopted to minimize the dewetting of water from reversed-phase LC stationary phases.

Figure 9 compares the kinetics of water dewetting from the same silica material (1.6 μm 90 Å CORTECS superficially porous particle) derivatized with different ligands (C

 with an amine group). Surprisingly, the phenylhexyl ligand prevents the column from any retention loss. The reason is that the receding contact angle of water on the phenylhexyl-bonded surface is smaller than 90

-silica surface is functionalized with an amine group, the dewetting of water is nearly eliminated because the water molecules interact favorably with such a surface. As described above for fully porous silica particles, CORTECS C

 by more than an order of magnitude despite a smaller Laplace pressure (due to a larger pore size after bonding and a lower contact angle). Experimental water porograms have revealed that the extrusion pressure was higher by about 13 bar for C

-bonded CORTECS particles (8). Additionally, the internal porosity and the pore connectivity both decrease from C

-bonded silica, creating more pore bottlenecks and pore constriction in the mesopore network of the latter relative to the former material. Finally, the tip of the C

 chains shows a higher degree of disorder than the shorter C

 chains for the same surface coverage. Consequently, water vapor bubbles grow and coalesce more rapidly in C

-bonded silica particles. It is noteworthy that CORTECS T3 (120 Å, with a C

 surface concentration around 1.6 μmol/m ) without surface charge dewets less than CORTECS C

 by an order of magnitude (cf. Surface concentration of the bonded ligand).

Based on a series of well-designed experiments, this work provides a comprehensive description of the mechanism of retention loss of reversed-phase LC columns using 100% aqueous mobile phases after flow interruption.

1. Retention loss starts with the formation of the very first gas micro-bubbles (from either dissolved gases or water vapor) in the mesopore space.

2. It is then driven by the Laplace pressure difference between the water vapor (~20 bar) trapped inside the mesopores and the liquid water pressure outside the particle (at atmospheric pressure) as the vapor/liquid water system is no longer at equilibrium after the flow was stopped.

3. The microbubbles grow in size and eventually coalesce at a rate that is primarily controlled by the surface chemistry (contact angle >90

), the pore size (Laplace pressure greater than a few bars), the temperature (controlling the nucleation rate of the microbubbles), and the mesopore architecture (pore connectivity and size distribution).

Based on this better understanding of water dewetting from reversed- phase LC columns, any HPLC experimenter can adopt a simple and systematic strategy to eliminate or at least minimize the dewetting of liquid water, which can cause severe retention losses in reversed-phase LC. The following strategy applies if the user needs to use reversed-phase LC columns with a near 100% water mobile phase under isocratic conditions, and does not want to modify their HPLC system.

1. Choose a column containing a stationary phase that is compatible with 100% water mobile phases. This may be an intermediate coverage C

 bonded phase on a 100 to 120 Å pore-size silica, a bonded phase incorporating both hydrophobic and hydrophilic groups (such as a polar-embedded or charge-modified reverse-phase material), or a phenyl-hexyl bonded phase.

2. Use the lowest possible temperature and degas the aqueous mobile phase.

3. Condition the column with a mobile phase containing a sufficient concentration of organic solvent to ensure that the pore network is filled. While the concentration needed varies with the stationary phase, 40% organic works with even highly hydrophobic stationary phases (2,3). Change to the high water content mobile phase, and ensure that the flow is not stopped until all analyses are completed. If the flow must be stopped, recondition the column with the same organic or water mobile phase used initially, then change to the high water content mobile phase and continue injecting samples.

The authors would like to thank Kevin Wyndham, Darryl Brousmiche, Jessica Field, Nicole Lawrence, Martin Gilar, Yuehong Xu, Amit Patel, Kenneth Berthelette, Cheryl Boissel, Bonnie Alden, Jonathan Turner, and Daniel Walsh (Waters Corporation) for fruitful discussions, suggestions, and for providing the research prototype stationary phases and their physicochemical properties. The authors also thank David Bell from Restek, Bradley Van Middlesworth of Thermo Fisher Scientific, and Mike Shifflet of Johnson & Johnson consumer health for helpful technical reviews of the manuscript.

(2) T.H. Walter, P. Iraneta, and M. Capparella, Observations on the Wetting of Reversed-Phase HPLC Packings, Poster P-202/A, HPLC 97, Birmingham, United Kingdom, available at http://www.waters.com (URL: http:// www.waters.com/watersdivision/ pdfs/TWHPLC97.pdf).

(3) T.H. Walter, P. Iraneta, and M. Capparella, 

(4) F. Gritti, D. Brousmiche, M. Gilar, T.H. Walter, and K. Wyndham, 

(6) A. Tinti, A. Giacomello, Y. Grosu, and C. Casciola, 

 (John Wiley and Sons, Hoboken, New Jersey, 2nd Ed., 2019), pp. 59–60.

(8) F. Gritti, D. Hlushkou, and U. Tallarek, 

(9) F. Gritti, M. Gilar, T.H. Walter, and K. Wyndham, 

(10) R. Lindsey, J. Rafferty, B. Eggimann, J. Siepmann, and M. Schure, 

(11) J. Rybka, A. Holtzel, and U. Tallarek, 

(13) E.S.P. Bouvier, D.M. Martin, P.C. Iraneta, M.Capparella, Y.-F. Cheng, and D.J. Phillips, 

(16) A. Cavazzini, N. Marchetti, L. Pasti, R. Greco, F. Dondi, A. Laganà, A. Ciogli, and F. Gasparrini, 

(18)J. Folkers, P. Laibinis, and G. Whitesides, 

(19) S. Lee, A. Puck, M. Graupe, R. Colo- rado, Y. Shon, T. Lee, and S. Perry, 

 are with Waters Corporation, in Mil- ford, Massachusetts. Direct correspondence to: 

Peer-Reviewed Article

We investigate a phenomenon observed by many practitioners of reversed- phase LC: a dramatic loss in retention volume or time after the column flow is stopped and resumed when using highly aqueous mobile phases with certain columns.

Retention Loss of Reversed-Phase Columns Using Highly Aqueous Mobile Phases: Fundamentals, Mechanism, and Practical Solutions

The application of temperature is frequently employed to enhance analytical extractions, especially with solid samples or volatile analytes. Dating back to the earliest development of modern chemical analysis, such as with Soxhlet extraction, using temperature to enhance analytical extractions continues today with more recently developed techniques. Too often, chemists rely on the rule of thumb from chemical kinetics, which states that reaction rates double for every 10 degree temperature change. However, extractions are not reactions. Temperature impacts solubility, diffusion, surface tension, and other properties of the sample, potentially leading to solute decomposition. This month, we explore the role of temperature in analytical extractions.

Who am I to disagree with Bill Gates? Like the Microsoft founder, I found the book 

Range: How Generalists Triumph in a Specialized World

 by David Epstein (1) to be one of my recommended, thought-provoking reads during the COVID-19 pandemic. Epstein argues that, with exceptions like golf which require rote repetition (such as muscle memory), a breadth of knowledge and experiences are essential for personal and professional
development. He claims that innovators and “systems thinkers” cultivate an “ability to connect disparate pieces of information from many different sources” (1). This philosophy is embraced in the American Chemical Society’s push to include systems thinking of addressing the United Nations Sustainable Development Goals (see, for example, a special issue of 

When it comes to analytical problem solving, the hyperspecialization of our discipline into high-resolution mass spectrometrists, vibrational spectroscopists, open-tubular chromatography gurus, and others can be to our detriment, because the analyst must understand what the nature is of the problem at hand, how might the samples of interest be similar to or different from previous samples, and what tools are available in the analytical arsenal to solve the problem. Fundamental knowledge of our techniques, and their limitations, is essential to applying them in the most appropriate manner.

Many of our analytical extraction methods manipulate temperature to enhance extraction yields. In Soxhlet extraction and its derivatives, accelerated solvent extraction (ASE), also called pressurized solvent extraction (PSE), microwave-assisted extraction (MAE), ultrasound-assisted extraction (USAE), and related methods all use increased operating temperatures to improve extraction yields and accelerate the rate of extraction. As a consequence of the increased solute solubility, solvent use can be dramatically decreased compared to room temperature methods. For volatile analytes, temperature is often elevated with purge and trap, static or dynamic headspace, or thermal desorption systems to drive compounds of interest into the gas phase for trapping and analysis. However, whenever increased temperature is applied to an analytical extraction, it is not as simple as turning up the heat, and more heat (higher temperatures) is not necessarily better. Thermal degradation of sample components is always a concern, but it is also important to note that, while there is a kinetic effect to elevated temperatures, it is thermodynamics that drives the extraction in many cases. In subsequent sections, we provide a broad overview of these temperature effects on analytical extractions.

Generally speaking, increasing temperature increases the solubility of solid solutes in liquid solvents. However, the extent to which this occurs may vary dramatically between solutes. For example, we can see in Figure 1 that the solubility of sugar and potassium nitrate in water changes dramatically as a function of temperature. For sugar, the aqueous solubility of sugar approximately doubles with a temperature increase of 40 °C, and the effect is even greater for potassium nitrate. On the other hand, the water solubility of salt (sodium chloride) is essentially unchanged over a broad temperature range, while for cesium (III) sulfate (Ce

), there is even a solubility decrease as the system rises above room temperature. Now imagine the most probable scenario when our system of analytical interest is a mixture. We cannot be assured extraction enhancement, because increased solubility as a function of temperature is not equivalent for all analytes of interest. Luckily, it is exceedingly rare where we work close to the solubility limits of a chemical system.

A special case of applying increased temperature to liquid solvents is with so-called subcritical or superheated water. At temperatures above 200 °C up to the critical temperature (374 °C), the dielectric constant of water is lowered until it is similar to some common organic solvents (note that increased pressure is also applied to keep water in its liquid state). In this case, the added thermal energy is sufficient to begin to disrupt the hydrogen bonding between water molecules, allowing the “hot water” to begin to solubilize nonpolar solutes, which may be completely insoluble in conventional liquid water. This is the basis for “hot water extraction,” which has shown some promise in the literature, but has yet to be exploited for widespread use.

In supercritical fluid extraction (SFE), the situation is even more complicated. The solvating power of a supercritical fluid is directly related to the fluid density, which is a function of both temperature and pressure. Within a given extraction, pressure is most easily controlled, so temperature is held at a selected value and pressure is used to adjust density (change solubility) if selectivity during extraction is desired. At constant pressure (often the case during an analytical extraction), increasing temperature will decrease density, and, hence, solubility. However, this is not always the case, and, when it is, there is not a clear relationship between temperature, pressure, and solubility. For example, Figure 2 shows the solubility of soybean oil in supercritical carbon dioxide. In this diagram, solubility of the triglycerides is fairly low until a certain temperature (60–70 °C in this case) is reached, at which point solubility increases to a great extent. We can infer that solute fugacity may play some role and numerous equations of state have been developed to predict density and corresponding solubility. Adding an additional level of complexity, and not addressed in this column, is the common approach of adding small amounts (5–20%) of organic co-solvent (modifier) to increase solute solubility in supercritical fluids.

We often use equilibria to describe analytical extractions, though, in many (if not most) cases, we do not operate at equilibrium conditions. Commonly, the octanol-water partition coefficient, K

, is used to estimate relative solubility in extraction solvents:

as the octanol solubility may, for example, mimic solute partitioning through a nonpolar lipid cellular membrane. Given that solute solubility as a function of temperature varies greatly from solute to solute, can we predict what may happen to K

 values? While there are no simple generalizations, we can look at the heat of solution and apply Le Chatelier’s principle—that is, if the dissolution process is exothermic (releases heat), the partition coefficient should decrease with increasing temperature, while for endothermic systems, which absorb heat, the corresponding partition coefficients will increase. The magnitude of the change in partition coefficient will be proportional to the magnitude of the change in the molar heat of solution.

Like solubility, relative volatility can vary to a large extent with temperature, and is dependent on operating pressure and the contribution of other components of the sample mixture. This has even led some to claim that headspace extractions may not be quantitative and was the subject of this “Sample Prep Perspectives” column about two years ago (4). In that column, we claimed, “It makes sense that heating will increase the rate of evaporation, enhancing the mass transfer, and driving analytes into the vapor phase, thus increasing their concentration for subsequent collection. The problem lies in the fact that different molecules possess different volatilities and, thus, differing amounts extracted” (4). This is demonstrated in Figure 3, where aromatic hydrocarbons are sampled using solid-phase microextraction (SPME) in the headspace above samples of olive oil. The results show that, as the sample is heated, the behavior of different sets of compounds change in a less than straightforward manner. This resulting change in headspace composition as a function of temperature not only influences the extraction yield of an individual analytes, but it could also potentially be exploited to gain selectivity or the ability to isolate one com- pound in preference to others in the sample. As a result, we admonished that the extraction temperature during headspace analysis must be well-documented.

It is well-established that chemical extractions do not occur solely via solubility concerns, but also due to the system thermodynamics. Most important, especially when isolating analytes from solid samples, is the role of solute diffusion through the solid. Diffusion is often described using the Stokes-Einstein equation, 

 is activity. At first glance, there is a direct propor- tionality between diffusion and temperature, which means higher temperatures result in fast diffusion. Diffusion, though, is also a characteristic of other solvent properties like viscosity and surface temperature. Starting with viscosity, we can describe the temperature dependence with the Andrade equation, 

, where dynamic viscosity is related to temperature (

) through an exponential function and the constants 

 are available in comprehensive thermodynamic tables. The relationship between surface tension and temperature is an even more complex function also involving the solvent critical temperature as surface tension decreases to zero at the critical temperature. Thus, increasing temperature will increase solute diffusion, speeding extractions, but the relationship with extraction rate is not necessarily linear. We have previously discussed that the effect of diffusion is independent of extraction type (ASE/PSE, MAE, USAE) at constant temperature (6).

The case of supercritical fluids is a bit more confounding. Solute diffusion in supercritical fluids is indirectly related to density via the fluid viscosity. The diffusivity in these fluids decreases with increasing pressure at constant temperature and increases with increasing temperature at constant pressure.

Extractions generally follow a first-order rate model, similar to the kinetics of chemical reactions. However, extractions are due to a combination of solubility and analyte diffusion. Neither alone dictates speed of a reaction and, as we have seen, neither is necessarily a linear function of temperature. So, while adages like “doubling the rate with every ten degree temperature change” may have merit to estimate reaction kinetics, this does not hold for analytical extractions.

Any time we heat a sample, breakdown, usually by oxidation, is a concern. A good analytical practice is to run suitable standards or well-characterized samples and check for degradation products. Is the degradation concern exacerbated with the temperatures used in modern analytical extractions? This was a concern in the early development of ASE and was addressed in research by Ezzell (7). He looked at the ASE of dicumyl peroxide (DCP), a known free radical generator. Half-life calculations predicted that up to 30% decomposition would be expected in at 7.5 min extraction at 150 °C. Next, DCP was spiked onto sand and extracted via ASE with hexane, first at 100 °C, then at 150 °C, with a 10 min heat and extract time. At 100 °C, no sample degradation was observed, as 101% recovery with a 5.9% relative standard deviation (RSD) was obtained. With an extraction at 150 °C, extraction recovery dropped to 77%, close (within 75–80%) to the estimated 30% decomposition. In both cases, the solvent bottle was pressurized with air and was not degassed. When the hexane was degassed and pressurized with nitrogen, the extraction yield at 150 °C increased to 91% with a 0.83% RSD, demonstrating that when proper precautions are taken, thermal decomposition can be avoided in many cases. It is assumed that these findings, with similar precautions, are transferrable to other techniques. For example, Ezzell also noted that degradation of unsaturated fatty acids during extraction of triglycerides from oilseeds with ASE at 130 °C was similar to that observed during Soxhlet extraction. However, free-radical generation with ultrasound extractions is well-known among practitioners, in this case because of the high sonic energy applied during the extraction.

The development of modern analytical extractions has progressed through the application of increased extraction temperature. In fact, aside from solute solubility in the chosen extracting solvent, applied temperature is perhaps the single most important parameter (along with particle size, for solid samples) driving sample extractability and, to a lesser extent, selectivity. However, to most effectively exploit the role of temperature in extraction, the analyst must have the suitable combination of knowledge and experience with their sample type and their extraction techniques.

Range: How Generalists Triumph in a World of Specialists

 (Riverhead Books/Random House, New York, New York, 2019).

(2) P.G. Mahaffy, F.M. Ho, J.A. Haack, and E.J. Brush, 

(5) S. Vichi, L. Pizzale, L.S. Conte, S. Buxaderas, and E. Lopez-Tamames, 

(7) J. Ezzell, Thermo-Fisher Scientific Technical Note 206 (2014).

 is a Department Head and Associate Professor at South Dakota State University. His research interests include green chemistry, alternative solvents, sample preparation, high-resolution chromatography, and bioprocessing in supercritical fluids. He earned his PhD in 1990 at Brigham Young University under the direction of Milton L. Lee. Raynie is a member of LCGC’s editorial advisory board. Direct correspondence about this column via e-mail to 

Sample Prep Perspectives

Temperature is frequently employed to enhance analytical extractions, especially with solid samples or volatile analytes. Using temperature to enhance analytical extractions continues today with more recently developed techniques, which we explore.

Turning Up the Heat: The Effect of Temperature on Analytical Extractions

Gas chromatography (GC) is among the richest data-producing techniques in analytical chemistry. A chromatogram can provide a wealth of information about an individual analyte in a sample, about the sample itself, and about how well the instrument is performing. Traditional isothermal chromatograms provide useful information about the thermodynamics and kinetics of the analyte-stationary phase interactions and whether these are changing over time. They also provide measures of instrument performance through theoretical plate and tailing factor calculations. Many of these determinations are automatically performed by today’s data systems, but they trace their origins to calculations and simplifications that were done in days when chromatograms were printed on rolls of paper and calculations were done with slide rules. We will see how our data systems both assist and hinder in obtaining maximum information from chromatograms.

The fundamental data produced by a gas chromatography (GC) experiment is a plot of detector signal vs. time, called a chromatogram. A typical chromatogram comprised of a mixture of several common solvents is seen in Figure 1. The figure caption includes the experimental information that should be provided along with any chromatogram, including the instrument it was obtained with, carrier gas, the inlet and detector conditions, injection technique, column dimensions, stationary phase, and temperature conditions. Identities of as many of the peaks as possible should also be provided.

In the early days of GC, most of the traditional data values, such as retention times, peak widths, and peak areas, were measured from the chromatogram by hand, using output from a strip chart recorder. Think of a paper electrocardiogram (EKG) strip in your doctor’s office or hospital, or the seismographs seen in movies. Strip chart recorders are often still used in applications like temperature monitoring. Retention times were calculated by hand by measuring the distance on the paper from the start of the chromatogram with a ruler (in cm) and dividing by the chart speed (in cm/min). Peak widths were determined by drawing tangent lines to the plot at the baseline and measuring the distance between them at the baseline. Peak areas were often determined by counting squares (chart recorders used rolls of graph paper) by cutting the peaks out with scissors and weighing them. Finally, the origins of the calculation of performance terms, like theoretical plate counts and tailing factors, go back to measuring the needed quantities by hand.

There are numerous calculations in chromatography that not only provide analytical performance data and figures of merit, but insight about the chemistry of the analyte and the separation as well. Our classical definition of the retention time, seen in equation 1 below, tells us that the total retention time (

) is the sum of the adjusted retention time (t’

), the time spent sorbed on or in the stationary phase, plus the hold-up time (

), the time spent moving in the mobile phase.

The hold-up time is usually determined in a separate experiment or calculated from the column dimensions, gas flow rate, and temperature by the data system (1). For good chromatography, we often advise that t’

 should be at least two but not more than 20 times t

The three most reported measures of a chromatographic peak, which are retention time, peak width, and peak area, each relate to a different and important aspect of the chemistry of the analyte. Retention time relates the thermodynamics of the intermolecular interactions between the analyte and the stationary phase. Peak width relates the kinetics of the sorption process at the stationary phase surface and the diffusion processes within the mobile and stationary phases. Finally, the peak area or height relates to the amount of analyte present. We will now discuss retention time and peak width, which relate to the thermodynamics and kinetics of the separation.

All chromatographic techniques (and extraction techniques) are dependent on the thermodynamics of the simple chemical equilibrium shown in equation 2, in which an analyte that begins completely dissolved or vaporized in a mobile phase partitions between being absorbed on, or dissolved in, a stationary phase. For extraction, a second stationary phase is usually substituted for the mobile phase, but the same principle of phase transition at a boundary applies. In a previous column, we discussed how this theory leads to the concept of selectivity which governs how the chemistry of solute-stationary phase interactions generates separation power (2).

, is calculated as the ratio of the adjusted retention time and the hold-up time, as seen in equation 3.

The retention factor has a deeper physical meaning, as it is also equal to the ratio of the mass of analyte sorbed in the stationary phase at a given instant to the mass of analyte vaporized in the mobile phase. This allows connection to the concentration equilibrium constant through the phase ratio, which is the ratio of the volume of the mobile phase in the column to the volume of the stationary phase, as seen in equation 4.

For GC, how do data systems both assist and hinder us in obtaining maximum information from chromatograms? We explain how a chromatogram can provide a wealth of information about an individual analyte in a sample, about the sample itself, and about how well a GC instrument is performing.

January 2021 | LCGC North America

LC Troubleshooting Odds and Ends from 2020

Tips for Electrospray Ionization LC–MS

Retention Loss of Reversed-Phase Columns Using Highly Aqueous Mobile Phases: Fundamentals, Mechanism, and Practical Solutions

Turning Up the Heat: The Effect of Temperature on Analytical Extractions

What Chromatograms Can Teach Us About Our Analytes

The Multi-Attribute Method (MAM) for the Characterization of Biopharmaceuticals