details the US Food and Drug Administration (FDA)’s recent expansion to 30 analytes, from a previous 16, in the method for determining per- and polyfluoroalkyl substances (PFAS) in the US food supply, which, in turn, may mean that additional analytes may still yet be identified (1). The FDA’s action was preceded by a March 2022 guidance document from the European Union Reference Laboratory for Halogenated Persistent Organic Pollutants in Feed and Food (EURL POPs) defining method parameters for finding priority PFAS of interest, as well as limits of quantification (LOQs). 

 reached out to the FDA for further comment on this study, and the agency’s responses are presented here in a question-and-answer format. Some minor edits for clarity may have been made.

Food donations on the table. Text Donation. Close up. | Image Credit: © fotofabrika - stock.adobe.com

Q: The study explains the reasoning behind some of the choices made for which samples to use (such as chocolate milk vs. regular milk). Can you provide some insight into why some of the other foods were chosen?

The matrices were chosen to represent different food categories. Lettuce and blueberries represent fruits and vegetables, milk and eggs for dairy, salmon and clams for meat and seafood, and bread for grains. For agricultural samples, corn snaplage and corn silage were chosen based on experience with these being challenging matrices.

Q: What is the working relationship between EURL POPs and the FDA (and, presumably, similar agencies in other parts of the world) when it comes to PFAS? That is to say, do these different agencies check and balance each other to attempt to set global standards for LOQs?

The Association of Official Analytical Chemists (AOAC) is an international organization that brings together government, industry, and academia to establish standard methods of analysis. They also develop standard method performance requirements (SMPRs), which describe the minimum recommended performance characteristics to be used during the evaluation of a method. During 2023, a SMPR for PFAS in produce, beverages, dairy products, egg, seafood, meat products, and feed was developed that defines method performance requirements and required limits of quantification. The working group for this SMPR
was chaired by the FDA and included members who are experts in PFAS analysis from a variety of sectors and countries. Standards for LOQs were set during this process.

Q: Among the techniques mentioned in this study are solid-phase extraction (SPE), liquid chromatography (LC), and mass spectrometry (MS). Can you explain the significance and importance of chromatographic techniques in your research?

Due to a large number of potential matrix interferences in food and feed, SPE was essential to be able to remove co-eluting interferences. Additionally, the use of a longer column (in this case 150 mm) was necessary to improve the resolution of matrix interferences from target analytes and prevent detection of false positives.

Q: It seems that there is much still to be learnt about quantification levels for hundreds, perhaps thousands, of PFAS, although several key ones are closely monitored. Is that accurate?

Currently the FDA method focuses on legacy PFAS that have been identified as stable end products in the environment, such as long-chain perfluorosulfonic acids (PFSAs), and long-chain perfluoroalkyl carboxylic acids (PFCAs) that have the potential to uptake into food, and emerging PFAS in which analytical standards are available. There are still a lot of unknowns about the number of PFAS present in the environment, their physical chemical properties, toxicity, and ability to transport into food. The FDA continues to develop methods, including those using high-resolution mass spectrometry (HRMS), to gain a better understanding of additional PFAS that may be present in food.

(1) Genualdi, S.; Young, W.; Peprah, E.; et al. Analyte and Matrix Method Extension of Per- and Polyfluoroalkyl Substances in Food and Feed. 

Articles

A new study details the US Food and Drug Administration (FDA)’s recent expansion to 30 analytes, from a previous 16, in the method for determining per- and polyfluoroalkyl substances (PFAS) in the US food supply, which, in turn, may mean that additional analytes may still yet be identified (1).

FDA Talks to LCGC About Chromatographic Techniques for PFAS Detection in Food Supply

California State University, Los Angeles (Cal State LA) (Los Angeles, USA) and Leco Corporation (St. Joseph, Michigan, USA) have unveiled the collaborative Leco Complex Chemical Compositional Analysis Lab at Cal State LA’s Rosser Hall. The lab offers a collaborative space for students, faculty, and industry partners to explore complex chemical samples. Spearheaded by Petr Vozka from the Department of Chemistry and Biochemistry, the lab aims to educate and train both undergraduate and graduate students. “Our mission is to mold adept students ready to lead in the industry and excel in top-tier graduate programmes. Every milestone, every achievement, is a testament to our collective efforts,” he said. René Vellanoweth, dean of the College of Natural and Social Sciences at Cal State LA, commented: “Our country was built on the private-public relationship, and that’s exactly what Petr Vozka has done here. He’s brought the private sector to campus. Our local community will benefit from this relationship.” Farai Rukunda, director of separation science at Leco Corporation, added, “Cal State LA, Leco Corporation is very proud of the work you do. You’re creating future scientists who are helping us solve tomorrow’s problems today.”

Image Credit: © J. Emilo Flores/Cal State LA

California State University, Los Angeles (Cal State LA) (Los Angeles, USA) and Leco Corporation (St. Joseph, Michigan, USA) have unveiled the collaborative Leco Complex Chemical Compositional Analysis Lab at Cal State LA’s Rosser Hall.

Cal State LA and Leco Launch Chemical Analysis Lab

Manufacturing capillary gas chromatography (GC) columns is a very complex procedure, with many production factors to consider. In this 

Blog, Tony Taylor lists some of the vital components of the GC column making process.

 is Group Technical Director of Crawford Scientific Group and CHROMacademy. His background is in pharmaceutical R&D and polymer chemistry, but he has spent the past 20 years in training and consulting, working with Crawford Scientific Group clients to ensure they attain the very best analytical science possible. He has trained and consulted with thousands of analytical chemists globally and is passionate about professional development in separation science, developing CHROMacademy as a means to provide high-quality online education to analytical chemists. His current research interests include HPLC column selectivity codification, advanced automated sample preparation, and LC–MS and GC–MS for materials characterization, especially in the field of extractables and leachables analysis.

After having recently written about how to kill your gas chromatography (GC) column (1), I wanted to “flip” the situation and explain a little about how wall coated open tubular (WCOT) capillary GC columns are manufactured. Figure 1 presents a typical cross-section of a WCOT column, showing the fused silica tubing with its polyimide coating and internally coated film of stationary phase.

I’ve always believed that by gaining an insight into the manufacture of the columns we use daily for GC applications, we can reach a deeper understanding of analytical problems as they occur.

The length of the list below indicates just how complex GC column manufacturing can be; steps 2–13 alone typically take between 10 and 12 days to complete.

Filling with dissolved stationary phase or monomers

Let’s look at some of the steps in more detail and explore possible implications to problems with the column in use. With this, we can pick up some troubleshooting hints related to the manufacture of the world’s most used chromatography columns.

Figure 2 shows a typical manufacturing process for the slow draw/low tension process of fused silica capillaries (2). It should be noted that an even more complex process is used for fast draw/high tension processes.

Synthetic fused silica rods are fed into a 2000 ºC graphite furnace (often 10 m above the production floor), which is gas-shielded. The silica melts under precise heating conditions and is “drawn” by a capstan, which is many metres away on the factory floor. The drawing speed and tension are very closely controlled, as these parameters dictate the uniformity of the tubing’s outer and inner diameters. These parameters are also closely monitored by laser micrometers positioned within the drawing rig, which are connected to the capstan so that draw speed may be adjusted to maintain the capillary diameter within specification tolerance. Available data show that silica capillary manufacturers can control within around 4% of the nominal internal diameter, which, for a 0.53 mm capillary, would be 0.508–0.554 mm. This may not seem significant, but it equates to approximately a 10% variation in the optimum linear carrier gas velocity or 20% in column volume for capillaries of nominally the same length.

Along the drawing path, several coating baths apply successive layers of polyamic acid solution, which are subsequently cured to build the yellow/brown outer coating we are all familiar with; this imparts mechanical strength, protection from abrasive damage, and flexibility to the capillary. A single “draw” operation can produce as much as 15 km of capillary with 0.25 mm internal diameter at speeds between 3 and 40 m per minute.

Improper or poorly cured polyimide layers can lead to issues with the quality of column cuts. Under-cured polyimide is relatively soft and does not yield easily to most tools used for cutting capillary columns. Clean cuts (defined as cuts at approximately 90° to the column axis with only minor protrusions or voids of glass or polymer and no silica chip formation) are quite difficult to achieve with poorly cured polyimides. Such “ragged” column cuts can lead to issues such as peak tailing and/or splitting; chips of silica may fall inside the column, leading to irreparable damage of the stationary phase and exposure of the underlying silica, which will typically give tailing peaks with more polar analytes.

To reduce the level of surface activity within the drawn capillary tubing, it is possible to complete the drawing process with the inner surface of the capillary under an inert gas atmosphere, which reduces the level of acids of nitrogen forming on the inner surface. When combined with residual or atmospheric water, as shown in Figure 3, the silica will hydrolyze to active silanol groups (2). Controlling the level and homogeneity of any residual surface silanol species is important for the next phase of capillary column production.

The leaching process typically involves an acid wash, which can help to remove impurities such as chlorine, acids of nitrogen, and other sources of catalytic activity such as metal ions. All of these can ultimately give rise to active sites, which will cause peak tailing with more polar analytes.

Next, the inner surface is hydrolyzed to maximize the concentration of surface silanol species. Whilst this may seem counter-intuitive, as silanol species cause peak tailing with polar analytes, it does ensure that further hydrolysis post-stationary phase deposition is less likely, and that the silanol concentration is normalized from batch to batch.

The next stage in the production process is to block or deactivate the surface silanol species using purified and well-characterized reagents. Impurities in the deactivation reagent may lead to problems with the column coating, and changes in the composition of the deactivation reagent(s) can lead to batch-to-batch variation in the stationary phase bleed profile. Reagents such as organochlorosilanes, alkoxysilanes, hexamethyldisilazine, or other reactive compounds are used for the chemical deactivation process. The reagents and reaction conditions used tend to be proprietary to manufacturers, and the variation in deactivation chemistry are often responsible for the differences in column performance between manufacturers. Deactivation chemistry can also be “tuned” for various classes of problematic analyte and the resulting phases are designated as “optimized” for a named application.

Finally, in this stage of production, further treatments may be added to optimize the “wettability” of the surface to less polar or more polar stationary phase polymers. This helps to ensure a uniform stationary phase deposition and, hence, optimized column efficiency. The column is then washed with a pure solvent and dried under an inert atmosphere.

The next stage in the process is coating and cross-linking, which is critical to ensure good chromatographic resolution and reproducibility. It is important to carefully control phase (film) thickness and homogeneity. Most modern columns are cross-linked to bind them tightly to the inner wall of the column, adding thermal stability, lowering activity, and giving the ability to solvent wash the column if required.

The purity and chemistry of the polymer used to coat the column is of utmost importance. Good manufacturers will synthesize, purify, and test the polymers in-house prior to coating, to ensure quality and reproducibility. Small variations in the ratio of the monomers within the polymer can cause large relative retention shifts, so manufacturers will check each batch of polymer using the retention indices of test mixes. They may also remove lower molecular weight fractions of the polymer to reduce column bleed to acceptable levels. Again, column bleed may be tested on a small number of columns prior to the polymer batch being accepted for large-scale manufacture.

Once the polymer has been demonstrated to be fit for purpose, it is dissolved in a suitable (usually proprietary and optimized) solvent mix at a concentration that will ultimately determine the stationary phase film thickness.

Most modern WCOT capillary GC columns are coated using a “static coating” process in which the entire column is filled with the stationary phase solution, one end carefully sealed, and the other end connected to a vacuum pump. As seen in Figure 4, the column is held at a constant and optimized temperature—typically using a water bath—and the volatile solvent evaporates back towards to the plugged end of the column (3).

The level of vacuum applied and the temperature must be precisely controlled to achieve the correct rate of evaporation of the solvent to avoid “bumping” of the stationary phase, which results in a non-homogenous deposition of the stationary phase and poor efficiency. The temperature of the column is typically controlled via immersion into a water batch, which is shown in Figure 5. A “bumped” GC stationary phase is shown in Figure 6 where “gaps” or “bubbles” within the stationary phase can be seen as the lighter regions highlighted in the figure.

For columns that require higher thermal stability, the polymeric molecular weight and degree of cross-linking need to be considerably higher, and the polymer has gum-like physical properties; consequently, the production of a useable polymer “solution” may not be possible. In this case, oligomers (or other precursors of the final polymer) and polymerization initiators are coated onto the capillary wall. The polymerization reaction can then be performed in situ either before or after solvent evaporation, in an oxygen-free environment. These “cross-linking” processes are highly proprietary, as they are, in part, responsible for the thermal and chemical stability of the stationary phase, effectively immobilizing the coated polymer onto the inner wall of the capillary column. These processes are the “secret sauce” of the column manufacturer, and almost nothing is available online or in patents regarding cross-linking or immobilization chemistry.

As mentioned above, when using the static coating technique, the film thickness of the stationary phase is controlled using the concentration of the polymer or monomers/oligomers used to coat the inner wall of the capillary. The phase ratio (β) of the column is the ratio of the volume of stationary phase to the amount of carrier gas within the capillary, and this is a critical parameter to ensure reproducible analyte retention time from different batches of columns.

This goes some way to explaining why the variations in capillary inner diameter are so important and how any unexpected variance in the column inner diameter (2d in equation 1) may cause variation in the phase ratio if the polymer concentration, and therefore the film thickness, used to coat the column is constant. Therefore, to avoid batch-to-batch variability, manufacturers may measure the external and internal diameters of the capillary column and make small adjustments to the polymer concentration to maintain a constant phase ratio on a batch-to-batch basis. This should ensure that the pressure applied by the electronic pressure control of the GC process does not have to be altered to obtain the same analyte retention time after changing to a new column of the same stationary phase and physical dimensions. However, no matter how diligent the manufacturer, it is almost impossible to obtain an exact phase ratio throughout the entire length of the capillary column—that is to say, the ratio of column internal diameter to coating film thickness may subtly vary along the length of the column. This is the reason why if one cuts a 60 m GC column exactly in half, retention times from each of the two resulting 30 m columns may vary!

Following the application of the stationary phase and any cross-linking, any unreacted polymer or impurities are removed from the column through solvent rinsing using the appropriate solvents.

After drying in an inert atmosphere, the column may be heated (cured) prior to any final “special treatments”, which are primarily chemical modifications of the stationary phase or underlying silica surface. These treatments may, again, modify the stationary phase to perform particularly well with certain analyte classes. The modification chemistry may be performed using gas phase or vapour deposition techniques.

The column is then heated (cured) by gently raising the column temperature in an oven containing an inert gas, up to its maximum operating temperature. This will expel any remaining by-products and impurities from the column, but this “bleed” will quickly reduce to a level that represents the bleed profile of the new column. It should be noted that WCOT GC columns bleed all the time, but these modern manufacturing techniques and treatments ensure that we have extremely low levels of underlying bleed for our analyses. The columns will continue to produce low levels of bleed if we are diligent in excluding oxygen, moisture, and contaminants from the column during routine use, typically by using high-quality carrier gases and using gas filters.

Finally, the columns are QC tested by manufacturers, who choose test mixes that contain analytes to act as probes for the phase chemistry under test, or the specific application for which the column will be used. The probes are typically chosen to highlight any issues with retention, selectivity, efficiency, and peak shape, exploring the phase chemistry, phase ratio, phase bleed, and the deactivation chemistry of the stationary phase. Some manufacturers will test each individual column whilst others may test only a selection of columns from a particular batch. Typically, the test chromatograms will be obtained under isothermal conditions, which tend to reveal more about test probe peak shape and efficiency than temperature-programmed operation, where peaks are sharpened because of thermal focusing and lower column residence times. Manufacturers will have their own internal test specifications, which may be more stringent than the specifications provided within their sales literature.

I hope that this has given you some insights into the complexity of GC column manufacturing and the care with which manufacturers take to produce a column that will perform to our exacting standards out of the box. I also hope that this information helps with your future troubleshooting efforts.

https://www.chromatographyonline.com/view/gc-column-killers-

(2) Griffin, S. Fused-Silica Capillary—The Story Behind the Technology. 

(3) Majors, R; Decker, D.; Vickers, A. K. The Art and Science of GC Capillary Column Production. 

is chief scientific officer of Element Materials Technology and technical director of CHROMacademy. His background is in pharmaceutical R&D and polymer chemistry, but he has spent the past 20 years in training and consulting, working with clients to ensure they attain the very best analytical science possible. He has trained and consulted with thousands of analytical chemists globally and is passionate about professional development in separation science, developing CHROMacademy to provide high-quality online education to analytical chemists. His current research interests include HPLC column selectivity codification, advanced automated sample preparation, and LC–MS and GC–MS for materials characterization, especially in the field of extractables and leachables analysis.

Events

A list of some of the vital components of the GC column-making process.

Capillary GC Column Manufacture—A Troubleshooting Insight

Similar to Stephen Covey’s “Seven Habits of Highly Effective People,” effective troubleshooters take a systematic approach to liquid chromatography (LC) troubleshooting and rely on several key principles to help them navigate the complex task of troubleshooting. In this installment I add to this list of principles described in prior installments with three specific ideas: 1) Ask—does it make sense?; 2) Get a second opinion; and 3) Join a chromatography discussion group to help grow your chromatography network.

 is the editor of “LC Troubleshooting”. Stoll is a professor and the co-chair of chemistry at Gustavus Adolphus College in St. Peter, Minnesota, USA. His primary research focus is on the development of 2D-LC for both targeted and untargeted analyses. He has authored or coauthored more than 75 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: 

As 2023 comes to a close, I’ve been reflecting a bit on the problems with instrumentation that I’ve encountered this year, both through messages from folks in my professional network who ask me troubleshooting questions, and in my own laboratory. In the process of thinking about these various problems, a few themes have emerged, and I think it is worthwhile sharing them here because—at least on the timescale of a career spent working with instruments—they are relevant to all of us at some point. I’m a big fan of systems—systems-based approaches to tackling complex problems, and a systematic approach to problem solving. Maybe this is the training I had as a young scientist rubbing off on other parts of my work, but I think a systematic approach to liquid chromatography (LC) troubleshooting is very valuable because it leaves us with “results” that we can interpret and use to inform rational next steps in the troubleshooting process. If we don’t follow a systematic approach, the only tool we have at our disposal is a trial-and-error approach, which is usually frustrating, and it can also be very expensive. In this installment, I elaborate on this point using troubleshooting cases I’ve encountered this year to emphasize important things to keep in mind, including getting a second opinion and the value of a robust professional network.

In the October 2020 installment of “LC Troubleshooting,” I wrote about some essential principles of effective troubleshooting (1), referring to a manual developed by the U.S. Army that provides an introduction to logical troubleshooting (2). The list of principles included:

Build up knowledge about expected behavior

In this installment, I’d like to extend this list with two additional ideas:

Developing troubleshooting habits based on these principles can lead to more effective and efficient troubleshooting over time, reduce stress over instruments that don’t work, and lead to significant savings in the cost of instrument operation.

A few troubleshooting cases this year have highlighted the importance of asking a basic question when considering potential causes of instrument malfunction, and potential solutions—does it (that is, the cause or solution) make sense? Part of what makes troubleshooting most analytical instrumentation challenging is that there are so many ways for things to go wrong. Given all these possibilities, it is also not hard to come up with a pretty long list of potential causes and solutions. Moreover, it is typically prohibitively expensive to actually evaluate all the potential causes and solutions in the laboratory. Thus, it is exceedingly important to critically evaluate each of them so that we can prioritize which ones from the list we will actually evaluate. Prioritizing the wrong possibilities can lead to a lot of wasted time, effort, and money working through the causes that are unlikely to be the real problem, and the solutions that are unlikely to work.

So, how do we actually evaluate the potential causes and solutions? I guess as individual troubleshooters we either need to have the expertise and knowledge needed to critically evaluate the causes and solutions, or we need to seek out the expertise and knowledge from other individuals or sources. As I often say to my students, in 2023 the question is not whether information on a particular topic exists, but rather discerning which information is “good” (as in correct, accessible, and approachable), or “bad.” Determining which troubleshooting advice is good or bad can be tricky, especially if it comes from a source unfamiliar to us. At a minimum, though, we can ask a simple, yet powerful question—does it make sense? A couple of months ago when I was playing around with ChatGPT, I asked it some LC troubleshooting questions. For example, I asked it: “What should I do if the pressure on my HPLC instrument is too high?” Some of the responses made good sense, including: 1) “Check the column: Make sure that the column is properly installed and has not been damaged. Check for any clogs or debris in the column that may be causing the pressure to increase”; and 2) “Check the flow rate: Verify that the flow rate is within the recommended range for the column and the instrument. If the flow rate is too high, it can cause increased pressure.” On the other hand, some responses did not make sense at all. For example: “Check the detector: Verify that the detector is properly calibrated and functioning correctly. If the detector is not calibrated correctly, it can cause increased pressure.” This simply has no basis in reality. How could calibration of a detector affect the pressure drop in an LC system? In this case, I would not seriously consider evaluating this potential cause of my pressure problems, and move on to other possibilities instead.

Another real-life troubleshooting example from the mailbag will help illustrate the value of asking—does it make sense? Earlier this year, a PhD chemist with considerable experience in LC reached out to me about a problem with a pump that had been elusive. They explained to me that the main symptom they observed was bubbles in the waste line of the pump during purging, and that after purging, the pump would slowly lose pressure to the point where the pump was unusable. They also indicated that the pump vendor suggested that the cause of these symptoms was that their method involved a high concentration of a commonly used organic solvent (and not tetrahydrofuran [THF], by the way). My first reaction upon hearing the facts of the case was that the stated cause of the symptoms simply did not make any sense. I could not imagine any physically- or chemically-based line of reasoning that would lead to this explanation. Although the suggested cause of the problem could possibly have been correct, it seemed improbable, and there would be many other explanations that I would put on a list before the one that was suggested. In the end, after further investigation, it turned out that the actual 

cause of the bubbles was that the pump head was so loose that it was drawing air into the pump head from the back, and then pushing that air out of the head, which manifested as bubbles in the waste stream.

Get a Second Opinion, Particularly if the Fix is Going to Be Expensive

On two separate occasions in the past year, a troubleshooting exercise I’ve participated in has led to the conclusion that a very expensive repair would be required involving the replacement of an electronic board. In each case, the troubleshooting process was guided remotely by a person very knowledgeable about the particular instrument. In the first instance, I contacted a different person I knew that had intimate knowledge of the instrument, purely on a hunch that we should double-check to be sure we were not overlooking a different explanation for the cause of the symptoms. Indeed, the second person suggested a completely different potential cause, and it turned out that resolving this problem, which was entirely software-related, resolved the root cause and we did not have to replace any parts at all! Having had this experience, it was natural for me to seek a second opinion again a few months later when we encountered a different set of symptoms with the same instrument. Again, the suggested remedy was replacement of a very expensive electronic board. As in the first case, a second expert on the instrument suggested a different line of inquiry that ultimately concluded in finding that the observed symptoms were software-related and could be addressed at the level of the software, rather than replacing electronic components of the instrument.

No troubleshooter I know has a perfect track record, and sometimes the best of us misdiagnose. The point here is not that I think we can completely eliminate those mistakes and oversights. Rather, the lesson I’ve learned from these troubleshooting exercises is that if the conclusion of the exercise is that I’m going to spend a lot of time and money on a repair, then I will always get a second opinion moving forward. Much like it is common to get second opinions on health matters in cases where the suggested intervention is going to be painful, expensive, or both, we should also feel comfortable reaching out for a second opinion in cases of troubleshooting complex instrumentation where there is high potential for misdiagnosis and painful and expensive repairs.

Professional Networks Hold Tremendous Value—Grow Yours, and Use It to Help You Troubleshoot

I live in the upper Midwestern state of Minnesota in the United States, and we have a local (regional) professional organization for chromatographers and those with some affinity for chromatography called the Minnesota Chromatography Forum (MCF). I have been involved with MCF in various ways for approximately 20 years, but currently I chair the Symposium and Educational committees. At our most recent board meeting, we were discussing the trajectory of the organization and related factors including a lot of turnover in membership as we see long-time members retire, and many new people coming into the field. We also discussed how the Covid-19 pandemic has or has not affected how scientists and their employers interact with an organization like MCF. At one point during the discussion one of the board members asked rather pointedly—what is our response to people who ask what is the value of membership in MCF? In other words, why should they bother joining and regularly attend MCF events (typically three quarterly meetings and an annual symposium, in our case)? I think this is a fair question, especially in 2023, post-pandemic, in a time when it seems increasingly likely that people turn more to AI tools like ChatGPT for answers rather than consult the historical sources of expertise, such as books and expert sources like 

 magazine. However, as I thought about the question after our board meeting, alongside of my thoughts about this installment of LC Troubleshooting, it occurred to me there is a deep and important connection here. A big reason to join a chromatography discussion group is that it can be a really efficient way to grow your professional network, and a network of 10, or 30, or 100 chromatographers that you can reach out to at the drop of a hat to get some troubleshooting advice is invaluable. Just think about this—an annual membership in the MCF costs a whopping $25. This fee buys you admission to quarterly MCF meetings where you get to know tens of other chromatographers in the area. There is a good chance that one of them will have good advice when you encounter the next problem with your LC instrument that you can’t answer. If their advice saves you from a single visit by a service engineer, this will probably save you or your employer enough money to pay for a lifetime membership in the MCF.

On a related note, recently Dr. Jim Grinias and I interviewed Dr. Kevin Schug for 

www.chromatographyonline.com/analytically-speaking-podcast

). I like to finish these conversations with some quick, light questions, and one of them is: “If you could wave a magic wand and solve any problem in your laboratory, what it would it be?” Kevin’s answer (paraphrasing here) was that he would wish to have service contracts for all the instruments in his laboratory. As an academic researcher (Kevin is at the University of Texas at Arlington), instrument maintenance is an acute, persistent challenge because the organizations we typically seek funding from (as well as our host institutions), such as corporate sponsors and governmental agencies, are not fond of paying for instrument maintenance. My point in bringing this up here is that in laboratories where funds for service contracts simply are not available, having a professional network to lean on for troubleshooting advice (and sometimes even loaning instrument parts!) is very valuable.

What Other Chromatography Discussion Groups Are There?

I don’t have a comprehensive list of chromatography discussion groups around the world, but a considerable number of groups in the United States are listed at the SIS website: 

www.sisweb.com/referenc/sites/chmtgrop.htm

. Some of the groups I have personally interacted with over the years are the Chromatography Forum of the Delaware Valley (CFDV; 

), the North Jersey Chromatography Discussion Group (

). I especially encourage young scientists and new users of chromatography to find a discussion group and start building a network of separation scientists that they can reach out to in the future for troubleshooting or other professional advice.

In this installment of “LC Troubleshooting,” I’ve discussed some habits and practices that can improve the effectiveness and efficiency of any troubleshooter. These include asking the question “does it make sense?” when considering the potential causes of a problem with an LC instrument, as well as potential solutions to solve the problem. Also, increasingly, I think that getting a second opinion on a diagnosis of an instrument problem is a good idea, especially when the solution that is suggested to solve the problem is expensive, intrusive, or both. Finally, I strongly encourage chromatography users to engage a local chromatography discussion group as a way of building a professional network of separation scientists. These networks are great resources for us to call upon when troubleshooting a specific LC problem, or looking for a second opinion.

(1) Stoll, D. R. Some Essential Principles of Effective Troubleshooting. 

(2) Introduction to Logical Troubleshooting, 1996. 

https://www.militarynewbie.com/wp-content/uploads/2013/11/US-Army-electronics-course-Introduction-to-Logical-Troubleshooting-IT0338.pdf

 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 75 peer-reviewed publications and four book chapters in separation science and more than 100 conference presentations. He is also a member of 

’s editorial advisory board. Direct correspondence to: 

There are three important habits and practices that can improve the effectiveness and efficiency of any troubleshooter. 

Troubleshooting Odds and Ends to Close Out 2023: Questions from the Mailbag, and Second Opinions

Many developments in silica particles used in liquid chromatography have been well documented over the years. The move from irregular silica to spherical silica, the decrease in particle size from >5µm particle in HPLC to sub-2-µm particle size in UHPLC, the improved silica purity of type B silica over that of type A silica, and more recently the adoption of superficially porous particles versus traditional fully porous particles. One area of development that has been discussed less and is still open to debate is the particle size distribution (PSD) of these chromatographic materials. In this article, we discuss the move towards improved monodispersity of silica particles for use in high performance liquid chromatography (HPLC) and how the use of monodisperse particles can impact the resulting chromatographic parameters such as reduced plate height and column impedance. On a practical level we review how the reduction of PSD impacts efficiency, backpressure and sensitivity.

Chromatographic phases have come a long way since the early large pellicular particles that were in the range of 30–80 μm. In the 1970s, 10-μm and 5-μm spherical fully porous particles (FPPs) superseded pellicular particles and became the dominant particle of choice. Since then, particle sizes have been reduced still further with 3-μm and sub- 2-μm diameters, adding a higher degree of efficiency to separations, albeit at the expense of increased backpressure.

Silica-based spherical FPPs have many benefits, including a high surface area, high physical strength, and robust nature of the columns produced. This is why silica remains today the number one support material for chromatographic stationary phases despite the availability of other materials such as carbon, polymeric supports, zirconia, and hybrid materials, which have all been evaluated over the years. Because of the high surface area and the highly reactive nature of amorphous silica, there are few limitations to the stationary phase types that have been bound to the surface to enhance selectivity. This combination of selectivity from the stationary phase and efficiency from the particle is paramount to any separation in high performance liquid chromatography (HPLC) and ultrahigh-pressure LC (UHPLC).

Many early silica powders developed for use in chromatography were generated by the destabilization and aggregation of silicate solutions. They possessed irregular morphology and broad particle size distribution coupled with high impurity levels from metal ion contaminants.

In 1968, Stober and associates (1) designed a process for growing non-porous silica particles. By mixing alkyl silicate with ammonium in a water-alcohol solution, the formation of spherical silica particles was achieved, with the ability to produce different particles sizes by altering the reaction conditions. The problem was that this produced non-porous particles only. Later developments led to surfactants and porogens being introduced as a modification to the Stober process (2), which allowed silica morphology to be manipulated, producing what we know today as fully porous silica particles.

Commercial silicas produced using variations of the modified Stober process tend to have a wide particle size distribution (polydisperse). Previously sub-2-um, monodisperse particles have been manufactured and been assessed in literature (3,4). However, the major drawback of these early attempts was the lack of scaling between particle sizes, meaning its use as a commercial phase was limited. By carefully manipulating the processing conditions, a new commercial, monodisperse FPP (MFPP) has been produced. This process has been tailored to produce particle sizes ranging from sub-2-μm through to 10 μm.

The difference in uniformity between polydisperse and monodisperse particles can be seen in Figure 1. The scanning electron microscopy (SEM) images of traditional HPLC particles and new monodisperse particles visually highlights the uniform size distribution of the new monodisperse particles.

FIGURE 1: Particle SEM imaging, (a) commercial polydisperse silica particles, and (b) monodisperse particles (Fortis Technologies Ltd).

To accurately quantify particle size and distribution, techniques such as electrical zone sensing or laser diffraction are commonly used. To characterize the particle size distribution generated by either of these techniques, the ratio of D

 may be applied to gauge the degree of size uniformity of the particles. The parameter D90 signifies the point in the size distribution, up to and including, 90% of the total volume of material in the sample is “contained.” For example; if the D90 is 6 μm, this means that 90% of the sample has size of 6 μm or smaller. The definition for D50 is then the size point below, in which 50% of the material is contained. Similarly, the D10 is the size below, in which 10% of the material is contained. This description has long been used in size distribution measurements. As the particle size distribution for chromatographic silica moves towards monodisperse then the D90 and D10 values become closer together and the D

Using a Coulter Multisizer 3 (Beckman Coulter Inc.), an electrical zone sensing instrument, we measured two commercial 3-μm porous silicas and compared against the MFPP. Figure 2 shows the particle distribution of two commercial 3-μm spherical silica samples in comparison with the MFPP. As can be seen, both commercial silicas have a much broader size distribution than the monodisperse material, with one having a slightly smaller mean particle size and the other a slightly larger mean particle size than the 3 μm specified in the manufacturer’s literature.

Figure 2: Particle size distribution measured by Coulter counter. Measuring aperture 50 µm, aperture current 800 µA, measurement diluent is Isoton II. Color Key: Green is commercial 3 µm silica sample A; Blue is commercial 3-µm silica sample B; Red is monodisperse commercial 3-µm silica sample. Resulting numbers are shown in Table I.

 values calculated from the size distribution data can be seen in Table I, where the traditional particles possess D

 values greater than 1.5. In comparison, the new monodisperse particles achieve a D

 of 1.1. To this day, commercial silica columns containing particles with these high D

 values (>1.5) are being successfully used with an acceptable level of column efficiency for the user. Theoretically, we should now expect these monodisperse particles to improve column performance.

Figure 3 shows a graph of the average column efficiencies obtained for twenty 150 x 4.6 mm columns packed with a 5-μm polydisperse C12 (internal Fortis Technologies bonding) with a D

 value of 1.5. An aver- age efficiency of 72,500 plates per meter (p/m) was achieved. A monodisperse 5-μm particle exhibiting a D

 of 1.1 with identical C12 bonding realized an average efficiency of 114,000p/m over 20 packed columns of identical dimension. Therefore, a gain in the region of 57% efficiency because of the difference in the monodispersity of the particles was achieved.

FIGURE 3: Efficiency gains over traditional porous particles. Each bar represents the Average of 20 packed columns of each material. (a) 5 μm traditional porous particles D

 1.1. (b) 3 μm traditional porous particle and 3 μm monodisperse particle. All columns: 150 x 4.6 mm; 60:40 acetonitrile:water, flow rate 1mL/min, wavelength 254 nm. Analytes: uracil, phenol, propiophenone, butyrophenone, napthalene.

When the experiment was repeated with 20 columns of 3-μm particles, the average efficiency for traditional polydisperse 3-μm particles was 98,000 p/m. Monodisperse particles achieved 165,000 p/m on average.

Figure 4 shows a typical chromatogram from each batch of monodisperse and polydisperse columns or packed columns. Using the 3-μm C12 150 x 4.6 mm columns, efficiency is shown to be significantly higher on the monodisperse column, as would be expected. Efficiency is manifested chromatographically as improved resolution and sensitivity.

FIGURE 4: Chromatographic gain in efficiency. (a) 3 μm monodisperse C12, (b) 3 μm polydisperse. Both columns 150 x 4.6 mm, 60:40 acetonitrile:water, temperature: 25 oC, and a wavelength of 254 nm. Analytes: uracil, phenol, propiophenone, butyrophenone, naphthalene, and a wavelength of 254 nm. Axis labels are Time (min) for 

This research will continue to include multiple column diameters (that is, 3 mm and 2.1 mm i.d. columns) to ascertain the contribution from packing and to ensure it is representative across dimensions and is not adversely influenced by increased wall effects or the inherent difficulty in packing narrow bore columns.

So, What Causes This Efficiency Increase Seen in HPLC Columns Packed with Monodisperse Particles? 

Assuming the particles are packed under controlled conditions and testing has been optimized (reduced dwell volume of system to a minimum), there will be three main parameters which contribute to lower reduced plate heights (5) (h

) as defined in the van Deemter equation. The first term, A (Eddy diffusion) is the function of the size and distribution of the interparticle channels or nonuniformities in the packed bed. Secondly, the B term is inversely proportional to linear velocity so describes the molecules diffusion in the axial direction into and out of the pore structure. Finally, the C term which is proportional to linear velocity represents the mass transfer of the molecule from the solvent into the particle stationary phase and back again.

When superficially porous particles (SPP) with narrower particle size distributions came to market (6.7), it was widely assumed that their lower h

 counts were attributed to the narrower PSD, allowing the formation of homogenous packed beds and therefore, a reduced A term, coupled with a smaller impact from the rapid mass transfer of solutes into and out of the reduced porous shell structure. Further studies (8,9) have suggested that longitudinal diffusion into a lower pore volume could be a more significant contributing factor than was initially envisaged. With MFPPs, we should potentially see the same gains from the A term (Eddy diffusion) as SPP particles first imagined. Since both have an almost identical level of monodispersity with D

If pore size, pore structure, pore diameter and mean particle size do not differ between MFPP and traditional porous particles in any significant respect, the flow path around a homogenous well packed column bed will have to be the main contribution to the much-enhanced efficiency seen for MFPP columns. Further study will be required to ascertain the individual contributions.

Effect of Monodispersity on Column Backpressure

By moving to monodisperse high efficiency particles, do we have a positive or detrimental effect on column backpressure?

There is evidence in the literature to suggest that it is difficult to differentiate between the contribution of PSD on the column backpressure as opposed to the impact of column packing process itself. Daneyko (10) suggested column packing was a high contributing factor. Cabooter (11) suggested a small PSD was key. Liekens (12), similar to Dewaele (13), fabricated mixed particle sizes to try and determine the impact of PSD, concluding that while there was no significant drop in h

 when used at optimum linear velocity, at higher elution speeds there was both a drop off in efficiency and also significant increase in backpressure.

Anecdotally, we see in our early evaluations that, although column packing processes impact on the resulting efficiency, there is a clear improvement in column performance when monodisperse particles are compared with polydisperse particles without any discernible increase in backpressure. These new MFPP in various particle sizes will aid in the evaluations since until now narrow PSD was only really available with SPP particles.

In our laboratory, we studied the column backpressure of commercial silicas, each possessing different PSDs (Table I). This was done by packing each silica under identical pressure and flow conditions, to ensure parameters such as sedimentation rates played no part in the ensuing results. Silicas were selected that possessed the same pore volume and pore diameter. From the results shown in Figure 5, we can see that although the mean particle size affects the backpressure, the degree of monodispersity (D

) did not. This would tie in well with the opinions of Dewaele.

FIGURE 5: Impedance of two commercial particles and a monodisperse particle, all marketed as 3 μm in the manufacturer's literature. Size measured by Coulter counter.

Because of the much higher surface area available on the MFPP than the SPP, sample loading can be increased without loss of peak shape, efficiency, and therefore, resolution. Currently, this is where we see limitations in the performance of SPP particles.

The monodisperse particles studied in this article have a surface area of 350 m

/g thereby offering higher retention as well as increased loading capacity. When peak overload occurs, critical separations, such as a parent peak and its impurities, become compromised and the loading capacity is significantly reduced potentially up to a 10-fold difference.

A loading study was performed, for both SPP and MFPP, by steadily increasing the mass of sample that was injected onto the respective column (Figure 6). It can clearly be seen how efficiency drops rapidly as overload quickly occurs on SPP particles. The importance of this issue is significant when considering the development of analytical methods for any new molecular entity (NMEs) that will ultimately require purification once they move to a manufacturing process. The ability to move from a UHPLC sub-2-μm particle in initial method development to a 5-μm or 10-μm FPP in a production environment relies on the ability to have a scalable particle at a non-prohibitive cost that is available in multiple column diameters. Because of the processing costs involved in the manufacture of SPP materials, they are often not commercially available in larger preparative column dimensions, and those that are can be prohibitively expensive. By contrast, these new MFPP materials are produced by conventional manufacturing methods at no more expense than the current commercial silicas. Therefore, they can be supplied in all preparative column formats at a cost affordable to most production sites requiring this type of chromatography.

FIGURE 6: Loading study on (a) monodisperse fully porous particle, and (b) SPP particle. Compound: napthalene at 6 different concentrations. Both columns 150 x 4.6 mm, mobile phase 50:50 acetonitrile:water. Axis labels are Time (min) for 

The primary goal of HPLC is the separation of one or more analytes within a mixture. Focusing on increasing efficiency alone is analogous to overcoming only part of the challenge posed by separation science.

Selectivity is an often-overlooked concept as the majority of analysts will start method development with the selection of a C18 stationary phase running a simple aqueous: organic mobile phase. Although this approach is great for simplicity and with a relatively high percentage success rate, it does not always allow for the separation of complex samples or closely related species. The separation challenges that lie ahead include isomers and molecules with near identical structural properties as well as complex samples from, for example, biological sources. These challenges require the resolving power of stationary phase selectivity.

If we can expand on the traditional stationary phase characteristics by introducing not just alkyl chain hydrophobicity (that is, C18 and C8), but by their halogenated, aromatic, or polar character, then these secondary mechanisms will promote greater analyte-stationary phase engagement. Figure 7 shows the separation of a diverse mixture of compounds on two, predominantly C18 alkyl chain phases, however one has aromatic secondary character and one has pentafluorophenyl (PFP) secondary character. It can be clearly seen that in some areas of the chromatogram the phases appear to be quite similar in selectivity, whereas with some of the components there are large shifts in resolution between analyte pairs. This is the type of movement that can then be tuned for the NME and its impurities in initial method development screening.

FIGURE 7: Selectivity on a (a) monodisperse C18/AR, and (b) a monodisperse C18/PFP. All columns are 3 μm 100 x 2.1 mm. Mobile phase A: 10 mM ammonium formate pH 3.0, B: 10 mM ammonium formate 3.0 in a cetonitrile. Flow rate is 0.4 mL/min., wavelength is 254 nm, temperature is 40 

C. Compounds are: 1. hydroquinone, 2. theobromine, 3. paracetamol, 4. theophylline, 5. paraxanthine, 6. 4-hydroxybenzoic acid, 7. 2-acetamideophenol, 8. caffeine, 9. phenol, 10. aspirin, 11. 2-hydroxybenzoic acid, 12. 4-nitrophenol, 13. 4-chloracetanilide, 14. 2-nitrophenol. Axis labels are Time (min) for 

Further surface modifications produced by manufacturers to offer enhanced selectivity are far too numerous for the scope of this article and have been characterized in multiple ways, such as the Tanaka (14) protocol, Engelhardt (15) test or the Synder, Dolan (16) hydrophobic-subtraction model. The reader should take some time to review as much of this work as possible as it offers a good insight into the diversity available in stationary phase design over the years along with many good examples of application development to solve challenging separations.

The more selectivity that can be imparted from the stationary phase the less demand there is to manipulate the mobile phase, temperature or pH range. Changes in the organic mobile phase component seem to have become somewhat limited in RP chromatography because of miscibility, safety, cost, and environmental impact of solvents. Fully porous monodisperse particles available with a wide range of orthogonal stationary phases will therefore allow the separation scientist to optimize selectivity and speed of analysis without the need for exhaustive method development or pushing the extremes of pH, additives or solvent mixtures.

This simplification leads to more robust, reproducible methods which is a productivity gain within our development process.

There have been many developments in particle technology over the years aimed to improve performance, resulting in chromatography with increased speed, efficiency, and sensitivity. However, these changes always appeared to provide a benefit at the expense of another parameter, whether that be the high backpressure trade-off for the efficiency gain in UHPLC, or the limited sample loading and cost tradeoff made for the efficiency gain seen with SPP particles. With the development of a monodisperse fully porous particle (MFPP) there is now a commercially available silica support that brings performance benefits without associated drawbacks.

MFPP particles have now been optimized to a degree where commercialization has now been achieved. Improving the particle morphology has led to gains in efficiency over existing porous particles in the region of 50–60%, giving greater sensitivity and resolution. These gains are attributed to the reduced A-term as a result of the better flow path through the interstitial spaces in the packed column bed.

Our studies show when comparing equivalent 3-μm monodisperse packed beds and polydisperse packed beds we see no discernible backpressure differences that could be attributed to the improved monodispersity. By increasing monodispersity we have in effect simultaneously eliminated both small and large particles, and their respective contribution to increasing and decreasing back pressure is therefore canceled out. Hence, we see no net increase in backpressure.

By maintaining a fully porous structure in these monodisperse particles we show the high surface area leads to high sample loading capacity. Our loading studies showed a >4-fold increase in capacity on a simple pharmaceutical molecule when comparing to a high efficiency core-shell particle.

We acknowledge how even with the enhanced efficiency of a monodisperse particle, a choice of orthogonal stationary phases is critical to the more complex samples faced in the current pharmaceutical and biomolecule workflow. This topic will be covered in further articles.

Further study of these monodisperse particles will revolve around additional comparison with SPP, trying to understand all of the contributions leading to the source of the efficiency gains. Assuming the A-term, particle size and packing density are similar with both, what is the difference between C-terms? Also, can you compartmentalize the column packing process impact from the particle architecture contributions?

In summary, MFPP offers high efficiency, high surface area with homogenous well packed column beds for analytical through to preparative scale chromatography. Method development and method transfer can move seamlessly from initial UHPLC through to preparative scale production environment. In particular, 3-μm MFPP particles have been shown to offer gains in efficiency similar to UHPLC particles without a trade off in increased backpressure or loading capacity.

(1) Stober, W.; Fink, A.; Bohn, E. Controlled Growth of Monodisperse Silica Spheres in the Micron Size Range. 

 62–69. DOI: 10.1016/0021-9797(68)90272-5

(2) Buchel, G.; Gruin, M.; Unger, K.; Matsumoto, A.; Kazuo, T. Tailored Syntheses of Nanostructured Silicas: Control of Particle Morphology, Particle Size and Pore Size. 

 253–259. DOI: 10.1016/S0968-5677(98)00016-9

(3) Gritti, F.; Guiochon, G. The Quantitative Impact of the Mesopore Size on the Mass Transfer Mechanism of the New 1.9μm Fully Porous Titan-C18 Particles. I: Analysis of Small Molecules. 

76–87. DOI: 10.1016/j.chroma.2015.01.047

(4) Gritti, F.; Bell, D.; Guiochon, G. Particle Size Distribution and Column Efficiency. An Ongoing Debate Revived with 1.9 μm Titan-C18 Particles. 

 179–192. DOI: 10.1016/j.chroma.2014.06.029

(5) van Deemter, J. J.; Zuiderweg, F.; Klinkenberg, A. Longitudinal Diffusion and Resistance to Mass Transfer as Causes of Nonideality in Chromatography. 

(6) Kirkland, J.; Langlois, T.; DeStefano, J. Fused Core Particles for HPLC Columns. 

https://www.americanlaboratory.com/913-Technical-Articles/1304-Fused-Core-Particles-for-HPLC-Columns/

(7) DeStefano, J.; Langlois, T.; Kirkland, J. Characteristics of Superficially-Porous Silica Particles for Fast HPLC: Some Performance Comparisons with Sub-2-µm Particles. 

46, 254–260. DOI: 10.1093/chromsci/46.3.254

(8) Guiochon, G.; Gritti, F. Shell Particles, Trials, Tribulations and Triumphs. 

1915–1938. DOI: 10.1016/j.chroma.2011.01.080

(9) Hayes, R.; Ahmed, A.; Edge, T.; Zhang, H. Core–Shell Particles: Preparation, Fundamentals and Applications in High Performance Liquid Chromatography. 

 36–52. DOI: 10.1016/j.chroma.2014.05.010

(10) Danyenko, A.; Holtzel, A.; Khirevich, S.; Tallarek, U. Influence of the Particle Size Distribution on Hydraulic Permeability and Eddy Dispersion in Bulk Packings. 

(11) Cabooter, D.; Fanigliulo, A.; Bellazzi, G.; Allieri, B.; Rottigni, A.; Desmet, G. Relationship Between the Particle Size Distribution of Commercial Fully Porous and Superficially Porous High-Performance Liquid Chromatography Column Packings and their Chromatographic Performance. 

, 7074–7081. DOI: 10.1016/j.chroma.2010.09.008

(12) Liekens, A.; Bilen, J.; Sherant, R.; Ritchie, H.; Deneyar, J.; Desmet, G. High Performance Liquid Chromatography Column Packings with Deliberately Broadened Particle Size Distribution: Relation Between Column Performance and Packing Structure. 

, 6654–6662. DOI: 10.1016/j.chroma.2011.07.055

(13) Dewaele, C.; Verzele, M. Influence of the Particle Size Distribution of the Packing Material in Reversed-Phase High-Performance Liquid Chromatography. 

13–21. DOI: 10.1016/0021-9673(83)80002-8

(14) Kimata, K.; Iwaguchi, K.; Onishi, S.; Jinno, K.; Eksteen, R.; Hosoya, K.; Araki, M.; Tanaka, N. Chromatographic Characterization of Silica C18 Packing Materials. Correlation Between a Preparation Method and Retention Behavior of Stationary Phase. 

 721–728. DOI: 10.1093/chromsci/27.12.721

(15) Engelhardt, H.; Jungheim, M. Comparison and Characterization of Reversed Phases. 

(16) Synder, L.; Dolan, J.; Carr, P. The Hydrophobic-Subtraction Model of Reversed-Phase Column Selectivity. 

77–116. DOI: 10.1016/j.chroma.2004.08.121

 is co-founder and Research Director of Fortis Technologies Ltd and has master degrees in Chemical Technology and Business from Bradford and Strathclyde Universities. Over the past 25 years, he has worked directly in the chromatography industry, specifically on the manufacture of silica particles and the design and commercialization of stationary phases for HPLC. With a proven track record of successful product development, he has presented his research and development data at symposia worldwide. His continued focus remains on the improvement of particle and phase chemistry performance in order to provide the analytical chemist with the best tools for achieving their desired chromatographic separations.

 co-founded Fortis Technologies Ltd in 2005, having spent 10 years developing stationary phases for what used to be the Hypersil brand. Mark worked as the Technical manager and the Global Product Manager for HPLC columns at Thermo Hypersil. Mark has a BSc and Masters in Analytical Chemistry as well as an MBA from Manchester University (UK). Mark is currently involved in the development and marketing of new columns from Fortis Technologies and has an excellent relationship with many key people in major pharmaceutical companies in order to ensure that the needs of the industry are met.

We explore advancements in silica particles for liquid chromatography, focusing on the shift toward improved monodispersity and its impact on chromatographic parameters, efficiency, backpressure, and sensitivity in high-performance liquid chromatography (HPLC).

The Effect of Particle Monodispersity in HPLC Column Performance

Nearly all gas chromatographic analyses are preceded by sample preparation, which is often the major determiner of success. Recently, 

 surveyed its readers about their work in sample preparation, covering the overall state of the field, and the results were presented in the “Sample Prep Perspectives” column. In this installment, we discuss the impact of part 1 of this survey, which covers broad questions about who does sample preparation, the fields they work in, and their most important aspects and goals for sample preparation on the gas chromatographic analysis that follows. We see that sample preparation has been (and remains) a critical step in any gas chromatographic method. In a second installment, we will discuss the impact of specific sample preparation techniques and their management on gas chromatography, following the release of part 2 of the sample preparation survey.

 is the Founding Endowed Professor in the Department of Chemistry and Biochemistry at Seton Hall University, and an Adjuncy Professor of Medical Science. During his 30 years as a chromatographer, he has published more than 70 refereed articles and book chapters and has given more than 200 presentations and short courses. He is interested in the fundamentals and applications of separation science, especially gas chromatography, sampling, and sample preparation for chemical analysis. His research group is very active, with ongoing projects using GC, GC-MS, two-dimensional GC, and extraction methods including headspace, liquid-liquid extraction, and solid-phase microextraction. Direct correspondence to: 

Sample preparation and sample injection are often the most challenging steps in a full gas chromatographic method. Gas chromatography (GC) is generally amenable to liquid and vapor phase samples, and in most applications, the sample must be in the vapor phase as it enters the column. This can be seen in the most common injection techniques, split and splitless, in which a liquid sample is injected using a syringe into an inlet where it is vaporized. Sample preparation for GC can be online, with direct interfacing, usually through a transfer line, between a separate sample preparation technique, such as static headspace extraction, or offline, with samples prepared separately, aliquoted into vials, usually as solutions, and injected as liquid samples.

Table I provides a summary of some sample preparation techniques commonly used with GC for solid, liquid, and vapor samples. Typically, for solid samples, the solid is dissolved or otherwise treated, followed by one of the techniques for liquid samples. Commonly, solid samples are dissolved in a solvent, but they can also be extracted using a number of instrumental techniques, including headspace extraction, accelerated solvent extraction, and microwave assisted extraction. Liquid and vapor samples can be injected “neat,” but usually require sample preparation to remove nonvolatile or reactive sample components.

Sample types amenable to common sample preparation techniques for GC (S = solid, L= liquid, G = gas).

 surveys reported in 1991 (1) and 2023 (2), we see that sampling and sample preparation occupied over 50% of analyst time in a typical analysis, so the importance of sample preparation cannot be overlooked. In both surveys, analysts were also asked about the most important error sources in their methods, with the sample preparation-related responses of sample processing, operator and contamination combining for just over 50% of the responses in 1991 and about 37% in 2023. In 2023, calibration was stated as the largest single contributor to error, while in 1991, it was sample processing. This change was attributed to the rise in automation over the past 30 years. Interestingly, the major sources of error in most gas chromatographic methods are likely outside of the instrument, either in sample preparation and handling (which happens prior to the chromatographic analysis), or data analysis (which happens following chromatography).

Subtleties Fundamental to All Sample Preparation Techniques

From Table I, we see that nearly all sample preparation techniques used with GC involve a phase transition and phase equilibrium, just as GC depends on the theory of equilibrium between the mobile (vapor) and stationary (usually liquid or solution) phases. A brief review of phase equilibrium applied to GC and sample preparation will show principles common to all sample preparation techniques. The chemical equation and equilibrium constant expression for a phase transition, shown in equation 1, are among the simplest that describe a chemical process, but there are many subtleties.

The first subtlety is the consequences of the value of the equilibrium constant. This determines how much of the analyte can be transferred from one phase to the other in a single extraction step. In GC, a single extraction step is analogous to a single theoretical plate, as we saw last year in our discussion of the classical Golay equation (3,4). Figure 1 shows a comparison of several common extraction methods, including solid-phase microextraction (SPME), liquid-liquid extraction (LLE), and low-volume LLE. The mole ratio of a hypothetical analyte extracted from an aqueous phase into an organic phase is plotted against log

 is large, indicating that the analyte is much more soluble in the organic phase than the aqueous phase (as is commonly seen in gas chromatographic methods, when extracting organic compounds from water or other aqueous systems into an organic phase), then a nearly complete, or quantitative, transfer of the analyte from the aqueous phase to the organic phase is possible.

Comparison of some extraction methods. MLLE–liquid-liquid extraction with both phases of low volume; SPME–solid-phase microextraction; High–large volume of aqueous phase extracted with a small volume of organic phase; Low–like MLLE but using a smaller volume of organic phase and a large volume of aqueous phase.

The second subtlety, also seen in Figure 1, is seen in the relative volumes of the sample (in this case aqueous) phase and the extract (organic) phase. The micro-liquid-liquid extraction (MLLE) case is a low, but roughly equal, volume of both phases, volumes that would fit into a single autosampler vial; the high case is a large volume of aqueous phase extracted with a small volume of organic phase, while the low case is like MLLE, but using a smaller volume of organic phase and a large volume of aqueous phase. Finally, SPME represents an extreme volume difference with the very low-volume coated fiber immersed in a large volume of aqueous sample.

The third subtlety is that while equilibrium constants may be very large or very small, they are finite. This means that in any extraction system, even with a very large constant, some amount of the analyte will remain in the original phase. This challenge opens an additional idea that has not been explored much in the literature. If the equilibrium constant is small, multiple extractions form the same sample, using a fresh extraction phase, can result in appreciable extraction of the analyte when the separate aliquots of the extraction phase are combined.

A fourth subtlety is that for any chemical reaction or process, especially extraction, reaching equilibrium takes time. Even in the simplest of systems, a “dilute and shoot” procedure, the diluted liquid must be mixed. When diluting one liquid by another, how does the analyst know that the two liquids have fully mixed into a homogeneous mixture? Mostly, we count on indirect evidence based on our judgment of the time and vigorousness of mixing, appearance of the solution, and reproducibility of the data. The same questions apply to simply dissolving solids. Mostly, we determine that the solid has dissolved when we no longer see particles, and we also know that no solid dissolves instantly. In short, when diluting or making solutions, allow sufficient time for complete mixing.

We see, from the simplest of techniques, that all sample preparation methods require time to come to equilibrium. This amount of time may be on the same order of or longer than the time required for the chromatographic separation. Our fifth subtlety in all sample preparation techniques is kinetics. While equilibrium determines how much analyte we can transfer between phases, kinetics determines how long it takes. Due to the variety and complexity of most samples, the kinetics of extraction must be determined experimentally and may vary widely for seemingly similar samples.

Fortunately, coming back to the simplicity of equation 1, most extraction techniques follow or approximate first order kinetics. In the simplest case, we have individual particles partitioning between two phases. Extraction kinetics may be complicated by additional matrix components in the sample phase that bind or adsorb the analytes of interest. In any method development involving extraction, the kinetics of extraction should be carefully studied. A kinetic plot for a simple and fun extraction is shown in Figure 2. This is the extraction of fats from a chocolate bar using supercritical fluid extraction (5). In this case, time is measured by the volume of supercritical carbon dioxide delivered at constant flow. This is a quantitative extraction example, but it shows the key elements of extraction kinetics.

For the best reproducibility and maximum recovery, extraction should be allowed to proceed for long enough so that the amount extracted is expressed on the flat, nearly horizontal part of the curve. Small variations in the extraction time or conditions will have the least effect on this portion of the curve. Shorter extraction times, where the curve is steeper, can be used with calibration, but at the risk of larger uncertainty and impact of minor variations in the extraction conditions.

A recent sample preparation survey explored the critical role of sample preparation in gas chromatographic analysis.