Although symmetric peaks with Gaussian shapes are predicted by models of the chromatographic process, “perfect peaks” are not observed very often outside of textbooks. Several physical phenomena can lead to asymmetric peak shapes, including heterogeneity of the particle density inside the column, rearrangement of the particles over time, and accumulation of debris at the column inlet frit. Understanding these phenomena can help identify whether the cause of asymmetry is most likely to have a physical or chemical origin, which, in turn, dictates which troubleshooting steps to start with when dealing with poor peak shapes.

Last month, in the first installment of this series of LC “Troubleshooting” articles on peak asymmetry, I discussed some basic concepts in peak asymmetry, including commonly used models of chromatographic peak shapes, how to quantify peak tailing, and the impact of peak tailing on separation performance. I then went on to discuss in some detail how poorly-made connections between the column and the rest of the LC system can lead to serious peak tailing. The good news is that this particular cause of peak tailing can usually be fixed rather easily by carefully considering the parts (such as capillaries and unions, to name two) used in the flow path between the injector and detector, and replacing those that are inappropriately sized (for example, a union with a very large through-hole) or somehow improperly connected (for example, a ferrule set too shallow). In addition to these problems, there are many other potential causes of peak asymmetry—too many to cover in a single one of these articles—some having primarily physical origins, and some having primarily chemical origins. In this month’s installment, I will focus on several other potential physical causes, including problems with column packing, changes in the packed particle bed over time, and accumulation of debris in the column. A common symptom of all of the physical causes of peak asymmetry discussed here is that all peaks in a chromatogram will be affected similarly. This can be an important clue to help determine if the source of the asymmetry is more likely to have chemical or physical origins. If all of the peaks in a chromatogram are either fronting, or tailing (or both [1]), the cause is most likely physical in origin. If only some of the peaks are fronting or tail- ing, but the other peaks look good, then it is most likely that the cause of the poor peak shape is chemical in nature. This distinction is helpful when deciding which potential solutions to improve the peak shape to try first.

Brief Review of Flow Through a Packed Bed of Particles

To understand the different peak shapes that can be observed as a result of different physical problems within a LC column, it is helpful to first review some foundational concepts related to mobile phase flow through a column packed with small particles like those used in HPLC. Figure 1a shows a highly idealized illustration of the organization of particles (depicted as porous spheres) in a perfectly packed bed. Such perfect arrangements of particles are not achievable in practice, though some come close, in the case of small very small (<1 μm) particle columns (2). The main point of this illustration is that a highly ordered, consistent arrangement of the particles in the column leads to highly consistent mobile phase velocities across the column radius. Since the rate of migration of analyte molecules (that is, analyte velocity) from the inlet to the outlet of the column is proportional to the mobile phase velocity, the consistency in mobile phase velocity directly translates into consistent analyte velocities, and thus a symmetric analyte peak observed at the detector. In the case of perfectly consistent mobile phase velocity across the column diameter, there would be no “A-term broadening” of peaks, and their widths would be dictated primarily by diffusion of analytes along the long axis of the column, and into and out of pores in the particles. The consistency of the mobile phase velocity in this case is communicated in Figure 1a with yellow arrows of the same size. Analyte molecules are illustrated as green dots, and the resulting chromatographic peak observed at the detector is shown at the right of the column.

FIGURE 1: Illustration of porous particles arranged in LC columns in different ways. Drawings are not to scale, are highly idealized, and with features that are exaggerated to illustrate specific concepts. Porous particles are depicted in textured circles, mobile phase velocities at different positions in the cross-section of the column are indicated with yellow arrows, analyte molecules are depicted as green dots, and the peak at the right in each case illustrates the type of peak shape that can result from the particle arrangement shown at left. (a) Perfectly ordered arrangement of particles that leads to consistent mobile phase velocities and symmetric peak shapes; (b) Random arrangement of particles—local variations in the tightness of the packing lead to variations mobile phase velocity, which in turn lead to asymmetric peaks; this particular shape is referred to as a “fronting peak”; (c) Empty void space at the column inlet due to consolidation of the particle bed can lead to mobile phase mixing (orange arrows) and tailing peaks; (d) Accumulation of insoluble debris from the mobile phase at the inlet frit can lead to differences in the velocity of mobile phase passing through the frit, and thus asymmetric or even split peaks.

Variations in Particle Packing Tightness Throughout the Column Can Lead to Asymmetric Peaks

In contrast to the highly ordered bed structure illustrated in Figure 1a, Figure 1b shows that, in real columns, the structure of the particle bed is rather disordered, leading to regions where the particle density (that is, the number of particles per volume of column, not the density of the particles themselves) is much higher than others. In recent years, several studies discussed in the literature have made clear that much of this heterogeneity in packing density throughout the column arises as a result of friction between the column wall and the particles as they are pushed into the tube. This results in large variations in density near the wall, moving from the wall toward the center of the tube. This is sometimes referred to as a wall effect on the packing density. The net effect of this variation, though, is that the mobile phase velocity will be lower in regions of high density, and higher in regions of low density, because there is less friction opposing the flow of mobile phase as the spaces between adjacent particles increase. This variation in mobile phase velocity then manifests as an “A-term type of peak broadening,” and results in peaks that are broader compared to the situation where there is no variation in mobile phase velocity across the radius of the column. In the particular situation shown in Figure 1b, the packing density near the wall is significantly lower compared to the center of the column. If the difference in densities is large enough, this can actually result in peak asymmetry like that shown in this case, which we refer to as peak fronting. We typically do not observe this behavior much in commercial LC columns, because the manufacturers do a good job of mitigating this particular problem, but I’ve packed enough columns during my days working in the column business to know that this effect can be very serious, and must be solved through optimization of column packing procedures. During the development of new stationary phases and column technologies, column manufacturers study the impact of a large number of variables on the packing quality, including things like the slurry solvent (that is, the solvent used to suspend the particles to flow them into the column), slurry concentration (particles per volume of solvent), packing flow rate, and packing pressure. Readers interested in learning more about the column packing process and the topic of heterogeneity of the particle bed are referred to recent articles on the topic (3).

Development of Particle-Free Void Spaces in the Column Leads to Peak Tailing

When packed particle LC columns are manufactured, the slurry containing the particles is pushed into the tube at very high pressures, typically exceeding 10,000 psi for modern materials. In principle, these high pressures force the particles into an arrangement that is unlikely to change significantly when used in an LC instrument at lower pressures. In the early days of HPLC it was not uncommon for column performance to deteriorate upon settling or rearrangement of the particle bed. Fortunately, modern manufacturing procedures have generally improved the robustness of LC columns significantly, and I have to say I am often impressed at just how resilient modern columns are, surviving instrument failures (for example, pressure spiking due to sticky check valves) or user error (for example, allowing columns to dry out without flushing first with an organic/water mixture to remove buffer salts). However, rearrangement of the particle bed can still happen—for example, in response to physical stress on the column (such as repeated pressure fluctuations [4]). Although there are many ways that the particle bed could conceivably rearrange, the classical observation is that the particle bed consolidates in the direction of the outlet (think of sand settling in a bucket when vibrated), leaving a significant “void” at the column inlet where there are no particles and only mobile phase. These void spaces can then act like small mixing chambers and lead to significant peak tailing like that shown in Figure 1c. Sometimes reversing the flow direction can restore some of the column performance, but, in my experience, this performance is usually very short-lived, and when a void develops in a column it is best to just replace the column. Although many modern LC columns are highly resilient to various physical stressors, it is still helpful in the long run to avoid causes of such stress in order increase column lifetime. This includes avoiding major pressure fluctuations (for example, due to air bubbles in pumps), and properly flushing columns according to manufacturer recommendations before storing the column for more than a few days.

Accumulation of Debris on Column Frits Can Lead to Asymmetric Peaks

As I’ve written about in the past, one of my favorite troubleshooting tips is to consistently use inline filters in LC systems, especially immediately upstream from the column (5). There are many ways that insoluble debris can make its way to the column inlet, including particulate matter in the sample that is injected, particulate matter in the mobile phase that comes from unfiltered solvent feeding the pump, and polymeric material that is shed by valves (for example, from a rotor seal) like those found in autosamplers. If an inline filter is not used between the sample injector and the column, then much of this insoluble debris will accumulate on the inlet frit of the LC column. I’ve looked at many inline filters when replacing them after they’ve become blocked, and, without exception, I see that debris never accumulates across the frit in a uniform way. Sometimes it is concentrated at the edges, sometimes in the middle, and other times there is no obvious pattern. However, the non- uniform distribution of the accumulated material again means that flow through the column inlet frit will also be nonuniform, leading to different mobile phase velocity streams at the column inlet, peak dispersion, and asymmetric peak shapes. In the illustration in Figure 1d, I’ve attempted to show accumulation of debris at the center of the inlet frit, and that in some cases this can lead to severely distorted split peaks as shown at right. The good news is that this particular cause of peak asymmetry can largely be avoided through consistent use of inline mobile phase filters directly upstream from the analytical column. It is also possible in many cases to physically replace the inlet frit on the LC column, but this requires extraordinary care to avoid disrupting the particle bed, and I would not recommend this remedy as a routine practice.

In this installment of “LC Trouble- shooting,” I’ve discussed several of the common physical causes of peak asymmetry in LC, and remedies for some of them. In some cases there is not a whole lot the user can do to address the root cause of peak asymmetry, as some problems occur at the point of manufacture of the column, but in the spirit of increasing our troubleshooting knowledge, it is still helpful to know what all can go wrong, and this knowledge can also help determine if the problem is likely to be solvable, or if the column must simply be replaced. In the next installment in this series, I will discuss several chemical causes of peak asymmetry, where we as users typically have more opportunities to improve peak shape through changes in operating conditions.

(1) M.F. Wahab, D.W. Armstrong, and D.C. Patel, 

(2) B.A. Rogers, Z. Wu, B. Wei, X. Zhang, X. Cao, O. Alabi, and M.J. Wirth, 

, 2520–2526 (2015). https://doi.org/10.1021/ac504683d.

(4) E.S. Talus, K.E. Witt, and D.R. Stoll, 

, 50–57. (2015). https://doi.org/10.1016/j.chroma.2014.12.019.

 is the editor of “LC Troubleshooting.” Stoll is a professor 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: 

Articles

In a continuing series on peak shapes, we focus on potential physical causes of asymmetry, including column packing, changes in the packed particle bed, and accumulation of debris in the column.

But My Peaks Are Not Gaussian! Part II: Physical Causes of Peak Asymmetry

On June 27, 2021, Harold Monroe McNair passed away peacefully in his home, surrounded by his family. Harold’s career as a chromatographer spanned over 60 years, from his 1959 authoring of the first gas chromatography (GC) doctoral thesis in the United States on stationary phase chemistry to the first edition of his classic book, 

, in 1964, to a 2019 journal article on the diet of post-weaning heifers (cows). McNair’s remarkable career and writings spanned the entire breadth of chromatography and separation science. Using McNair’s early writings and works as a guide, I explore three fundamental areas of understanding in GC, seeing ideas about problems that still challenge gas chromatographers today. With McNair, we explore stationary phase chemistry, computers in chromatography, and liquid chromatography (LC) compared to GC.

Harold McNair had a remarkable 60-year career as a chromatographer, and his writings spanned the entire breadth of chromatography and separation science. By looking back at some of his key early writings, we have an opportunity to explore three key areas in gas chromatography (GC), which are still relevant today: stationary-phase chemistry, chromatography and computers, and liquid chromatography (LC) versus GC.

Harold McNair’s doctoral dissertation, presented to the faculty of Purdue University in 1959, entitled “Efficiency of Solvents in Gas Chromatography,” was the first doctoral thesis on GC in the United States (1). The original thesis is freely available by open access through the university and ProQuest. The thesis title alone offers interesting historical insight because the thesis was written prior to the definition of many of the currently used terms in chromatography (2). When we think of efficiency today, we mostly discuss peak widths and theoretical plates. In 1959, McNair was discussing retentiveness and selectivity. When we think of solvents today, we would likely think of sample preparation or dilution solvents; McNair was discussing the stationary phase. Translated to the terminology of today, this title might read something like: “Retentiveness of stationary phases in gas chromatography.” McNair performed the first systematic study of retention and polarity of stationary phases in GC, which is a topic that we are still debating and discussing today.

McNair’s thesis also provides insight into how gas chromatographs were constructed back in the 1950s before commercial instruments were available. Figure 1 shows a schematic of McNair’s home-built GC instrument. A complete description of the construction can be found in the thesis. A few construction details about this instrument provide lessons about gas chromatographs and columns that are still relevant today. McNair describes making and packing the columns using 6–10 ft lengths of copper tubing, which can easily be coiled, handled, and fitted into the instrument. Although stainless steel and glass columns would be more inert, McNair was thinking practically about ease-of-use. Today’s fused-silica capillary columns are designed with ease-of-use in mind as well. Other materials might be more inert and more temperature stable, but fused silica columns are easy to use.

FIGURE 1: Schematic diagram of McNair’s original laboratory-built gas chromatograph. Adapted and updated from reference (1).

McNair’s GC instrument did not have a column oven as we have come to know them. Traditional ovens of the day at a reasonable cost would not likely have provided precise enough temperature control for systematic and reproducible studies of retention. In McNair’s gas chromatograph, the column and detector were placed in a vapor jacket that contained the vapor of a refluxing solvent at constant temperature. Using acetone, water, and anisole provided stable constant temperatures at 55 °C, 100 °C, and 153 °C, respectively. Although this arrangement provided stable temperatures, it was obviously difficult to change temperature. Temperature programming, a new concept at the time, was out of the question.

McNair recognized the need for strong analyte retention in studies of stationary phase properties, so he prepared packed columns using 30% by weight of each stationary phase with the other 70% being the solid support particles. He commented that this was a higher than usual loading of the stationary liquid phase onto the solid particles, to ensure greater retention of the analytes through having a higher mass of stationary phase in the column. Today, the equivalent thinking is to use a thicker film capillary column to increase retention.

Finally, McNair provides a summary of classical early works on chromatography, some from before the beginnings we think of today. He notes an original work describing gas–solid chromatography but not described as chromatography, as it predates Tswett’s coining of the term chromatography by several years (3,4). In 2010, McNair provided an excellent summary of the history of GC for 

, was first published in 1964 and became the standard by which all other books intended for new users to learn analytical instruments is measured (6). Figure 2 is a photograph of my own well-worn copy that I purchased upon joining his research group in the 1980s. Of course, this book was required reading in his courses and at the time it still contained much timely information. Today, the original versions with the instantly recognized classical green cover seem dated but the concise descriptions of stationary phases, detectors, and troubleshooting are still relevant. Over the decades, the original 

 sold more than 130,000 copies and was published in eight languages. The original paperback is out of print, but second-hand copies are often available through online booksellers. The most recent edition, published by John Wiley and Sons, with me and Professor James Miller as co-authors, was published in 2019.

FIGURE 2: Image of the original green cover of the book entitled 

The more modern discussion of stationary phase chemistry and polarity presented in the later editions 

 demonstrate the continuing timeliness and relevance of this discussion, which began with McNair’s thesis and was re-energized with the development of ionic liquid–based stationary phases in the 2000s (7). When these highly polar stationary phases were being developed, it was quickly discovered that the chemical names of the compounds used to make them were far too complex for marketing purposes, or even for most chemists to remember. In 2011, to simplify the discussion of the polarity of these new stationary phases, Mondello seized on an idea presented in 

 that an overall stationary phase polarity value could be generated using the sum of the McReynolds constants for that phase (8). Mondello’s polarity numbers, calculated from the sum of McReynolds constants, are now widely used to express the overall polarity of stationary phases (9).

Since its start in 1965 and written in a style that does not require the reader to be a highly experienced chemist, 

 has been the “go-to” first book on GC for analysts all over the world.

McNair’s publications also provide insight into major developments in chromatography over the years. Although he is best known as a pioneer in GC, McNair’s publication list includes many important works in high performance liquid chromatography (HPLC), supercritical fluid extraction (SFE), supercritical fluid chromatography (SFC), capillary electrophoresis (CE), mass spectrometry (MS), and many more techniques. Perhaps the most important lesson from McNair’s publication list is to not just focus on a single technique, but think about solving problems. Thinking about or learning one technique is too limiting for the complex scientific problems of today.

In 1972, McNair hosted the first International Symposium on Computer Chromatography and Associated Techniques in Mainz, Germany. His editorial introducing the symposium, which was captured in a special issue of 

, included several comments about data systems and chromatographic data analysis that remain relevant today (10). McNair asked the following two questions: “What are we doing with computers?” and “What should we be doing with computers?” The symposium volume provides an excellent set of answers to the first question, which included developing interfaces for single and multiple instruments, acquiring the data, and processing the data. McNair commented that the introduction of computers to chromatography caused chemists to complain about the large amounts of data generated each morning. This complaint rings true today in the fast GC and comprehensive two-dimensional gas chromatography (GCxGC) communities, which often deal with large data sets. A few of the article titles from this 1972 symposium, including Kaiser’s “PPB-Analysis Computerized?” and Battista’s “Computerized Blood Alcohol Analysis” demonstrate the intense interest in quantitative analysis. Several other articles on data analysis and evaluation include diagrams showing integration schemes for overlapping and asymmetrical peaks that look very similar to those used to describe these processes in today’s modern data systems.

McNair emphasized the need to use computers for qualitative analysis, mentioning the early work of Schomburg and Ziegler on the use of Kovats retention indexes to identify analytes. These early ideas led to the development of retention index libraries that are still in common use today. I was fortunate to work with McNair and Sadtler Research Laboratories in the 1980s on the development of their retention index library into a “poor man’s gas chromatography–mass spectrometry (GC–MS)” concept, whereby retention indexes measured on two significantly different stationary phases could be compared to libraries to generate an accurate qualitative analysis. With the rise of benchtop GC–MS and GCxGC–MS instruments, tools for qualitative analysis have been included in many of today’s data systems. McNair’s comments about qualitative analysis and large data sets still resonate in the GCxGC community, where both are the norm, and the chromatograms themselves are increasingly complex.

In 1974, McNair posed a question that is still commonly asked today in some form: “How soon will liquid chromatography replace gas chromatography?” (11). He then comments that asking the question at all may demonstrate a general lack of understanding about the two techniques. Difficulties in fundamental understanding exist today. In a comprehensive edited volume on GC published this year, Poole devotes a short section and commentary to this challenge (12). Interestingly, having published exclusively on GC until then, McNair built an extensive publication record on HPLC and other techniques, including GC. When I was in his group, there were two active laboratories in the group: the “LC group” and the “GC group.” The LC and GC laboratories were even in separate buildings for a time. McNair kept us all working together: LC group members worked with and challenged GC group members and vice versa He made sure we were all cross-trained and that we all fundamentally understood separation science, not just individual techniques, and problem solving. The answer to the question of LC replacing GC was never fully decided, and McNair’s response is as true today as it was back in 1974. McNair’s concise two-page comparison of LC and GC, including thoughts on the separation principle, sample types, minimum detectable quantities, analysis time, theoretical plates, preparative capability, and price range, is as useful today as it was back then. Viewing LC and GC as complementary highlights an important principle of analytical chemistry—that the problem should be considered before the technique, and the technique should be designed to solve the problem, not the other way around. Viewing LC, GC, and other analytical methods as competitive to one another only limits the work and experience to a single technique, which is an elementary mistake new analytical scientists can make.

In 1984, Bowermaster and McNair demonstrated the fundamental complementary nature of LC and GC, describing temperature programming in HPLC (13). In both GC and LC, partitioning between the mobile and stationary phases is an equilibrium- controlled process so both techniques are subject to similar phase thermodynamic principles that govern retention. As a simple analogy, mobile-phase strength in LC is like temperature in GC. However, in LC, temperature can also be used as an additional variable to control retention. Temperature-programmed versus isothermal LC runs showed very similar behavior to temperature-programmed runs in GC, with the temperature-programmed runs showing roughly equal spacing of the peaks versus the exponential spacing seen in isothermal runs. Although temperature-programmed HPLC has not caught on very much, precise temperature control, obviously necessary in GC, which Bowermaster and McNair also discussed in detail, has been incorporated into nearly all of today’s commercial HPLC systems.

These brief vignettes provide a small taste of Professor Harold McNair’s massive contributions to separation science. His publication record alone does not capture the whole story of a career and life devoted not only to the science but to people all over the world. There are few separation scientists of my own and previous generations that did not meet or interact with McNair at a conference, a short course, or in the laboratory. He was quick to invite visitors from all over the world to visit his laboratory in Blacksburg, Virginia to share knowledge, experience, and good times. He was a world traveler who routinely visited the laboratories of colleagues all over the globe. We had a globe of the earth in our laboratory with a small arrow attached, pointing to wherever in the world “Doc” was, often not Blacksburg. Whether through publication, working in the laboratory together with other scientists, or from conversations, Harold McNair freely shared his knowledge and experience. His work and spirit influenced separation science far beyond GC and he is easily considered among the most influential analytical scientists of the past 60 years.

(1) H.M. McNair, “Efficiency of Solvents in Gas Chromatography” PhD Dissertation, Purdue University, 1959. Retrieved from https://www.proquest.com/dissertations-theses/efficiency-solvents-gas-chromatography/docview/301871733/se-2?accountid=13793

(8) C. Ragonese, D. Sciarrone, P.Q. Tranchida, P. Dugo, G. Dugo, and L. Mondello, 

(9) “Selecting a GC Column by a Specific Stationary Phase” Millipore Sigma, 2021. https://www.sigmaaldrich.com/US/en/technical-documents/protocol/analytical-chemistry/gas-chromatography/specific-stationary-phase? (accessed August 2021).

 (Elsevier, Amsterdam, The Netherlands), pp. 15–16.

 is the Founding Endowed Professor in the Department of Chemistry and Biochemistry at Seton Hall University, and an Adjunct 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: 

The late Harold McNair had a remarkable 60-year career as a chromatographer. He taught us many valuable lessons, three of which we discuss here.

Remember Harold McNair: Three Fundamental Areas of Understanding in Gas Chromatography

In this column, and elsewhere throughout the research community devoted to chromatographic sample preparation, the importance of the knowledge of the fundamental principles underlying sample preparation is emphasized. What is the role of solubility, diffusion, surface tension, and other parameters on the efficacy of extraction, selectivity, and so on? Of course, the answer is partly based on insight into the physicochemical principles upon which they are based, and partly based on serendipity. This month, we take a look at some of the more popular sample preparation methods, and present a discussion of their initial conception and development, to shed light on their current roles in our analytical “toolbox.”

Two years ago, we presented a retrospective look at the classical Soxhlet extraction, including the origins, operation, standard methods, and derivations (1). One can learn about the principles of modern techniques for extracting solid samples, such as via supercritical fluid extraction (SFE), pressurized liquid extraction (PLE), and microwave-assisted extraction (MAE), from a working knowledge of Soxhlet extraction, according to our premise. Now, let’s take it to the next step and investigate the origins of more modern treatments of extraction. To do this, we look to the chemical literature, but more importantly, some of the folklore is presented based on my conversations or subsequent communications with key players in the field of sample preparation. Last year, my colleague Brian Logue described his thought process in combining freeze concentration with stir-bar sorptive extraction (SBSE) to form a novel approach called 

ice concentration linked with extractive stirrer

 (ICECLES) (2). This is a great example of combining natural curiosity and an understanding of fundamental principles to develop modern approaches to analytical problem solving. Stories about the development of modern analytical extractions follow.

Perhaps the place to start is the beginning...of chromatography. Of course, A.J.P. Martin and R.L.M. Synge are foremost among the pioneers of analytical separations. In 1941, they separated amino acids via partition between aqueous and organic phases by designing a “mixer-settler” extractor (3). They abandoned this approach when they encountered mechanical difficulties with their apparatus, and turned their attention toward the development of liquid–liquid (partition) chromatography (LC). However, L.C. Craig picked up on this work in refining his countercurrent extractor.

As a side note, when I was in graduate school, Milton Lee always showed a Craig countercurrent apparatus during his separations course. Each time, one or more of the glass tubes broke off. I feel sorry for the more recent students that probably never observed a somewhat intact device.

We start this discussion with the advent of liquid chromatography (LC), because in 1977, James Waters, founder of the LC company that bears his name, challenged company scientist Patrick McDonald to “find new, faster, more convenient ways to do traditional sample preparation operations (4).” McDonald proposed to “solve a real analytical problem using, whenever possible, our LC technology.” The team at Waters used their silica-based adsorbent technology, along with triaxial bed compression and individual cartridge packaging to create the SEP-PAK product. Within a few years, countless competitors began appearing and the J.T. Baker Company rearranged the SEP (which stood for “Sample Enrichment and Purification”) acronym into SPE, or the more generic solid-phase extraction. This application of LC technology to analytical sample preparation was forward thinking to the extent that many of us are still asking the questions posed by Waters in their original marketing literature; see Figure 1 (4).

FIGURE 1: Questions posed by analysts in evaluating sample preparation technologies, as posed by Waters Corporation during the introduction of SEP-PAK Cartridges.

One of the most recent, and more intriguing, techniques in the sample preparation arsenal is that known as QuEChERS or quick, easy, cheap, effective, rugged, and safe extraction, developed in the 2000s. This approach has been adapted for use with the extraction of almost any analyte from almost any matrix, or so it seems. Steve Lehotay in the U.S. Department of Agriculture’s Agricultural Research Service laboratory in suburban Philadelphia and his colleague Michelangelo Asastassiades at the EU Reference Laboratory for Pesticides set out to develop what Lehotay described in an email message as, “the most efficient method for multiclass, multiresidue analysis of pesticides in foods.” (5)

Previously, both researchers had explored SFE and taxed it to its limits. Steve describes their collaboration as something like, “the Holy Grail of regulatory and industry laboratories for decades.” He explained further:

Increasing concerns about excessive glassware, use of chlorinated solvents, high labor needs, and low sample throughput were putting more pressure on laboratories to adopt more efficient practices. More sensitive, smaller, and less expensive gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–tandem mass spectrometry (LC–MS/MS) instruments were also being introduced at about that time, which permitted an even broader scope of analysis while still maintaining high selectivity in detection. This meant that sample preparation needed to recover a wide range of polar and nonpolar pesticides, but cleanup was still needed to avoid instrument contamination. (5)

Ultimately, it became a brute force effort. They were aware of magnesium sulfate as both a drying agent and an extraction aid, so that was a starting point. They isolated and studied solvent type, ratio of sample size to solvent volume, sample and buffer pH, salting-out salts and amounts, and extraction time and temperature. They determined recoveries depending on analyte polarity relative to the amounts of water and solvent used, along with measuring co-extractives. After tailoring the extraction for a broad range of pesticides and food samples, their attention turned to the dispersive-SPE step, addressing the perceived disadvantages of matrix-solid phase dispersion, the cost of cartridges, and related factors. Since that time, several vendors have modified the salts or parameters to expand the scope of the technique, and Lehotay has refined the approach to a new QuEChERSER which will be the subject of an upcoming "Sample Prep Perspectives" column.

In the food industry, it is customary to name extraction techniques after those who developed them, such as the Luke or Randall methods. However, the inventors apparently felt that the “Lehotay and Asastassiades Method” didn’t roll off the tongue with the same impact as listing the key attributes of the technique!

Continuing along the theme of extraction techniques based on chromatographic sorbents is solid-phase microextraction (SPME). Despite its name, SPME is not a miniaturized version of SPE. It is described as an open bed, diffusion rate-controlled technique (6). While numerous versions of the approach continue to appear, our discussion will focus on the original, traditional variant of SPME, and this is perhaps a case where sometimes a researcher can be too advanced.

The story of SPME begins in 1987, when Pawliszyn and Liu described sample introduction in capillary gas chromatography (GC) using laser desorption of the sample from the end of an optical fiber, as seen in Figure 2 (7). This provided inspiration to Pawliszyn, who realized that the fiber, clad with a stationary phase like polydimethylsiloxane (PDMS), could also extract organic compounds. The fiber optic replaced the wire used in microsyringes.

FIGURE 2: Depiction of laser desorption from the end of an optical fiber for sample introduction into capillary GC. Reproduced with permission from reference (7).

Since then, SPME continues to develop, with myriad configurations providing unique advantages. For example, thin-film SPME, the SPE Arrow, and SBSE all provide enhanced sample loading and sensitivity compared with the original device. One distinctive format is the coated-blade spray, also developed in Pawliszyn’s laboratory. Coated-blade spray builds from the substrate-spray ionization approaches to MS developed by John Fenn at Yale University, and later by Virginia Commonwealth University, Jentaie Shiea in Taiwan, and Graham Cooks at Purdue University. Coated-blade spray marries SPME and substrate-spray ionization for direct-to-MS analysis. A flattened, sword-shaped stainless steel blade is coated with stationary phase, much like SPME but with a broader array of phases. Then, after the sample is applied, an electrospray solution is added, and the device receives a high potential difference across the uncoated portion of the blade, resulting in electrospray ionization in the mass spectrometer.

SBSE represents an interesting example of applying your expertise to a seemingly unrelated situation, at least partially according to the folklore. We remember overhearing a conversation involving Pat Sandra from Belgium’s Research Institute of Chromatography, where he claimed that his inspiration was reading one of his colleague’s papers where, in performing a mass balance for an extraction, the author looked at sample losses due to volatilization, adsorption to the walls of the glassware and stir bar, and other reasons. Sandra thought he could apply a stationary phase to the stir bar and intentionally adsorb the analyte onto the device for subsequent desorption. There is more to this story, again demonstrating knowledge of fundamental principles reapplied in a novel manner.

David, Ochiai, and Sandra note that, in the early days of SPME, a controversy existed regarding the nature of the sorption phenomenon observed (8). Apolar solutes could potentially adsorb onto the Teflon-coated stir bar used for sample agitation, as well as onto the PDMS SPME coating. This led to the development, and subsequent commercialization, of PDMS-coated stir-bars for extraction, the advent of SBSE. In the two decades since Sandra’s keen insight, approximately 1000 reports of SBSE are in the literature.

The 1990s are considered the heyday of the development of modern instrumental approaches to sample preparation, including SFE and MAE. In the early part of that decade, Dionex/Lee Scientific introduced the Model 703 supercritical fluid extractor. Within a very short period, their competitors responded with their SFE offerings and with the more advanced developments, shortcomings in the earlier equipment rose to the forefront. In response, the Dionex Salt Lake City Technical Center, home to the SFE development, convened a customer focus group to “fix the SFE.” Led by Bruce Richter and Brian Jones, the conversation led to questions like “If nearly all SFE requires the use of an organic co-solvent, what is the role of the carbon dioxide?” From here, the concept evolved into the concept of an “analytical pressure cooker”—that is, the application of pressure to an extracting solvent with the intent of increasing its boiling point to create enhanced extracting conditions. Both kinetic and thermodynamic factors become favored at temperatures of 100–150 °C. The resulting technique became Accelerated Solvent Extraction (ASE), a trade name more generally referred to as PLE. During the development of SFE instrumentation in the 1990s, the U.S. Environmental Protection Agency’s Office of Solid Waste issued a memo to equipment manufacturers delineating the requirements to gain approval for an official EPA method utilizing SFE. Dionex followed this guidance during their development of the ASE technique, and they received early market acceptance. As a result of the introduction of ASE, not only did other vendors follow suit in creating competitive instrumentation, but the overhype of SFE declined. Applications of SFE became less risky and increasingly oriented toward those applications, like foods, flavors, or polymers, where supercritical fluids truly had advantages.

Finally, we introduce a novel sample preparation approach based on knowledge of extraction fundamentals and creative reapplication of casual observations. While I know little about the phenomenon of vaping, I realized that this approach is fundamentally sample preparation. The vaping device, via application of elevated temperature, vaporized sample components for delivery by inhalation. We obtained a dry herb vaporizer and, as the final part of his dissertation (8), one of our graduate students, Ahsan Ahmed, evaluated its use in analytical extractions. The particular device we used allowed controllable temperatures up to 240 °C. What was intriguing was that, not only could we employ temperatures similar to conventional headspace techniques and thermal desorption, but also at often unexplored temperatures intermediate between these techniques and pyrolysis. Ahsan used the vaping pen with little modification and SPME to collect the emitted vapors. Due to the volume of the vaping chamber, improved sensitivity resulted. Figure 3 shows the GC–MS results for the extraction, or vaping, of horseradish root as a function of temperatures from 150 to 240 °C. While further investigation is warranted and improvements to the device may be necessary, it shows promise for use in analytical laboratories, perhaps even for applications done “in the field.” Our initial paper describing this approach, our application to food and environmental samples, and comparison to headspace sampling is in preparation, with the intent of journal submission this fall.

FIGURE 3: GC–MS results demonstrate the use of a dry herb vaporizer for the extraction of horseradish root at 150 °C (blue), 200 °C (green), and 240 °C (red).

We’ve presented the told and untold stories surrounding the development of several modern extraction techniques. These examples confirm that the invention process requires understanding of the fundamental principles in a given field, often reapplied in a unique setting. While some of these reapplications may seem intuitive in retrospect, what is obvious to one investigator may not be so to others. Of course, serendipity also plays a role in the creative process. Perhaps, sometime down the road, readers of this column may be inspired to develop new approaches by employing their knowledge and experience.

(2) B.A. Logue, C. Skaggs, and A.H. Alluhayb, 

, H.A. Laitinen and G.W. Ewing, eds. (American Chemical Society, Washington, DC, 1977), pp. 292–326.

(4) P.D. McDonald, “James Waters and his Liquid Chromatography People: A Personal Perspective,” http://www.waters.com/webassets/cms/library/docs/wa62008.pdf.

(6) N. Reyes-Garces, E. Gionfriddo, G.A. Gomez-Rios, M.N. Alam, E. Boyact, B. Bojko, V. Singh, J. Grandy, and J. Pawliszyn, 

(9) A. Ahmed, Ph.D. dissertation, South Dakota State University, Brookings, South Dakota (2021).

“Sample Prep Perspectives” editor Douglas E. Raynie 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 

’s editorial advisory board. Direct correspondence about this column via e-mail to 

We look at five modern treatments of chromatographic sample extraction, explaining their initial conception and development to shed light on their current roles as analytical tools.

Origins of Sample Preparation Technologies

Kevin A. Schug is a Full Professor and Shimadzu Distinguished Professor of Analytical Chemistry in the Department of Chemistry & Biochemistry at The University of Texas (UT) at Arlington. He joined the faculty at UT Arlington in 2005 after completing a Ph.D. in Chemistry at Virginia Tech under the direction of Prof. Harold M. McNair and a post-doctoral fellowship at the University of Vienna under Prof. Wolfgang Lindner. Research in the Schug group spans fundamental and applied areas of separation science and mass spectrometry. Schug was named the LCGC Emerging Leader in Chromatography in 2009, and most recently has been named the 2012 American Chemical Society Division of Analytical Chemistry Young Investigator in Separation Science awardee.

I am flummoxed at the number of times I have encountered documentation of measurements made by public and private forensics laboratories for blood alcohol or drugs of abuse that does not include proper method validation. Over the years, I have been doing some consulting, reviewing what are called discovery documents associated with myriad different cases along these lines. I have also written previously, now more than six years ago, about an apparent lack of understanding of the importance of method validation by lawyers and judges involved in litigation involving forensics measurements (1).

With each case I have worked on, it becomes apparent there are common deficiencies regularly encountered in forensics analysis. Rarely have I been asked to review a case where I felt a comprehensive and completely reliable job had been performed. Of course, I am sure there are forensics laboratories out there that “do it right,” but somehow records from those cases do not often cross my desk.

The deficiency in method validation for forensics laboratories regularly manifests itself in two steps. The first step is where the forensics laboratory does not even provide any indication of method validation when delivering documentation of the case. The second step comes when the documentation made available indicates a lack of rigor in method validation.

The most complete guidance for forensics method validation is the recently published ANSI/ASB Standard 036 (2). Standard 036 replaces previous comprehensive guidance documentation from the Scientific Working Group for Forensic Toxicology (SWGTOX) and provides all of the necessary steps for full and partial method validations pursuant to ISO 17025 performance criteria. ISO 17025 is more of a catch-all guidance on best practices and provides less specific detail about how to accomplish forensic method validation than Standard 036 does.

Overall, method validation is a series of documented steps that demonstrate that the chemical analysis method on a particular instrument is fit for purpose—that, with proper calibration and quality control, the method can provide a reliable result. Any chemical analysis method, be it widely used or not, must be fully validated on the instrument where it will be performed.

Analytical instruments are exceedingly high precision measuring devices; ultimately, each is manufactured separately (there are also many different manufacturers) and may perform differently, to some degree. Thus, simply saying that since the method is run on this type of instrument at another laboratory, does not preclude the need to validate a particular instrument to run that method reliably.

Forensics laboratories should be able to provide details regarding instrument installation, and that the system met manufacturer specifications for performance once installed. Following that, full method validation should have been performed and been well documented prior to the analysis of any case samples. Full or partial validation should also be performed following major instrument changes or maintenance. For example, replacing or changing an analytical separation column can have a major impact on method performance; the method performance needs to be rechecked using method validation procedures, and redocumented.

Those of you in the analytical science community are likely well familiar with the concept of method validation. If you have developed a new quantitative method, it is almost impossible to publish it without extensive validation information. Whether using guidance from Standard 036, or some other guidance from, for example, the Food and Drug Administration or the Environmental Protection Agency, method validation will regularly involve determining the accuracy, precision, limits of detection and quantification, specificity, potential for carry-over, and other figures of merit for the method. Processes to determine these are given using specific blank, fortified (in other words, spiked), and real samples, run multiples of times, and data treated to provide each measure. The extensiveness of validation can be somewhat dictated by the complexities of the method. For example, sample preparation procedures that contain multiple steps should be evaluated for their efficiencies and recoveries to help ensure that an accurate result is rendered.

A problem I regularly encounter is the lack of adequate evaluation of matrix-matched samples during method validation. A variety of steps should involve the analysis of blank or fortified matrix-matched samples to evaluate the specificity of the method and its subjectivity to matrix effects or changes in the analysis exerted by the presence of interferences in the sample. Chemicals other than those of primary interest for the determination in a sample (in other words, the sample matrix) can alter the final signal of the target analyte in many different ways.

Blood drug determination by liquid chromatography–mass spectrometry is famously prone to matrix effects associated with ionization efficiency. That is why stable isotopically labeled internal standards are a must for those determinations. Yet, matrix components for many types of chemical instrumental measurements can exert effects throughout the process from sample preparation, through chemical separation, to final detection of signals. The method validation steps involving the measurement of fortified matrix samples are key for establishing lack of interferences (in other words, specificity).

Here is another example. It is often desirable to routinely use neat solutions of target analytes to prepare calibration curves for quantitation of a chemical in a biological fluid sample. In such a case, it needs to be shown during method validation that equivalent calibration results can be obtained from neat solution vs. from biological fluid; the absence of matrix effects needs to be demonstrated. This is not an onerous task, but without this information, you would not know if the results were subject to some bias.

Sometimes, matrix effects can be subtle. Five years ago, I wrote about a case where matrix effects yielded statistically significant differences in the response of an n-propanol internal standard, when measured from neat solutions compared to when it was analyzed from real blood samples, for blood alcohol measurements (3). This matrix effect appeared to, on average, cause all blood alcohol determinations on that instrument to be reported 20% higher than they likely were. The laboratory in question never used fortified matrix samples in their validation, thus, they had no knowledge of this bias. The sad thing is that I have encountered this instrument again a couple of years ago. I was able to show the same matrix effect and bias in the data, as I had seen years prior. That instrument has likely been reporting high biased blood alcohol results since its initial routine use in 2011.

Another common problem with the lack of evaluating blank or fortified matrix-matched samples during blood alcohol measurement validation and routine use is that specificity can often not be demonstrated. Most forensics laboratories use flame ionization detection (FID) for their gas chromatograph. An FID instrument responds to anything carbon-containing that elutes from the column. Often one observes extra so-called “ghost peak” signals present in around the chromatogram near the ethanol peak and the internal standard peak when real samples are analyzed. These may be present or absent in various neat samples, but if a blank fortified matrix sample was never analyzed to show there are no background signals present at the retention times of ethanol and the internal standard, then there is no way to guarantee the accuracy of the result. Small or large coelutions of interferences with ethanol or the internal standard can have a marked and very unpredictable effect on the final calculated result of the measurement. Standard 036 specifies that blank matrix samples from a minimum of ten different sources be evaluated during method validation to establish the specificity, or the lack of interferences, for the method. I think I have seen that level of validation documented in forensics discovery documents only once or twice.

I could continue this discussion with other such examples. However, the point I want to make is that the steps for proper method validation are well spelled out. Many forensics laboratories appear to obtain various accreditations without apparently being able to show they have performed and documented the performance of these specific steps. I see poorly validated analyses from accredited forensics laboratories all the time.

The steps to proper method validation are not difficult measurements to make, but they are critical for establishing the reliability of the method. I do not understand why these deficiencies are so common, and I do not understand why they persist. As a result, I have started a business called Medusa Analytical, LLC (

) that will, for a nominal fee, evaluate the veracity of discovery documentation. We return a checklist to the lawyers after a preliminary review of the discovery documents to indicate what things are missing or deficient. We hope this will help provide a broader capability to help ensure that only quality forensic measurements are being considered in litigation.

Forensics chemical measurement methods are generally pretty straightforward and should be reliable. There are well prescribed and straightforward ways to show the method is reliable vis-à-vis Standard 036 guidance. It just seems wrong that measurement results shown deficient in some aspect of method validation should be allowed to stand; especially, if they are called into question based on some aspect of a particular case sample, like the presence of ghost peaks. If the appropriate steps were not taken to ensure specificity of the method, then specificity should be doubted, and the reliability of the result should be doubted.

In the end, it always seems like a game about how much deficiency in the forensics chemical analysis process a court or jury will tolerate. Why should there be any tolerance for deficiency when a person’s livelihood is at stake? In my opinion, the chemical analysis should be one of the most reliable pieces of evidence in the case; it is a shame to see that it often is not, because a forensics laboratory apparently decided to cut some corners.

K.A. Schug, Forensics, Lawyers, and Method Validation—Surprising Knowledge Gaps. The LCGC Blog. June 8, 2015. 

http://www.chromatographyonline.com/lcgc-blog-forensics-lawyers-and-method-validation-surprising-knowledge-gaps

ANSI/ASB Standard 036, First Edition 2019. Standard Practices for Method Validation in Forensics Toxicology. Microsoft Word - 036_Std_e1 (asbstandardsboard.org) (Accessed August 16, 2021).

K.A. Schug, Indisputable Case of Matrix Effects in Blood Alcohol Determinations. The LCGC Blog. Sept. 7, 2016. 

http://www.chromatographyonline.com/lcgc-blog-indisputable-case-matrix-effects-blood-alcohol-determinations

Kevin A. Schug is a Full Professor and Shimadzu Distinguished Professor of Analytical Chemistry in the Department of Chemistry & Biochemistry at The University of Texas (UT) at Arlington. He joined the faculty at UT Arlington in 2005 after completing a Ph.D. in Chemistry at Virginia Tech under the direction of Prof. Harold M. McNair and a post-doctoral fellowship at the University of Vienna under Prof. Wolfgang Lindner. Research in the Schug group spans fundamental and applied areas of separation science and mass spectrometry. Schug was named the 

Emerging Leader in Chromatography in 2009 and the 2012 American Chemical Society Division of Analytical Chemistry Young Investigator in Separation Science. He is a fellow of both the U.T. Arlington and U.T. System-Wide Academies of Distinguished Teachers.

The deficiency in method validation for forensics laboratories regularly manifests itself in two steps.

The LCGC Blog: Full Method Validation Is Still a Glaring Deficiency in Many Forensics Laboratories

 passed away suddenly and unexpectedly on August 5, 2021. He was one of the most famous Czech analytical chemists. He was 77 years old.

Jandera spent his entire professional career in the Department of Analytical Chemistry at the University of Pardubice, formerly known as VŠCHT Pardubice (the University of Chemical Technology). Jandera was a world leading scientist in the area of chromatographic techniques. He focused on various aspects of high performance liquid chromatography (HPLC), mainly the theoretical principles of the separation process, retention mechanisms, and the development and optimization of methods for the analysis of various types of compounds in the environment, food, and industrial products, such as dyes, pesticides, drugs, detergents, fats, oils, and in later years, antioxidants.

Jandera finished his master studies in 1967, at VŠCHT Pardubice in 1967, where he stayed for his PhD studies in analytical chemistry. Starting in 1970, he held the position of research assistant. Because of his involvement in the political events in 1968, he was not allowed to defend his PhD until 1977. In 1980, he prepared his associate professor thesis entitled “Theoretical and practical aspects of gradient elution in column liquid chromatography,” but he was not allowed to defend it until 1989. The same year, he also completed his DrSc grade defense at VŠCHT Praha. In 1990, he became an associate professor, and after his return from one-year research stay at the University of Tennessee, Knoxville, in the United States, he became a full professor at the University of Pardubice, where he worked until his very last day.

Jandera’s entire scientific career was closely connected with HPLC. He introduced a comprehensive theory of gradient-elution chromatography, which was published together with Professor Jaroslav Churáček in the book 

Gradient Elution in Column Liquid Chromatography,

 published by Elsevier in 1985. Then he continued with the development of gradient-elution techniques in preparative chromatography in cooperation with Professor Georges Guichon of the University of Tennessee, Knoxville. Jandera and his team developed new methods for the evaluation and characterization of columns for liquid chromatography. In recent years, he investigated microcolumn techniques of liquid chromatography, mainly the development of high-performance monolithic capillary columns with tailored selectivity and two-dimensional liquid chromatography (2D-LC). Jandera and his team optimized the coupling of polar and nonpolar columns in 2D-LC to increase peak capacity for a higher number of resolved compounds in a single analysis. His research results were published in 260 scientific papers in prestigious peer-reviewed journals, mainly within the field of analytical chemistry, as well as five monographs, and more than 20 book chapters. Jandera’s work was respected by the scientific community, as illustrated by his more than 9000 citations and H-index 52, and by his regular invitations for plenary and keynote lectures at leading international conferences and invitations to prepare review articles. Two of his review articles (1,2) classified as “highly cited in the field,” which means that they are among the top 1% of the most cited publications in a given field.

After the Velvet Revolution in the Czech Republic in 1989, Jandera was very successful with grant applications to fund the research work of his team. He was the principal investigator of eight research projects funded by the Czech Science Foundation and the Grant Agency of the Academy of Sciences of the Czech Republic, and a co-investigator of several international projects, including bilateral projects with researchers in the United States, Greece, and the North Atlantic Treaty Organization (NATO) Science Program. He also acted as a coordinator of many student exchange programs within the European Union Socrates and the Central European Exchange Program for University Studies (CEEPUS), which allowed foreign research stays for many of his students and internships in his laboratory for students and young postdoctoral researchers from Slovakia, Italy, Poland, Greece, Hungary, Slovenia, and the United States. He also participated in another important multilateral project, the 5th EU Framework program “Comprehensive Liquid Chromatography”(COM-CHROM, 2000–2006), which included cooperation with universities in Italy, the Netherlands, France, Norway, and Sweden, with the aim of educating young researchers in analytical chemistry. The international cooperation and internships allowed students to learn new techniques and establish new contacts with other leading analytical groups in Europe.

Jandera was also actively involved in numerous scientific committees. He was a member of the permanent scientific committee of the International Symposium on Separation Sciences and chaired this symposium in 2005 in Pardubice and in 2014 in Prague. He was also an honorary chair of the HPLC 2017 Prague symposium. He frequently chaired scientific sessions at international chromatographic conferences. He was a long-term member of Czech Chemical Society, where he held the position of vice-chair of the working group for chromatography and electrophoresis. He was a national affiliate of the Central European Group for Separation Science, an IUPAC fellow in the IUPAC committee for separation methods in analytical chemistry, and a member of the international committee “Mediterranean Separation Science Foundation Research and Training Center.” He was also a member of the editorial boards of the international journals 

Jandera’s contributions were highly appreciated by the scientific community, and he received many prestigious awards over his career. Highlights include the Tswett Foundation Award (1988), the Hanuš medal of Czech Chemical Society (2004), a memorial medal from Nicolaus Copernicus University in Torun (2005) and the University of Messina (2005), the A. Wakszmundski Award for important achievements in the field of separation sciences awarded by the Polish Academy of Sciences (2011), the AJP Martin Gold Medal awarded by the Chromatographic Society (2015), the Silver Medal of Senate of the Czech Republic (2015), the Jaroslav Janák Medal awarded by the Institute of Analytical Chemistry at the Academy of Sciences in the Czech Republic (2015), the Giorgio Nota Award for lifetime achievement in capillary liquid chromatography (2016), and the Tswett & W. Nernst Award by European Society for Separation Science (2016).

Jandera was also very dedicated to the teaching and education of students and young researchers. He regularly lectured on the topics of “Identification, structure elucidation, and determination of organic compounds,” “chromatography and electrophoresis,” and ”optimization of separation processes.” He supervised 25 PhD theses and dozens of diploma theses. His former PhD students now work at various positions in academia and industry, including his alma mater as well as Masaryk University in Brno, the University of Chemistry and Technology Prague, and other Czech universities and institutes of the Czech Academy of Sciences. When traveling was again possible after the end of the communist regime, he encouraged all his students to travel abroad to extend their knowledge and gain new experiences.

Group members and close cooperators will remember that Jandera had both deep knowledge in chemistry and broad knowledge in other fields, especially in history and the arts. He enjoyed lively discussion with colleagues and friends at conferences or other less formal occasions, preferably with a glass of good red wine. However, he always put his beloved family first, and his favorite summer vacation was at their cottage, immersed in nature.

We would like to preserve the memory of Professor Jandera, who shaped several generations of analytical chemists and mainly chromatographers. His scientific contribution to chromatographic theory is so significant that it will be forever remembered.

Anyone who wishes to share memories or condolences is welcome to do so at the following website: 

In loving memory, on behalf of the Department of Analytical Chemistry, his former cooperators, and his students.

P. Jandera, “Stationary and Mobile Phases in Hydrophilic Interaction Chromatography: A Review,” 

P. Jandera and P. Janas, “Recent Advances in Stationary Phases and Understanding of Retention in Hydrophilic Interaction Chromatography. A Review‎,” 

are associate professors of analytical chemistry at the University of Pardubice in Pardubice, in the Czech Republic. 

 is an assistant professor of analytical chemistry at the University of Pardubice. 

 is an associate professor at Masaryk University, in Brno, in the Czech Republic. 

 is a professor of analytical chemistry at the University of Pardubice in Pardubice, in the Czech Republic. Direct correspondence about this article to 

Professor Pavel Jandera passed away suddenly and unexpectedly on August 5, 2021. He was one of the most famous Czech analytical chemists. He was 77 years old.

In Memory of Pavel Jandera, Leading Chromatographer

Tony Taylor 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 LCâMS and GCâMS for materials characterization, especially in the field of extractables and leachables analysis.

Electronic pneumatic controllers (EPC) were introduced into gas chromatography (GC) systems from the mid-1990s onwards and do an excellent job of regulating gas flow and pressure for GC inlets, columns, and detectors. They take the hard work out of manual gas flow, pressure adjustment, and manual-flow measurement, and they typically provide accurate and reproducible results, time after time. One simply selects the required pressure or flow from the instrument or data system and then checks the instrument readback to see if the setpoint has been successfully achieved. Truly black box technology, what can possibly go wrong? Well, regular readers will know that, while I support innovation and improvements in engineering capability, I am inherently skeptical of anything with the “black box” tag and believe that unless we inherently understand how something works, we can neither fully harness the potential benefits, nor properly troubleshoot when something goes wrong. Therefore, read on as we open the lid and take a good look inside these particular black boxes.

So, how do EPC devices work? Typically, a forward-regulated gas supply from the source is provided to the EPC unit that contains a variable metering valve that can be varied according to the set point for flow or pressure required. The required gas flow or pressure value is sent to the EPC controller from the GC system and a flow or pressure transducer is used to monitor the actual flow or pressure and the metering valve adjusted to obtain and maintain the desired setpoint value. This is known as a “closed-loop” control system. As can be seen in Figure 1, frits of fixed diameter may be included to provide adequate flow resistance downstream of the EPC pressure sensor, or upstream of a flow sensor. Most EPC systems will calculate required pressure drops for the column dimensions and the gas type to account for the different compressibility of our common carrier and detector supply gases. Other factors may also be compensated for, such as controller temperature, gas supply pressure, and atmospheric pressure, which can reduce instability and drift in the gas flows delivered to the GC inlet, detectors, or auxiliary equipment.

Figure 1 shows a typical EPC-controlled split/splitless inlet operating in split mode. The total flow into the inlet is set and monitored by value A and flow sensor A. The flow through the split line is controlled by valve B and pressure sensor B. Valve C and pressure sensor C controls the flow through the septum purge line. The flow through the column is not directly sensed, but is the balancing flow between that which enters the inlet via valve A and the flows through valves B and C. So, let’s say we need a column flow of 1 mL/min and a split ratio of 100:1. Approximately 104 mL/min will be supplied via valve A, typically around 3 mL/min will leave the inlet via valve C and the septum purge line (which is physically separated from the inlet region occupied by the sample when injected) and 100 mL/min will leave via Valve B and the split line. The remaining and balancing flow of 1 mL/min will be transferred to the column. 

 Schematic diagram of an EPC module used to control gas flows in a split/splitless inlet (Figure courtesy of Agilent Technologies, Santa Clara, California, USA).

Figure 1 illustrates the EPC control of a split/splitless inlet, the configuration for gas control to detectors and auxiliary and sampling equipment may be different, but all work on similar principles.

The astute reader will have noted that in our inlet example, only the carrier supply flow into the inlet is measured as a flow. The actual flow of the carrier through the column is not directly measured by the instrument, rather it is calculated from a differential of flow into the inlet (flow sensor A) and pressures out of the inlet (pressure sensors B and C). Most GC vendors will have a calculator which highlights the principles on which this principle works and using such a calculator I was easily able to compute that in order to obtain a carrier gas linear velocity of 35 cm/sec-1 of helium through my notional 30 m x 0.32 mm x 0.1 mm GC column at 50 

C, the carrier gas pressure required at the inlet is 10.01 psig which will result in a column (outlet) flow of 2.13 mL/min. For a split ratio of 50:1, the required split flow can be calculated as 106.5 mL/min. Of course, I could have calculated the required pressure to obtain a particular column flow, rather than a linear velocity, in exactly the same manner.

These same calculations are carried out “on-board” the GC system and the required pressures for the inlet set by the EPC control units.

This leads me to highlight the first potential “gotcha” when using EPC systems for gas control. Unless the end user specifies the correct column dimensions in the chromatograph (or data system), the actual flow through the GC column may be different than intended, even though the GC system will report the correct flow value.

Let’s look at a quick example of this. Provided the GC can attain and maintain the pressure setpoint required for what it has calculated as the correct flow rate or linear velocity of the carrier through the column, it will carry on regardless. If we suppose that an error was made in the previously cited example and the internal diameter of the column was entered as 0.25 mm rather than 0.32 mm then the instrument would believe it needed to set an inlet pressure of 16.76 psig to achieve the desired 35 cm/sec-1 carrier gas linear velocity. As the actual internal diameter of column 0.32 mm, the actual column flow would now be 4.18 ml/min and the average linear velocity 57.4 cm per sec, a difference in flow rate of 196% and one would notice very much shorter retention times and perhaps compromised analyte resolution. Further, because the split flow rate would remain unchanged, the split ratio would be in the order of 25:1, risking column overload and perhaps further compounding any issues with the resolution of critical peak pairs. One also needs to remember that as the column length is “trimmed” to maintain good chromatography. This will also influence the pressure required to obtain a required flow or linear velocity. If significant lengths of the column are trimmed, one should note on the column hangar tag or column log, the “new” length of the column. The lesson here is to be very careful to properly specify and check the column dimensions (including stationary-phase film thickness) when prospering for GC analysis. While EPC control is highly advantageous, it is by no means infallible.

Of course, one might choose to manually check the column flow prior to analysis to ensure it is correct, using an electronic flow meter. Here is the second issue that I regularly get questions on: “Why does my flow meter read a different flow to the value reported by my GC system?” Of course, one answer could be that there has been an error in setting the GC column dimensions in the systems as discussed above, but even when the dimensions are correct, there can be differences between the instrument reported value and the measured value.

Some of these differences can be caused by the type of flow meter used and its calibration. These topics are beyond the scope of the current discussion, but I would point readers to an excellent article in 

 magazine by John Hinshaw on measuring gas flow for gas chromatography (1). In accounting for differences between instrument flow values and those measured by modern electronic flow meters used to manually check the flow rates produced, we must consider the concept of Standard Temperature and Pressure (STP). In most cases, the standard pressure will be assumed to be 101.325 kPa but Standard Temperature can vary depending upon the industry we work in, geographical location, and the manufacturers of the GC equipment and metering devices. The International Union for Pure and Applied Chemistry (IUPAC), specify the standard temperature for gas measurement to be 273.15 K (0 oC) but temperatures of 20 and 25

C are also used for “Standard” gas measurement by various bodies and indeed by equipment manufacturers. While some EPC units and flow meters can adjust for differences between standard and local conditions, clearly those which cannot need to have some correction factor applied to the measurement in order to account for the variations between the conditions under which the equipment was calibrated, and local conditions. Fortunately, there is a fairly simple equation that can be used for these purposes:

In this equation, the superscript “o” designates standard or reference conditions under which the equipment was calibrated, and the subscript “a” designates ambient (local) conditions under which the measurements are being made.

C and 101.325 as the standard conditions and an instrument flow reading of 2.1 mL/min—let’s see what differences there would be between flow meter measurements using a made-in-a-cooler laboratory under lower atmospheric pressure conditions (T-16 

C and p – 99.200 kPa) and a warmer environment under the same atmospheric pressure conditions (T – 28 

While these differences are not vast, they do go some way towards explaining why meter readings can be different from those displayed on the instrument, and they can highlight that, where methods are to be transferred between laboratories in different parts of the world with varying ambient conditions, some account must be taken to standardize the measurement of flow. It should also be noted that some flow meters impose a back pressure on the gas flow, which may change the response of the EPC system and then cause spurious flow reading. Again, I would urge readers to consult Reference 1 for further information.

A further contributing factor to the differences between flow meter and instrument readings involves the “drift” that can be encountered by EPC devices over time. While the “slope” (sensitivity) of EPC metering valve calibration tends to be steady, the “offset” values in terms of valve position versus metered gas flow can from time to need to be reset. There is no pre-defined time interval for this operation, but some manufacturers will include an EPC reset or zero function which will allow the user to reset the EPC valve position and “calibration,” and you should consult your manufacturer’s literature for guidance. Care should be taken as flow zeroing tends to be carried out with gas flowing, whereas pressure zeroing requires no gas flow.

The final EPC topic worthy of consideration is that of carrier gas operation in constant pressure or constant flow mode during GC oven temperature programming. As the oven or column temperature increases the gas viscosity also increases, and under constant inlet pressure conditions, the carrier gas flow and linear velocity will reduce. This is very often not the best situation for chromatography (long analysis times and broadening peaks) and several detectors also work more optimally with a constant flow situation. The ionization efficiency and fragmentation pathways analytes with the ion source of mass spectrometric detectors can be dependant upon ionization source pressure and therefore the flow into the ion source. Flame ionization dectors using hydrogen as the carrier can show changes in response if the volume of hydrogen to air and makeup gases changes. Therefore, it is better to keep a constant flow of hydrogen from the column during the temperature program.

EPC units are calibrated to calculate the required pressure drop across a column (provided we input the correct column dimensions!) versus temperature in order to maintain a flow rate setpoint. In this way, as the oven temperature rises, the EPC module can increase the inlet pressure so that constant flow is maintained as the column temperature and carrier gas viscosity increases. In our previous example, the 10.01 psig required to obtain 35 cm/sec helium flow at 50oC will rise to 15.02 psig in order to maintain this linear velocity at 300 

C. This helps to overcome some of the disadvantages of the constant pressure operation described above which is illustrated in Figure 2.

 Monomer separation carried out under constant pressure operation (top) and constant flow mode (bottom).

It is often advantageous to maintain a constant flow of carrier gas into a detector, and therefore, even if one is operating in constant pressure mode for the GC carrier gas, detector EPC units are often capable of ramping the flow of a fuel or make-up gas during the temperature program, such that, as the carrier gas flow decreases, then total flow experienced by the detector remains constant.

While these EPC operations are highly beneficial, the operator needs to be aware of how to implement them within the GC hardware or controlling software and everything that has been said above regarding EPC operation under non-standard conditions. Recalibration or zeroing needs also to be kept in mind for trouble-free operation.

I hope that this deeper dive into the working principles and potential issues of EPC modules in GC has helped to broaden your understanding. Certainly, these advances in gas control have brought many advantages to practical GC usage, but as always, without a deeper understanding of the working principles and limitations of such systems, one cannot ever truly exploit these advantages or properly investigate issues when trouble occurs!

https://www.chromatographyonline.com/view/measuring-gas-flow-gas-chromatography

Tony Taylor is the Chief Scientific Officer of Arch Sciences Group and the 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 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.

Electronic pneumatic controllers (EPC) were introduced into gas chromatography (GC) systems from the mid-1990s onwards and do an excellent job of regulating gas flow and pressure for GC inlets, columns, and detectors. Regular readers will know that, while I support innovation and improvements in engineering capability, I am inherently sceptical of anything with the “black box” tag and believe that unless we inherently understand how something works, we can neither fully harness the potential benefits, nor properly troubleshoot when something goes wrong. Therefore, read on as we open the lid and take a good look inside these particular black boxes.

The LCGC Blog: Electronic Flow and Pressure Control in Gas Chromatography: Opening the Lid of the Black Box!

Microplastics are now recognized as pervasive in the environment, as well as in stormwater, wastewater, ocean water, coastal sediments, drinking water, and even animal tissue. The mismanagement of plastic waste throughout the world is a matter of urgent concern that has led to product bans for small plastics, such as microbeads used in cosmetic products, to larger plastic items, such as bags and straws, that can degrade into microplastics. This concern has also resulted in new and planned requirements to monitor microplastics in the environment. The implementation of monitoring programmes requires reliable standardized methods and best practice guidelines, yet environmental measurement and monitoring practitioners still do not have established practices and methods for collecting and analyzing plastic pollution. This deficiency has resulted in significant challenges in the interpretation of research findings for use in corporate or government policy. A major issue with measurement based upon sampling and analysis of microplastics is their unique behaviour; environmental microplastics occur as non-homogeneously distributed particulates and fibres composed of various polymeric materials. This article provides an overview of the environmental and analytical challenges caused by microplastics; it proposes an analytical measurement approach that enables accurate qualitative and quantitative analysis of microplastics, and demonstrates some of the advantages of pyrolysis–gas chromatography–mass spectrometry (Py–GC–MS) for the analysis of environmental samples as compared to the other leading analytical methods.

Plastic waste has proven very difficult to measure. In 2019, 368 million tons of plastic were produced (1), an increase of more than 600% over the last four decades (2) (Figure 1). Global collection rates of plastic waste over the same timeframe remained stagnant, not surpassing 10% of production worldwide (3). Collection and sorting of plastic waste into recovered material is not a guarantee that it will be recycled. This low recycling rate has been exacerbated by implementation of China’s National Sword Policy on 1 January 2018, with its rejection of imported recovered plastic waste from Western countries.

Examination of the sources of these problems can also be misleading. For example, a leading economic model uses surrogate factors for plastic waste mismanagement and depicts non-Western countries as being primarily responsible for the inputs of plastic pollution into the environment (4). These models miss the point that countries like the United States have high per capita plastic consumption with sporadic and inconsistent waste management infrastructure, often exporting large portions of recovered plastic waste to non-Western countries (5). Final disposition of plastic waste exports from Western countries is now a bigger unknown than it was prior to 2018, with likely more plastic ending up in landfills, burned, or accumulating in outdoor heaps and piles and migrating to watersheds, creeks, streams, rivers, and the ocean during wind and rain events. The problem of plastic pollution does not belong to “other” countries but is very much one of every nation. As plastic debris enters roadways and watersheds, it threatens our natural environment (Figure 2), pollutes and clogs stormwater conveyances, and can pose significant sanitation and public health issues, such as an increase in standing water and mosquito vector growth. As debris enters streams and rivers, micro- and nanoparticles are generated at rates dependent on the forces acting upon them and their polymer type and plastic form. We anticipate that microplastic monitoring will become more prevalent as a means for measuring plastic pollution in the environment.

Plastic debris in the environment is not inert. Plastic debris ultimately fragments into smaller particles over time as a result of the effects of weathering, including UV radiation and wind and wave action. As debris breaks down into smaller and smaller particles, polymer surface areas increase relative to their volume, and these surfaces can host pathogens, such as bacteria and viruses. These smaller plastic particles, with their relatively higher surface area, have a greater propensity to sorb persistent organic pollutants (POPs) such as polychlorinated biphenyls (PCBs) and pesticides from surrounding air, dust, and water.

Additionally, the manufacturing process of plastic products typically adds chemical constituents, or plasticizers, to augment polymer characteristics and performance, and some of these additives are toxins or carcinogens. It is currently unknown to what extent plasticizers from within microplastics and any sorbed contaminants on the surface of particles are able to desorb and, upon ingestion by an organism, be taken up by the organism’s tissue and organs (Figure 3). These contaminated microplastics form dust pools both indoors and outdoors. Plastic particles have been documented in every environmental media, and reports in 2019 and 2020 present evidence that plastic is even raining down on us. This pervasiveness and persistence of microplastics and nanoplastics cause some to speculate that scientists of the future will use these plastics as a tool for dating abandoned habitations and geologic strata.

The behaviour of microplastics in environmental media is expected to be somewhat more predictive than that of larger debris, which is subject to chaotic ebbs and flows of wind and water. Although plastic fragments may initially float on the water’s surface, they soon become suspended in the water column as they become covered in biological growth; biofouling increases the specific gravity, which decreases buoyancy. It has been assumed that, ultimately, most waterborne microplastics are destined for the floor of an ocean, lake, or river, perhaps being ingested along the way or resuspended through various mechanisms on their way to, and once on, the bottom. However, colloidal suspension and electrostatic interaction between the smallest of these plastic particles and the resulting effect on transport and occurrence in the environment is an area of study that has yet to be explored.

Until recently, calculations of density and distribution of plastic in the environment focused almost exclusively on the visible size range above 300 µm, and employed visual techniques as a means of identification. In addition, these samples were collected on the ocean surface. The majority of microplastics in the environment, both water and air, are now believed to be smaller than 300 µm.

You Can’t Manage What You Can’t Measure

Rigorous and reproducible identification of plastic particles is critical to pollution monitoring. Considering the mantra “you can’t manage what you can’t measure”, effective upstream policy, including corporate and government action to reduce the occurrence of plastic particles, must rely on robust monitoring regimens. Efficacy of mitigation actions will not be measurable without such monitoring, and measurement standards therefore must be agreed on and widely adopted.

The risk of microplastics to our natural environment, and to public health, can be described as the likelihood of harm based on both toxicity and exposure, yet this understanding of risk has been stymied by the lack of rigour, standardization, and reproducibility of measurement practices and methods. While spectroscopy techniques measure plastic particle count, the properties of smaller plastic particles create a sort of fingerprint more easily traced with mass-based concentrations. Mass-based concentrations are much more conducive to benchmark comparisons such as ambient conditions or regulatory thresholds. Measuring concentrations of these tiny plastic particles and their effects on humans and animals necessitates the global standardization of collection, preparation, and identification procedures and methods.

Standardized methodologies for nondestructive collection, handling, separation, sample preparation, and positive identification of microplastics are in the early stages of development. ASTM International is leading the way with recently published standards for collection (D8332) and preparation (D8333) of microplastic particles. Some of the leading technologies currently available that yield scientifically defensible and reproducible results for positive microplastic identification include focal plane array detection, thermogravimetric analysis–pyrolysis–gas chromatography–mass spectrometry (Py–GC–MS), and infrared (IR) and Raman spectroscopy.

Presently, most researchers attempting to positively identify polymers are employing IR or Raman spectroscopy for analysis of particle type and count. Information on particle polymer type, count (per unit volume), and size are germane to specific research contexts, and some advanced spectroscopy technologies have reduced operational procedures from upwards of a week to only hours; in most instances, spectroscopy remains time-consuming and costly, and requires highly trained and skilled technicians with sophisticated laboratory equipment. Although a high degree of skill is also needed for Py–GC–MS, this technique offers a solution to speed up sample preparation and analysis time, while yielding perhaps more practical information on polymer types and mass per volume.

For water quality monitoring activities such as discharge management, plastic particle identification by mass per unit volume may be more useful for both point source and non-point source measurement. We believe that the use of Py–GC–MS for polymer identification has broader applicability than IR or Raman spectroscopy because it is less constrained by particle size (large or small), requires less preparation, has fewer interferences, has less potential for analytical error, enables straightforward calibration, provides consistent and highly reproducible results, much lower equipment entry costs, and readily available polymer identification libraries. It is also conducive to varied matrices, such as water, soil, and biota, enabling more easily accomplished comparisons.

Here, we outline the development of the Py–GC–MS method, and explain its practical application to understanding the occurrence and prevalence of microplastics, and potentially even nanoplastics, in the environment.

Recent studies have discovered the unique capability of the microfurnace pyrolysis–GC–MS technique in the identification of polymer types and quantities in microplastic particles. This article describes the study of microplastics in water samples with high and low suspended solids using a microfurnace pyrolyzer directly interfaced with a benchtop GC–MS instrument.

The samples were collected from drinking water, wastewater influent and effluent, surface water, and marine water. The developed method using the microfurnace Py–GC–MS confirms that the analysis of microplastics in such water samples is independent of polymer type, and not limited to any particular water matrices. The method proves higher analytical sensitivity for both qualitative and quantitative analyses, including better detection limits. The inorganic contaminants in the sample matrices do not impede the identification and specification of the polymers and associated additives. Detailed information about the chemical nature of the polymer and contained organic additives are also obtained simultaneously.

Most of the initial research on analyzing microplastics was developed using spectroscopy techniques such as Fourier-transform infrared (FT-IR) and Raman spectroscopy. These traditional techniques are nondestructive and are commonly used in analytical laboratories. They provide information for functional group identification and library comparison. Detailed information about the contained organic additives is usually not obtained because contaminants (organic or inorganic) and additives can overlap polymer bands. In other words, FT-IR can suffer from peak masking if two or more compounds in a mixture with the same dipole moments absorb IR rays at the same or nearby wavelength. In this case, identifying the overlaid peaks will be extremely difficult. With Raman spectroscopy, measurement of samples that contain fluorescent dyes is very challenging.

The need for sample preparation, such as matrix isolation, solvent extraction, or pretreatment, is another challenge with these traditional techniques. Typically, it could take several hours to perform the analysis, and quantitation is challenging. The limit on sample particle size with these techniques must also be considered. Micro-Raman spectroscopy and an optical microscope are used for particle size analysis that is larger than 1 µm, whereas FT-IR can be used for particle size larger than 10 µm.

In contrast, microfurnace Py–GC–MS can be used for both qualitative and quantitative analysis of low microplastics concentrations because of its high sensitivity capability. Although there is no practical lower limit in particle size, total polymer mass in a sample constrains the lower limit of the measurement (see Figure 4). In addition to microplastics, GC–MS adds the benefit of detecting and quantifying both additives and contaminants in the sample using interpretation libraries. Sample preparation is easy and straightforward; micrograms of a sample (including solids taken “as is”) are placed into an inert pyrolysis cup, and the analysis can be performed. The recent developments in F-Search software for microplastics data processing, which is an automated analysis (quantitative and qualitative), has also significantly shortened the time needed for the analysis.

The microfurnace utilizes a low thermal mass ceramic heater to quickly heat and cool with thermal uniformity. This technology can be used for multiple analytical techniques in addition to flash pyrolysis, such as evolved gas analysis (EGA), thermal desorption (TD), double‑shot (TD followed by flash pyrolysis), and heart-cutting. All the surfaces are quartz or temperature stable deactivated, and there is no cross-contamination.

The microfurnace performs continuous pyrolysis in a single step by directly depositing all the pyrolyzates on column as they are generated. The direct connection of the microfurnace to the GC injection port allows this single-step pyrolysis where reproducibility and temperature accuracy are obtained. The sample is held near ambient temperature and in an inert atmosphere prior to pyrolysis. Therefore, there is no chance for evaporation or degradation of the sample before the analysis, maintaining sample integrity and contributing to accuracy, precision, and reproducibility of the data set. The microfurnace is preheated to the desired temperature and precisely measured with a thermal couple sensor. The sample cup then freefalls into the quartz pyrolysis tube, where the sample is rapidly and reproducibly pyrolyzed. The pyrolyzates are directly swept onto the GC column for separation and detection by MS. A critical factor with the microfurnace is its ability to control the actual sample temperature to within ±0.1 °C set point of the pyrolysis temperature. This feature guarantees reproducibility and precision, as well as true flash pyrolysis, where the set temperature in the furnace by the analyst reflects the pyrolysis temperature on the sample.

There are other pyrolysis technologies: filament, which uses platinum coil wire, and Curie-point, which utilizes a ferromagnetic foil. These technologies can suffer from poor temperature accuracy and poor reproducibility because of non-uniform heating. In both systems, to avoid condensation of the pyrolyzates, the sample must be inserted into a heated manifold before pyrolysis. This preheating step can cause degradation or thermosetting of the samples prior to analysis. With filament pyrolyzers, sample placement and heat-transfer variations also affect the temperature of the sample, depending on where the sample sits in relation to platinum wire coils and on sample contact. The filament temperature is estimated from the electrical properties of the wire, but the temperature of the sample is not actually measured as it changes over time. In other words, the platinum wire can only control the temperature of its heating element, not the actual sample pyrolysis temperature, requiring the user to program the system at a much higher temperature than the desired true pyrolysis temperature on the sample.

In a study of microplastics in surface water using a filament pyrolyzer, the pyrolysis temperature was set at 750 °C, with the sample placed in a narrow quartz tube inside the platinum wire (6). Based on actual bond energy strengths, polymers and other organic material will typically pyrolyze prior to a temperature of approximately 700 °C. Therefore, the only reason to set an initial pyrolysis temperature in excess of 700 °C is that the actual sample temperature in the pyrolyzer is not accurate. Literature indicating pyrolysis at 1200 or 1300 °C is either unnecessary, over pyrolysis, or shows poor actual sample temperature control in the particular pyrolysis device.

It is critical to note that some filament pyrolyzers perform two-step pyrolysis. First, some of the pyrolyzates are collected on a trap, and then a switching valve sends the pyrolyzates from the trap through a long transfer line into the GC column. In this configuration, the pyrolyzates are indirectly placed on column. During this two-step process, polar and heavy compounds may cause cross-contamination, or become irreversibly stuck in the trap or the long transfer line, and are not transferred for analysis because of the potential of cold spots in the system.

Figure 5 shows the system configuration of the microfurnace pyrolysis–GC–MS used for microplastic analysis in the water samples. Experiments were performed with a microfurnace pyrolyzer (EGA/PY-3030D, Frontier Laboratories Ltd.) with Auto-Shot Sampler (AS-1020E, Frontier Laboratories Ltd.) coupled to a GC–MS system (5977B MDS, Agilent Technologies, or GCMS QP-2020NX, Shimadzu Corporation). Chromatographic separation was achieved using a metal capillary column (UA-5, 0.5 μm film of 5% diphenyl-95% dimethylpolysiloxane, 30 m × 0.25 mm, Frontier Laboratories Ltd.) with helium (He) as the carrier gas (1 mL/min). Reduced analysis time can be obtained by utilizing a backflush system, especially when dealing with high-boiling point matrix interference or high-molecular-weight pyrolysis products. This system consists of a precolumn (UA-50, 1 μm film 50% diphenyl 50% dimethylpolysiloxane, 2 m × 0.25 mm, Frontier Laboratories, Ltd.) connecting the injector and the separation column with a three-way split (7).

Using the flash pyrolysis mode of operation (the single-shot mode) of the microfurnace, the chemical composition analysis was performed on microplastic samples. The microfurnace was programmed at 600 °C to break down the organic bonds of the samples into smaller and more stable molecules, referred to as 

. The pyrolyzates are directly swept from the pyrolysis tube into a GC column, via a needle fixed in a split injection port. The column was interfaced directly to an MS instrument. The chemical species were ionized and sorted, based on their mass-to-charge ratio. Compounds eluted from the GC column were identified by comparing the mass spectra at a predetermined retention time to reference spectra and retention index (RI) to those contained in a database.

Table 1 shows some of the polymers that can be identified using microfurnace Py–GC–MS. The validation is performed using a pyrolyzate primary quantitative ion and identification ion(s) representative of a specific polymer. It is important to note that the developed method is not limited to the polymers listed in the table.

Figure 6 demonstrates a typical pyrogram of the 11 target pyrolyzates and their associated polymer (in parenthesis), using the developed method described above.

The concentration of each identified polymer is determined using either internal or external standard calibration. Using a multi-component standard (8), the calibration curves can be obtained. Table 1 lists the data precision of each polymer for 

As mentioned earlier, F-Search, an automated search program, has been augmented for the fast identification and quantitation (in the range of seconds) of microplastics. The search algorithm is based on the identification of the selected number of characteristic pyrolyzates of each polymer in the sample. Each selected pyrolyzate is only obtained from the pyrolysis of a polymer, and not from the pyrolysis of all other investigated polymers. For each characteristic pyrolyzate, a set of specific 

 signal intensities is also selected. A normalized summated mass spectra (SMS) is obtained from the selected 

 signal intensities so that the mass spectra are cleared from any interfering signals due to coeluted species. The similarity of the obtained SMS with the one in the library is calculated and expressed as a percentage. A signal-to-noise ratio (S/N) is calculated for each polymer by extracting a characteristic 

 signal chosen from one of the main pyrolyzates. If the S/N is lower than a set threshold, the presence of the corresponding polymer is excluded, regardless of the similarity index obtained by the algorithm.

Figure 7 demonstrates an example of the identification process of polypropylene (PP) in the reference mixture using the automated F-Search program. The ions at 

Py–GC–MS has advantages for the analysis of environmental microplastic samples compared to other leading analytical methods, including spectroscopic techniques.