In this installment of “GC Connections,” we take a close look at Golay’s famous equation that most people view as relating to height equivalent to a theoretical plate (HETP) to the carrier gas flow rate or average linear gas velocity in a capillary column. We explore the original works of Golay and Keulemans. We also look closely at the original equation, the assumptions involved with its development, and the assumptions (both good and bad) that have been applied to HETP over the years. In part two, we will explore the consequences and relevance of this theory today, with temperature programming, very long (and very short) columns, high pressure drops, and vacuum outlet detectors.

The height equivalent to a theoretical plate (HETP) is one of the most important parameters used to measure column performance. HETP is the length of column required to generate one theoretical plate, with a theoretical plate being one transfer process of an analyte molecule between the mobile phase and the stationary phase. We are all familiar with considering the number of theoretical plates in a column or the number of theoretical plates in a length of column, as these are often stated by column vendors as a measure of column quality. More theoretical plates and more theoretical plates per meter are often considered good, leading to better resolution. A 30-m column with 100,000 theoretical plates is said to have 3333 theoretical plates per meter.

We use a chromatogram to measure theoretical plates (as shown in Figure 1), using equation 1, where 

 and HETP (as discussed later) are dependent on many parameters, including temperature, carrier gas flow rate, inlet and outlet pressures, column dimensions, and the choice of carrier gas. One challenge in comparing plate numbers between different columns is that the experiments will almost always have been performed under different conditions, making true comparisons difficult.

FIGURE 1: Simple chromatogram showing the classical calculation of 

HETP is then calculated using equation 2, where 

 is the number of theoretical plates calculated using equation 1:

, or HETP, is also defined as the rate of band broadening. As we know, the peaks or bands get wider in all chromatographic techniques as the peaks and bands traverse the length of the column. HETP provides a measure of the rate of the broadening, with a smaller HETP indicating slower band broadening, leading to sharper peaks.

How was HETP as a measure of the rate of band broadening originally defined? This definition goes back to the earliest days of gas chromatography (GC) in the 1950s and the work of A.J.P. Martin and A.T. James, the inventors of GC; J. Van Deemter, who developed the original theory of band broadening for packed columns; Golay, who developed the theory for capillary columns; and Keulemans, who provided a fundamental conceptual definition for a theoretical plate.

Keulemans presented a picture of the separation process in chromatography in a classic text, 

, published in 1959 (1). In the foreword to this short text, A.J.P. Martin described it as “an admirably clear account of all the practical and theoretical aspects of this rapidly growing method.” The clear influence of the text is seen in the highly recognized 1965 text, 

As illustrated in Table I, Keulemans described each theoretical plate as a liquid–liquid extraction between immiscible solvents. Starting with a flask containing a solution of an analyte dissolved in a solvent, say, water. The solution is mixed with an equal volume of hexane. If the partition coefficient is 1, then equal masses of solute are present in each phase. The hexane layer is then removed and mixed with an equal volume of water in a second flask and fresh hexane is added to the first flask. Each flask now contains half of the original analyte, equally distributed between the two phases. This process can be repeated with a third, fourth, fifth, and up to any number of flasks, ultimately resulting in a distribution of analyte among all the flasks (seen in Table I), calculated for 10 flask theoretical plates, 10,000 molecules, and a distribution constant between the two phases of one.

The numbers in Table I represent the number of molecules out of the 10,000 in each flask or theoretical plate. We can note immediately that as the number of flasks increases, the number of molecules in each flask decreases, analogous to the chromatographic peak becoming broader and shorter. Also note that there are still some molecules in the initial flask, even after ten extractions, an often-unappreciated consequence of chemical equilibrium: There are always some molecules left behind.

The description provided above makes several assumptions that, although illustrative of the chromatographic process, do not account for all processes that occur in real columns. First, it assumes that each theoretical plate occurs independently and has no direct contact with the other theoretical plates. Obviously in a column with a mobile phase, this assumption cannot be true because the mobile phase is continuously transporting solutes along the column. Second, it assumes that there are no barriers to mass transfer at the phase interfaces. In a real system, of course, the kinetics of mass transfer across the phase interfaces must be considered. Finally, there is no consideration of diffusion both within and between the two phases. In a column, the solute molecules distribute throughout the mobile and stationary phases. Golay’s equation, described below, uses a description of the chromatographic process like Keulemans, and accounts for these assumptions, plus the dimensions and physical conditions observed within columns.

Golay provided a thorough description of an equation describing the rate of band broadening in the proceedings of the “Gas Chromatography 1958” symposium organized by the Hydrocarbon Research Group of the Institute of Petroleum and the Koninkiljke Nederlandse Chemische Vreniging in Amsterdam, the Netherlands, in May 1958. The symposium volume was published in 1959, edited by Desty (3). The equation for circular capillary columns is presented as equation 3:

Note that Golay also described a similar equation for rectangular capillaries. At the time, there was considerable discussion about which would be better, and clearly circular capillaries have become far more popular. Interestingly, with recent interest in columns etched into silicon wafers for “laboratory on a chip” applications, rectangular capillaries are increasing in usage and importance. This equation is popularly called the “Golay Equation,” but it combines the work of many early researchers in chromatography.

Definitions of the many variables are discussed in the “deeper dive” below. Interestingly, the proceedings volume includes commentary following the formal text of the talk, in which substantive discussion among the symposium participants was captured. The names of those participating in that discussion read like an all-star lineup of modern chromatography inventors, including Golay, A.J.P. Martin, R.P.W. Scott, I.G. McWilliam, and others. It was traditional in the past to assign scribes to record the discussions. In one especially important exchange between Golay and Martin, they appear to agree, possibly begrudgingly, to use the definition of HETP presented by Keulemans and illustrated above (4).

In the original work, several related forms of the equation are presented, relating to specific situations that may occur in the making of capillary columns; the form used here is equation 31a from that work, chosen for simplicity in discussing the basic principles and consequences.

The first thing to note is that this is a differential equation relating to 

, a differential of length or distance. The terms enclosed in the parentheses provide what we term as HETP or 

, the height equivalent to a theoretical plate, so the equation could be conceptually simplified to equation 4. Interestingly, similar to the Keulemans description, the independent variable is the length of the column (

), as the differential is distance and the dependent variable is the peak width, represented by the differential of the second statistical moment (

Equation 4 shows us that the rate of band broadening as the band traverses the column is equal to HETP. As we have learned in short courses and textbooks, smaller HETP means a slower rate of band broadening and sharper peaks. In many textbooks and courses, the terms within the parentheses in equation 3 are simplified to the form shown in equation 5. As we will see in Part 2 next month, equation 5 is an oversimplification that can generate confusion and possibly lead to false directions in method development and optimization.

Note the average velocity of carrier gas (

) is usually chosen as the independent variable in equations 4 and 5, leading to the “van Deemter” or “Golay” plots often seen in discussions of column performance in the scientific literature. The three terms are often described as representing analyte diffusion in the mobile phase (the “

” term), analyte diffusion in the stationary phase (the “

” term) and analyte diffusion in the mobile phase (the “

” term). In developing equation 3, Golay noted the similarity in form to the equation of van Deemter, developed a few years earlier.

Whether we perform detailed calculations based on it or not, equation 3 provides a very useful description of the many variables and processes relating to band broadening and ultimately to peak widths and resolution. Some important general principles are discussed here; for a detailed description of all variables and how they are used to evaluate column performance, see these book chapters or the discussion in ChromAcademy, 

’s online chromatography learning platform (5–7). In short, to minimize HETP, the quantities in parentheses in equation 3 should be minimized.

In the first term within the parentheses, often called the “

” term using the terminology in equation 5, diffusion in the mobile phase is considered. The numerator, 

, is the diffusion coefficient of an analyte molecule in the gas phase, which for simplicity, can be considered a constant for that analyte at a given temperature in a given carrier gas. Diffusion coefficients in the gas phase are mainly dependent on the identity of the analyte, the solvent gas, and the temperature. The denominator is the average carrier gas velocity in the column. Not surprisingly, this suggests an inverse relationship between HETP and average carrier gas velocity.

, relates to mass transfer, also in the mobile phase and is the major difference between Golay’s equation for capillary columns and the original van Deemter equation for packed columns. Capillary columns usually have much larger phase ratios (volume of mobile phase divided by volume of stationary phase) than packed columns, so mass transfer in the mobile phase becomes important. Note that in this term, the same diffusion coefficient described above is now in the denominator and the average carrier gas velocity (

) is in the numerator, suggesting a proportional (linear) relationship between HETP and carrier gas velocity.

 term include the square of the column radius, 

, and a complex polynomial of the retention factor (

). Note that all of the variables, except for the column radius are temperature dependent and that the retention factor is also related to the column dimensions and average linear gas velocity.

, relates to mass transfer in the stationary phase. Like the 

 term is linear with the average carrier gas velocity and the square of the column radius (

 term, the denominator includes a diffusion coefficient, this time in the liquid phase, which depends on the specific analyte, liquid phase and temperature. Additionally, the analyte partition coefficient (

) into the liquid phase is part of the denominator. The term also includes a polynomial function of the retention factor (

Taken together, the three terms of the expression describing HETP, as presented by Golay, have numerous dependencies, and many of the variables that make up the equation have their own dependencies. The column radius is fixed and appears in two of the three terms. All the other variables are dependent on temperature. The average carrier gas velocity is dependent on the choice of carrier gas, the column dimensions (length and inside diameter), and temperature. The partition coefficient depends on the chemical nature of the analyte and stationary phase and the retention factor depends on the partition coefficient, column phase ratio and is further related to the average carrier gas velocity.

In our next installment, we will examine these dependences and the assumptions upon which our traditional view of HETP, based on the “Golay Equation,” are founded. We will also discuss their relevance in today’s capillary GC The major changes between thinking about GC from the 1950s when these ideas were developed and today include: the nearly universal use of temperature programming, smaller diameter capillary columns, thinner stationary phase films, and high vacuum column outlets, as seen in GC–mass spectrometry (MS). We will see that many of the traditional views that we were all taught (and still teach) about HETP, peak broadening and peak widths in gas chromatography deserve some new thinking.

 (Reinhold, New York, NY, 1959), pp. 106–139.

(3) M.J.E. Golay, “Theory of Chromatography In Open and Open Tubular Columns With Round and Rectangular Cross Sections,” in D.H. Desty (ed), 

 (Butterworths, London, United Kingdom, 1958), pp. 36–55.

(4) C.S.G. Phillips and F. Sjenitzer, “Discussion: Authors’ Additional Comments,” in D.H. Desty (ed), 

 (Butterworths, London, United Kingdom, 1958), pp. 65–66.

(5) H.M. McNair, J.M. Miller and N.H. Snow, 

 (John Wiley and Sons, Hoboken, NJ, 3rd ed., 2019), pp. 15–36.

(6) L.M. Blumberg, “Theory of Gas Chromatography,” in C.F. Poole (ed), 

 (Elsevier, Amsterdam, The Netherlands, 2nd ed., 2021), pp. 48–67.

(7) “GC Band Broadening”, ChromAcademy, 

’s Online Learning Platform. https://www.chromacademy.com/channels/gc-training-courses/principles/gc-band-broadening/ (accessed December, 2021).

 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: 

Articles

We are all familiar with Golay’s equation relating to height equivalent to a theoretical plate (HETP) in GC. But do we understand it correctly?

Is Golay’s Famous Equation for HETP Still Relevant in Capillary Gas Chromatography? Part 1: A Common View of HETP

The contribution of hops to the bitter flavours in beer is complicated by a number of factors, including the relative concentrations of humulone homologues in hops, the extraction of bittering compounds from hops, and the conversion of humulones to isohumulones during the brewing process. This article describes a rapid liquid chromatography–mass spectroscopy (LC–MS) method using electrospray ionization (ESI) coupled with selective ion monitoring mass spectroscopy (SIM-MS) for the analysis of humulone and isohumulone content in beer. Individual beer samples are monitored directly following filtration and decarbonization. Using multiple injections in a single experimental run (MISER), data were collected in as little as 7 min for each beer sample. Results were displayed as a single “misergram”, which allowed for the convenient analysis of relative concentrations of humulones and isohumulones or hops utilization in sets of in-house brewed beers and commercial samples.

Beer is one of the most popular beverages in the world, and consistently ranks at the top of the list for consumers of alcoholic drinks. Growth of craft breweries and consumer interest in beer flavour has led to a wealth of readily available beer styles and flavours. In 1984, there were fewer than 100 breweries in the United States (1). The most predominant beer and perhaps the only style available at many locations in the United States was North American lager. By 2019, there were over 8000 breweries offering hundreds and hundreds of beer styles, as defined by the Brewer’s Association “Beer Style Guidelines” (2). This surprising variety of beers can be obtained from four basic ingredients: water, malted grain, spices (hops, fruits, and other consumables), and yeast. Control of the ingredients, brewing process, fermentation, packaging, and storage has a significant impact on the consistency of the final product, and also presents a challenge for brewing scientists monitoring the components contributing to the flavours in beer (3).

Beer bitterness derives from using hops during brewing, providing an important flavour balance to the sweet flavours of malts and grains (4). The dried hop cones or strobile used in brewing contain significant amounts of polyketides, particularly the humulones, or α-acids (AA), which can represent 2–15% of the total mass of the hops. The major homologues of the AAs are the co-, n-, and ad-humulones, which collectively account for greater than 98% of the α-acid or AA content. (5). During the brewing process, the AAs are isomerized to the more water-soluble isohumulones, or iso-α-acids (IAA), via an acyloin rearrangement with ring contraction (Figure 1). Beer bitterness is often described in terms of international bittering units (IBU), with a scale ranging from values of 5 to 100 (6). With the advent of craft brewing and very hoppy beers, some extremely high values of IBU have been claimed. The IBU numeric value has been suggested as approximately equivalent to the concentration of isohumulones in beer in parts per million (ppm). However, actual sensory beer bitterness is more complex and depends on the concentrations of a number of potential bittering agents (7–9).

The combination of extraction of humulones AA from hops and conversion to IAA during brewing is described as 

. Predicted values of IBU can be determined by calculating the amount of hops, percent AA content, volume of the wort, sugar concentration, and time of hop addition (10). This is particularly important for design and implementation of new beer recipes. The traditional method of analysis of beer bitterness relies on the spectrophotometric UV determination of IAA content of an organic extract of beer at 275 nm (11,12). A disadvantage of the spectrophotometric method is the inability to separate absorption of IAA from interfering components that absorb in the same region of 275 nm, but do not exhibit the same contribution to beer bitterness. The growth of the craft beer industry has led to a marked increase in strongly hopped and flavoured beers, resulting in significant changes in the absorption profile of organic extracts of beer. Late- or dry-hopped beers, in which hops are added at the end of the boiling process or after primary fermentation, result in higher concentrations of humulone AA and related oxidized products. Their contribution to UV absorption can result in unexpectedly high values of IBU by the spectroscopic method. Complete analytical separation of all the homologues and isomers of IAA has been achieved by high performance liquid chromatography (HPLC) with UV detection (13–16) and by liquid chromatography–mass spectroscopy (LC–MS) (17,18).

We recently introduced a rapid LC–MS method for determining the AA and IAA content in commercial beer samples using selective ion monitoring (SIM) (19). By employing multiple injections in a single experimental run (MISER), we were able to analyze 70 different beer samples in a total of 74 min. The single misergram allows facile comparison of the relative concentrations of AA and IAA in the beer samples in a single chromatographic display (20,21). MISER analysis has been used in our introductory course at the University of Missouri–St. Louis, “Beer Brewing: Chemical and Biochemical Principles” (22). In this report, we take advantage of a set of beers prepared in our beer brewing course to analyze hops utilization determinants of IBU and measure beer bitterness components. Knowledge of the individual brewing recipes allowed direct comparison of predicted IBU from hops additions, measurement of IBU by spectroscopic analysis, and final determination of the concentration of AA and IAA by SIM LC–MS in the finished beer samples. A sample set of commercial beers from a local brewery are also compared for content of AA and IAA.

 Methanol and acetonitrile (HPLC-grade) were purchased from Fisher Scientific. Ammonium formate (NH4HCO2) and formic acid (HCOOH) were purchased from Sigma–Aldrich. Ultrapure water was obtained from a Milli-Q Integral 10 from Millipore. Standards ICS-3 (dicyclohexylamine salts of trans-iso-α-acids) and ICE-3 (hops extract standard) were obtained from the American Society of Brewing Chemists (ASBC Check Sample Service; asbc@scisoc.org).

Unhopped beer, used for preparation of standard solutions, was prepared by addition of 225 g of dry malt extract (DME) to 1 L of boiling water. The mixture held at a boil for 15 min, the hot wort cooled in an ice water bath and subsequently transferred to a 4 L glass fer­mentation bottle equipped with an air lock. To this mixture, 5 mg of dry yeast (Safale-05) was added. After one week, the beer was transferred to a clean, sanitized 4 L glass fermentation bottle equipped with an air lock. After an additional two weeks, the unhopped beer was transferred to standard beer bottles, capped, and stored in a refrigerator at 4 °C. Humulone and isohumulone standards were prepared by dissolving a suitable amount of AA or IAA in a minimum amount of ethanol and diluted with unhopped beer to provide standard solutions of 5, 10, 25, and 50 ppm.

 Beer samples were collected immediately upon opening the specific bottle of carbonated beer. Several millilitres were transferred via gravity filtration through Whatman qualitative P8 filter paper into a 15 mL plastic centrifuge tube. Samples were capped, frozen, and stored for several days. Aliquots of the thawed samples were transferred into HPLC analytical vials for placement in the LC–MS autosampler. Samples were analyzed directly without dilution. Standard solutions of known concentration of humulone and isohumulone were prepared in unhopped beer.

 MISER LC–MS experiments were performed on a Shimadzu LC–MS-2010A equipped with two LC-20AD mobile phase pumps and a SIL-10AD autosampler. The mass spectrometer was operated in electrospray (ESI) negative mode with capillary voltage of 1250 V. SIM was conducted to continuously monitor ions at 347 and 361 

, corresponding to the deprotonated molecular ions of the AA and IAA homologues. The source and desolvation temperatures were 275 and 250 °C, respectively. Nitrogen nebulizing and drying gas flow rates were optimized at 1.5 L/min and 0.1 MPa, respectively.

Chromatographic separation of AA and IAA was achieved using isocratic conditions with an Agilent Poroshell 120 EC-C18 HPLC column having dimensions of 30 mm × 2.1 mm i.d. and 2.7 µm particle stationary phase. Mobile phase consisted of an isocratic mixture of 2 mM ammonium formate (HCOONH4) in 1:1 acetonitrile–water with a flow rate of 0.20 mL/min. MISER experiments were performed using sequential 5 μL injection volumes for each beer sample at intervals of 5–7 min.

Students in our introductory science course on beer brewing (22) have been preparing small batches of beer using recipes developed in class (Table 1). Over two semesters with 40 students, we brewed 13 different recipes. Students worked in pairs and some teams chose identical recipes. We obtained a wide range of beer styles from very light ales (2A, 5A, 7A, and 12A) to dark stouts and porters (4A, 8A, and 9A).

The hop addition sequence is very dependent on the specific recipe. Timing of hops addition during brewing and the amount added has a significant impact on the sensory taste profile of the final beer. Hops added at the beginning of the boil contribute to beer bitterness and undergo comparatively significant conversion from AA to IAA. Additions of hops near the end of the boil contribute to flavour and aroma, but have less impact on beer bitterness because of low levels of conversion of AA to IAA. The sugar concentration of the wort (boil gravity) also has an impact on extraction of AA, with higher sugar concentration resulting in less incorporation of bittering components. Hops utilization can be modelled as a function of boil time and wort boil gravity and used to calculate IBU for specific recipes. The calculated IBU value was determined using the Tinseth method from published utilization tables and free online homebrew calculators (10,23,24).

Values of IBU were determined using the industry standard spectroscopic method (11,12). Absorption of an isooctane extract of acidified, decarbonated beer at 275 nm can be related directly to IBU. For a number of the beer samples, the spectroscopic IBU showed significant deviation from the calculated value. This is not unexpected—variations can occur because of age and storage of the hops as well as deviations from the brewing process. Aged or improperly stored hops can result in higher concentrations of oxidized products, such as humulinones, that can contribute both to higher UV absorbance of the isooctane extract and higher perceived bitterness in the beer (25). Four of the beer samples, English brown ale, weissbier, imperial IPA, and porter (1A, 2A, 3A, and 9A), exhibited significantly higher spectroscopic IBU measurements compared to the calculated values. The imperial India pale ale (IPA) showed the greatest UV absorption, resulting in an IBU of 120 compared to the calculated value of 48. The solubility of IAA in beer is dependent on the concentrations of sugars and pH but limited to approximately 100 ppm (26). In the case of beer 3A, the unusually high absorbance and IBU value indicate the presence of additional UV absorbent compounds.

Analysis of the beer samples by LC–MS was achieved using MISER. This provides visualization of all of the beer samples in one chromatographic output or “misergram” (20,21). The beer samples were filtered, degassed, and added to sample vials for direct injection and analysis by LC–MS (Figure 2). A single 120 min misergram of beer samples 1A–13A along with IAA and AA standards was obtained using SIM in negative ion mode at 361 

. It is worth noting that the chromatographic conditions employing a short column and strongly eluting mobile phase result in the coelution of the homologues co-humulone (MW 348), ad-, and n-humulones (MW 362). However, the isomeric AA and IAA are well resolved because of their inherently different physical properties. Therefore, we observe a single chromatographic peak for the homologues of IAA and a second more retained peak for the homologues of AA. The misergrams obtained from either set of negative parent ions (SIM at 347 or 361 

) are very similar in profile and useful for qualitative assessment of relative amounts of IAA and AA. The misergram is divided into 7-min intervals, with vertical hash marks differentiating the results for each beer sample. The IPA (11A) contains the greatest amount of IAA, while light ales 5A and 12A contain the least IAA. These chromatograms are also useful for assessing the utilization of hops or conversion of AA to IAA. Imperial IPA (3A) and English Porter (9A) show low levels of utilization, as reflected by greater residual amounts of AA. Both of these recipes (3A and 9A) included late hops additions during the boil, which would be expected to result in higher concentrations of un‑isomerized AA. Quantitation of AA and IAA in each beer sample was determined by combined content of the individual homologues of co-, ad-, and n-humulones and isohumlones, respectively. Comparison of each beer sample was made to the standard curves obtained from commercial samples of IAA and AA in unhopped beer, as shown in Figure 3. For instance, the total concentration of AA was obtained by the sum of the ppm concentrations of cohumulone (MW 348) and n-ad-humulone (MW 362) obtained from two separate LC–MS chromatograms. The content of all homologues of AA and IAA was obtained for each beer style using the summation of the concentrations in ppm obtained from two misergram plots using SIM of 347 and 361 

A set of beers was also collected from a local brewery for evaluation using MISER LC–MS (Figure 4). The sample set included a range of products from a lemon shandy prepared from a light lager and lemon soda (2B) to the more bitter pilsners (6B and 7B), double IPA (8B), and American IPA (9B). From this small set of nine beers, the American IPA (9B) shows the greatest amount of AA, as evidenced by the second peak (blue).

A comparison of peak heights of AA and IAA at 361 

 in the MISER chromatograms (Figure 2 and 4) can also be displayed as a single scatter plot (Figure 5). This analysis is qualitative in nature because we are comparing peak heights rather than integration values and only the co- and n-IAA and AA at 361 

 are displayed. However, the scatter plot provides useful visualization of two important aspects: 1) relative amounts of AA and IAA in different samples, and 2) ratios of AA/IAA in a single sample. Similar beer styles also appear as clusters that can help identify features of particular recipes. For example, commercial weissbeer (1B) and lemon shandy (2B), known to have low bitterness and very little hops aroma, appear in the lower left-hand corner of the plot. A number of student beers (weissbeer 2A, lampo bianco 5A, cream ale 7A, and cherry ale 12A) were also characterized by low bitterness and hops aroma, appearing in the same general area of the scatter plot. Using this scatter plot from both the student and commercial samples provides a comparison between our classroom recipes and standard beer styles.

The results of this investigation illustrate the utility of using multiple injections in a single chromatogram MISER coupled with single ion monitoring LC–MS to obtain graphical, qualitative analysis of humulones/isohumulones ratios (AA/IAA) in sample sets of beers. By comparison to standard curves obtained at both 347 and 361 

, it is possible to determine concentrations of the combined homologues of AA and IAA. The technique is rapid, allowing analysis of large sample sets with a minimum of sample preparation. A simple decarbonation and filtration is all that is required prior to transfer to HPLC sample vials. The method is also useful for monitoring the brewing process and hops utilization during the boiling of the wort. Components that interfere with the traditional UV spectroscopic determination of IBU are largely eliminated by SIM and chromatographic separation. The ability to view both AA and IAA concentrations allows direct comparison of hops utilization and the sequence of hops additions in beer brewing recipes.

We are grateful to the students who participated and prepared beer samples in the University of Missouri–St. Louis course, “Beer Brewing: Chemical & Biochemical Principles” (CHEM 1021). This three credit hour course is specifically designed to fulfill the Life/Natural Sciences requirement of undergraduate degrees in the College of Arts and Sciences.

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. https://www.brewersassociation.org/edu/brewers-association-beer-style-guidelines/

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 (Elsevier, Amsterdam, The Netherlands, 2010), pp. 967–997.

For the Love of Hops: The Practical Guide to Aroma, Bitterness and the Culture of Hops

 (Brewers Publications: Boulder, Colorado, USA, 2012).

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, T.H. Shellhammer, Ed. (ASBC/MBAA, Saint Paul, Minnesota, USA, 2009), pp. 157–166.

C.D. Hahn, S.R. LaFontaine, C.B. Pereira, et al., 

 (Brewers Publications, Boulder, Colorado, USA, 2017), the first edition is available free online: http://www.howtobrew.com (accessed Feb 2021).

Beer-23: Beer Bitterness, in ASBC Methods of Analysis

, 14th edition (American Society of Brewing Chemists, St. Paul, Minnesota, USA, 2016).

S. Schneider, Agilent Application Note: On-Site Quality Control of Beer, 2016. https://www.agilent.com/cs/library/applications/5991-3510EN.pdf

A. Khatib, H.K. Kim, E.G. Wilson, et al., 

G. Vanhoenacker, D. DeKeukeleire, and P. Sandra, 

L. Ceslova, M. Holcapek, M, Fidler,et al., 

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Brewing Science: A Multidisciplinary Approach

 (Springer, Cham, Switzerland, 2017), pp. 252–255.

Bruce C. Hamper, Nicholas Viriyasiri, Aaron Boland, Lorna Espinosa, Hunter J. Campbell, and 

 are with the Department of Chemistry and Biochemistry at the University of Missouri–St. Louis in St. Louis, Missouri, USA.

 is with the Urban Chestnut Brewing Company in St. Louis, Missouri, USA.

A rapid LC–MS method using ESI coupled with SIM-MS for analysis of humulone and isohumulone content in beer is described.

Liquid Chromatography–Mass Spectrometry Analysis of Hop-Derived Humulone and Isohumulone Constituents in Beer:  The Bitter Truth of Hops Utilization During Brewing

Monoclonal antibodies (mAbs) dominate the pipelines in the biopharmaceutical industry today. Being complex products, this class of molecules has numerous critical quality attributes (CQAs). Their thorough characterization is a necessary and critical component of biopharmaceutical product development. One CQA is size-based heterogeneity. Aggregates are widely considered a CQA because of their likely impact on the immunogenicity of the product. There is no single analytical tool that can accurately characterize aggregates because of the significant diversity that they exhibit with respect to size, structure, and morphology. As a result, it is common practice to use multiple, orthogonal analytical tools for aggregate characterization. This article reviews efforts targeting the use of two-dimensional liquid chromatography (2D-LC) and mass spectrometry (MS) for aggregate characterization.

Two-dimensional liquid chromatography (2D-LC) is a technique that is capable of resolving heterogeneity of a biological sample via using two different LC columns, each corresponding to a different separation mechanism. The concept of 2D-LC has been around since 1944, when separation of amino acids was performed using a thin cellulose sheet and applying two different solvents, one after another, in different directions (1). This 2D-LC workflow was offline and tedious. Various coupling strategies have been conceptualized thereafter along with major developments in hardware, where first dimensional eluents are selectively transferred to the second dimension for separation of heterogeneous molecules within a single time frame (2). Advanced 2D-LC allows online analysis of samples without the need for in-between manual intervention, subsequently reducing offline workflow drawbacks including buffer exchange, sample loss, and contamination (3). General instrumentation of 2D-LC involves using an autosampler with binary or quaternary pumps, switching valves, two column compartments, and two diode array detectors (DADs) (Figure 1). The principle of 2D-LC is mainly based on a set of pumps and loop-valves present in-between the two chromatographic chambers, which collect and store the analyzed peak from the first dimension and subsequently transfer it to the second dimension. For inline analysis of 2D-LC, peaks can further be identified or characterized using mass spectrometry (MS) (4). The biopharmaceutical market as of 2021 occupies approximately 400 billion USD of the global market share and is further expected to grow annually at the rate of 7% (5).

FIGURE 1: General instrumentation of 2D-LC coupling with MS.

Monoclonal antibodies (mAbs) are the fastest growing therapeutics in the pharmaceutical industry and constitute a major portion of the biopharmaceutical market (6). These products are known to be complex and have numerous critical quality attributes (CQAs) that are known to impact the product’s safety and efficacy. As a result, the manufacturer is expected to closely monitor these during their production and distribution and have suitable process controls in place to ensure that the final product has consistent quality. One of these many CQAs is the size-based heterogeneity of aggregates. These are particularly difficult to analyze as they vary in size (from dimer to visible particles), morphology, and structure. As a result, no single analytical technique is sufficient for their accurate characterization. The typical approach that the manufacturer takes is to use multiple, orthogonal, high-resolution analytical methods for characterization and monitoring of protein aggregates. In light of these challenges, 2D-LC coupled with MS offers potential for this application (7,8).

In this article, we review the different approaches and coupling strategies that have been used to analyze aggregates through 2D-LC. One of the earliest applications of 2D-LC for aggregate analysis is that for antibody drug conjugates (ADCs) (9). Because the structure of ADCs is more complex and heterogeneous than that of corresponding antibodies (10), there is a need for newer characterization approaches to supplement the traditionally used, labor-intensive, and time-consuming analytical approaches like competition enzyme-linked immunosorbent assay (ELISA) (11), reversed-phase (RP) high performance liquid chromatography (HPLC) (12), protein precipitation, and solid-phase extraction (SPE) assay (13). By accessing 2D-LC technology, size exclusion chromatography (SEC) in the first dimension and RP in the second dimension, researchers have successfully analyzed the size-based heterogeneity, along with the conjugation and formulation of unconjugated small molecule drugs (14). MS detectors have also been successfully used to identify small molecular species, thereby elucidating the degradation pathways of the ADCs as well as to study the stability of an ADC at different temperatures and formulation pHs (15). Although SEC in the first dimension characterized the ADC aggregates, RP-HPLC in the second dimension differentiated the small molecular degradation products (16). Researchers had successfully identified the major degradation pathways associated with drug antibody maleimide functional group linker by 2D SEC-RP association (17).

The two most commonly used 2D-LC fractionation modes to analyze aggregates are comprehensive mode and the heart-cutting approach (18). The 

 represents constant cutting of the first-dimension eluent followed by transfer to the second-dimension to obtain a wide-ranging sample profile. In contrast, the 

 selects the specific peak of interest and transfers that particular peak to the second dimension. Hence, the heart-cutting mode has been reported to be more suitable for the separation different size variants in mAbs (19).

Aggregates have also been examined in analyzing harvested cell culture impurities while keeping SEC in the second dimension. Protein-A (ProA) has often been used in the first dimension to facilitate mAb capture from a myriad of species in the harvest, which is followed by SEC in the second dimension for aggregate characterization in the second dimension (20). The 2D ProA-SEC platform has also been demonstrated to successfully estimate the titer as well as the percent aggregation in a relatively short time (4.5 min) of analysis (21). However, it has also been reported that lower pH mobile phase of ProA columns reduces the recovery rate of aggregates while passing through the SEC column in the second dimension (22). Therefore, 2D ProA- SEC affords an oblique measurement to identify relative amounts of aggregates in different isolated areas of the ProA peak. Hence, in the ProA-SEC chromatogram, the first peak contains undesirable impurities of harvested samples, whereas the main peak contains protein aggregates including monomer and fragments thereafter (23). Thus, the 2D ProA-SEC sequence affords an oblique measurement to identify relative amounts of aggregates in different isolated areas of the ProA peak. Researchers have also used 2D-LC to estimate high and low molecular weight size variants using SEC-multiangle light scattering (MALS) along with charge variants in the first dimension (24).

A challenging task for researchers attempting to link size and charge based heterogeneities is that the process of isolating each charge variant is quite rigorous, time consuming, and laborious (25). 2D-LC offers a solution to this conundrum via use of complementary modes such as ion exchange chromatography (IEC) and SEC in the two dimensions (26). Although anion exchange chromatography (AEX)-SEC has been used to investigate aggregation of acidic variants (27), cation exchange chromatography (CEX)–SEC has been used to examine aggregation of basic variants (28,29).

Researchers have also attempted to improve recovery of aggregates in mAbs by using a novel hydrophobic capture phase as the injection loop in 2D-LC (30). A polyester capillary-channeled polymer (C-CP) fiber was used as a hydrophobic chromatography (HIC) capture phase and placed in between the protein A and size exclusion compartments, functioning with the heart cutting mode. The study revealed that the particular loop could enable higher recovery of aggregates (31). The ProA-HIC-SEC method has been proposed for testing the cell culture harvest in less than 10 min (32). Thus, the concept of fraction collection loop is quite successful for 2D-LC based analysis of aggregates and researchers are attempting to deliver high permeability and rapid solid-solution mass transfer characteristics of the HIC phase.

To analyze soluble aggregates, researchers have used SEC-IEX hyphenated with native MS (nMS) (33). The resulting SEC-IEX-UV-nMS offered detection via UV absorbance and mass detection in a single method. This approach has been successfully applied for analyzing a significant spectrum of biologics and biotherapeutics, to separate growth hormones, oligomer state distributions of liraglutides in solutions with different pHs (34), and native states of homodimers and heterodimers of force stressed studies of mAb mixtures (35). Researchers have indicated that by applying an external isocratic flow pump on a simple binary pump, any binary LC system can be transformed into a simple multi-dimensional analytical tool (35).

Researchers worldwide are showing increased interest in using 2D-LC for characterizing protein aggregates. Table I presents a summary of aggregation studies undertaken for mAbs specifically using SEC. It is evident that SEC in 2D-LC has also been used for excipient analysis during formulation development of mAbs, wherein methods like hydrophilic interaction chromatography (HILIC) and evaporative light scattering detector (ELSD) are usually employed in the second dimension. Researchers around the globe have already started establishing analytical methods of up to three to four dimensions with significantly high resolution. The advantages of 2D-LC are undoubtedly many. The technique can save time and labor, minimize product degradation, reduce manipulation and thus the chances of contamination, ensure product quality, and provide improved method attributes, including sensitivity, selectivity, and resolution. Of course, it is important to point out the challenges that are faced by users of 2D-LC as well. Incompatibility of solvents across two modes used for 2D-LC, higher complexity, more time required for analytical method development, and reproducibility are some of the hurdles that need to be crossed. However, there is no doubt that 2D-LC will continue to offer major developments in the time to come.

(1) R. Consden, A.H. Gordon, and A.J.P. Martin, “Qualitative Analysis of Proteins: A Partition Chromatographic Method Using Paper,” in 

 (Harvard University Press, Cambridge, MA, 2013), pp. 28–30.

(2) J. Camperi, A. Goyon, D. Guillarme, K. Zhang, and C. Stella, 

(3) X. Wang, G. Yan, H. Zheng, M. Gao, and X. Zhang, 

(4) L.S. Roca, A.F. Gargano, and P.J. Schoenmakers, 

(5) C. Wang, D. Wang, J. Abbas, K. Duan, and R. Mubeen, 

(6) D.M. Ecker, S.D. Jones, and H.L. Levine, 

(7) G. Vanhoenacker, I. Vandenheede, F. David, P. Sandra, and K. Sandra, 

(8) D.R. Stoll, “Introduction to Two-Dimensional Liquid Chromatography—Theory and Practice,” in 

Handbook of Advanced Chromatography/Mass Spectrometry Techniques

 (AOCS Press, London, United Kingdom, 2017), pp. 227–286.

(11) S.O. Doronina, B.A. Mendelsohn, T.D. Bovee, C.G. Cerveny, S.C. Alley, D.L. Meyer, et al., 

(13) F. Hudecz, M.C. Garnett, T. Khan, and R.W. Baldwin, 

(14) A. Wakankar, Y. Chen, Y. Gokarn, and F.S. Jacobson, 

(15) M. Alvarez, G. Tremintin, J. Wang, M. Eng, Y.H. Kao, J. Jeong, V.T. Ling, and O.V. Borisov, 

(16) Y. Li, C.D. Medley, K. Zhang, L. Wigman, and N. Chetwyn, 

(17) Y. Li, C. Gu, J. Gruenhagen, K. Zhang, P. Yehl, N.P. Chetwyn, and C.D. Medley, 

(19) Y. Li, D. Hewitt, Y.K. Lentz, J.A. Ji, T.Y. Zhang, and K. Zhang, 

(20) H. Han, Y. Miyoshi, K. Ueno, C. Okamura, Y. Tojo, M. Mita et al., 

(21) A. Williams, E.K. Read, C.D. Agarabi, S. Lute, and K.A. Brorson, 

(22) X. Gjoka, M. Schofield, A. Cvetkovic, and R. Gantier, 

(23) A. Williams, E.K. Read, C.D. Agarabi, S. Lute, and K.A. Brorson, 

(24) C.E. Doneanu, M. Anderson, B.J. Williams, M.A. Lauber, A. Chakraborty, and W. Chen, 

(26) Z. Chen, M. Zeng, S.J. Park, G. Balakrishnan, K. Zhou, D. Pan, and T.K. Das, 

(27) M. Wan and G.Y. Wang, Tanox Inc, U.S. Patent 6,177,548 (2001).

(28) Y. An, S. Verma, Y. Chen, S. Yu, Y. Zhang, S. Kelner, S. Mengisen, D. Richardson, and Z. Chen, 

(3), 1000365 (2017) DOI: 10.4172/2157-7064.1000365.

(29) G. Chen, A. Gerrior, G. Hale, and R. Ghosh, 

(30) L. Wang, H.K. Trang, J. Desai, Z.D. Dunn, D.D. Richardson, and R.K. Marcus, 

(32) M. Lemmerer, A.S. London, A. Panicucci, C. Gutierrez-Vargas, M. Lihon, and P. Dreier, 

(33) Y. Wang, A. Lomakin, S. Kanai, R. Alex, and G.B. Benedek, 

(2), 411–419 (2015). doi: 10.1021/mp500519s.

(34) F. Füssl, K. Cook, K. Scheffler, A. Farrell, S. Mittermayr, and J. Bones, 

(35) M. Jia, O. Mozziconacci, A. Abend, W.P. Wuelfing, and J. Pennington, 

 is a institute post doctorate fellow in the Department of Chemical Engineering, Indian Institute of Technology, Delhi, India.

 is a PhD Research Scholar in the Department of Chemical Engineering at the Indian Institute of Technology in Delhi, India.

 is an Associate Dean of Professional Programs and Graduate Affairs at the College of Science at Northeastern University, in Boston, Massachusetts. He is also the Director of Biotechnology and Informatics, as well as the Director of the Biopharmaceutical Analysis Training Laboratory.

 is a professor in the Department of Chemical Engineering at the Indian Institute of Technology in Delhi, India. Direct correspondence to: 

We review different approaches and coupling strategies for analyzing monoclonal antibody aggregates with 2D-LC.

Two-Dimensional Liquid Chromatography (2D-LC): Analysis of Size-Based Heterogeneities in Monoclonal Antibody–Based Biotherapeutic Products

Given the excitement surrounding the “green rush,” it is worth stepping back to examine the trends and nuances of the cannabis testing environment.

The buzz at the 2021 Cannabis Science Conference in Baltimore was palpable: People of widely disparate backgrounds were excited to address the ever-growing challenges and opportunities afforded by this burgeoning marketplace. The phenomenon known as the “green rush” outpaces all significant analytical market areas. Given all this excitement, it is worth stepping back to examine the overarching trends and nuances of the cannabis testing environment and offer some opinions about the key players and disruptive technologies gaining traction throughout this burgeoning marketplace.

The increased success of cannabis-based medical products is strongly correlated to the relaxation of the previously insurmountable bureaucratic hurdles, as well as humans’ ancient relationship with this pharmacologically active plant. For instance, it is entirely possibly, if not likely that humans crossing the land bridge from Asia into the Western hemisphere, brought cannabis along with them. Today, scientists from various disciplines are exploiting the endocannabinoid system in humans. Academic and governmental institutions, pharmaceutical companies, and the separations community are well into the hunt to utilize the plant’s unique chemistry and its relationship to our biology. To date, roughly one million scientific articles have been published on the topic. Research continues to flourish, aiming for some of the most important target markets in human health.

A few notable factors slowing the progress of cannabis-based medicines are the lack of certified professionals, the lack of harmonized regulations, and the high cost of analytical instrumentation—a frustration we know all too well. Fortunately, chromatography vendors are increasingly focusing on serving the analytical challenges of this burgeoning field—Shimadzu, in my opinion, is the most committed to winning this marketplace. They offer a version of simplified software on their benchtop system, application support, and many consumables to help any laboratory get off the ground. Gaining ground is Agilent, which introduced pesticide, mycotoxin, and potency-testing kits, in July 2020.

PerkinElmer’s most significant advance is owed to Avinash Dalmia, a principal R&D scientist. Dalmia wrote a proprietary dual electrospray and atmospheric pressure chemical ionization (APCI) ion source based method by which cannabis laboratories can analyze the complete California pesticide list using only liquid chromatography–mass spectrometry (LC–MS), eliminating the need for gas chromatography–mass spectrometry (GC–MS) to complete this task. With more companies entering this field, we will undoubtedly see advances in chromatography that suit the needs of the cannabis testing market.

Two other companies worth highlighting are Lucidity Systems and Icon Scientific. They both feature instruments that cost roughly half the “familiar” price. Both claim that the reduced complexity and easy-to-use interface of their systems do not diminish testing expectations. Icon’s ANSER liquid chromatography instrument is fully portable and small enough to put in your carry-on luggage. Lucidity’s Mini LC and GC instruments are half the footprint of typical benchtop units and can be shipped overnight for service.

Others are developing even more affordable systems. Emerging is a class of systems mainly targeting the fast-growing potency testing segment (US $229 million in 2019, with a 21.7% market share and a 17.3% compound annual growth rate), which are on offer for less than five thousand USD. These instruments are sold by GemmaCert, Orange Photonics, Purpl Scientific, and Sage Analytics. The efficacy of many of these instruments may come into question in the increasingly scrutinized cannabis marketplace. However, they are deemed sufficient for many typical applications and likely will always be useful for field testing performed by cultivators and law enforcement groups alike.

Navigating a marketplace as dynamic and often controversial as cannabis testing can be fraught with challenges. I hope this article has helped you under- stand and perhaps appreciate its value to our global community. On a personal note, I believe that the more visible and controversial areas of recreational cannabis unfairly encumber appreciation of the plant’s potential as a whole. This gap in understanding can only obscure the incredible potential of this ancient plant to alleviate human suffering, a gap that analytical chemists can help narrow. Delays in progress reduce the pharmaceutical community’s ability to bring meaningful and lasting changes to improve and prolong human health—a most worthy mission.

 is currently in business development at Restek. Direct correspondence to 

Analyzing Trends of the Cannabis Testing Market

In many industries, the concepts of “smaller,” “faster,” “easier to use,” and “cheaper” are key drivers when developing new technologies. The world of chemical separations is no different. Today, compact chromatographic instrumentation is being implemented in many workflows, as illustrated here through various examples.

The field of compact (or portable) chromatography has been a frequent topic of discussion in the pages of 

 recently, with contributions from our group (1) and others in the field (2–4) over the past 16 months. The broad advantages of miniaturized chromatographic instrumentation include reduced benchtop footprint and design simplification in both system operation and software control. Portability, decreased costs for consumables, and a reduction in waste generation can also be achieved, depending on the specific system. Ideally, the systems will achieve performance that matches or exceeds conventional benchtop equipment, although this can be difficult to accomplish while maintaining a small size and low cost. Our approach to implementing these compact chromatographic instruments in our research program has been through the practical approach of identifying areas in which simplified analytical tools can fill a particular need currently underserved by standard measurement strategies.

James P. Grinias, Associate Professor of Chemistry, Rowan University

One of these areas is related to point-of-care (POC) monitoring in clinical settings. We are specifically interested in improving the capability of healthcare professionals to test for recent drug usage, as this can aid in selecting an appropriate course of treatment. In POC settings, this testing is most often achieved by using lateral flow immunoassays to screen urine samples for drugs of abuse (5). Although this strategy can typically identify the presence of specific drug classes, it often suffers from cross-reactivity within a given class, making it hard to identify which specific compounds may be in a patient’s system. For broad drug classes, such as benzodiazepines, having this additional information may require chromatographic-based testing at an external laboratory facility, which can delay results for several days. Identifying the presence of these compounds has become increasingly relevant in drug screening, as overdose deaths attributed to combinations of opioids and benzodiazepines increased tenfold from 1999 to 2017 (6). In Figure 1a, an early result in the development of a rapid, liquid chromatography (LC)-based assay for measuring various benzodiazepines using portable instrumentation is shown. Analyte concentrations for this sample were in the 5–10 ppm range, which is approximately 20- to 30-fold higher than the cutoff level concentration required for screening. Here, an on-capillary light-emitting diode-ultraviolet (LED-UV) detector was used, so the absorbance pathlength was limited to 0.150 mm, which is much shorter than a typical flow cell in a benchtop instrument. This value can be increased by using slightly larger i.d. columns coupled to the on-column detector, or integrating a low-volume, post-column flow cell, both of which are being investigated. Furthermore, sample preparation techniques such as solid-phase extraction can be used to preconcentrate samples and improve detection limits. More-sensitive detection techniques, such as mass spectrometry, can also be used, as shown in Figure 1b. Here, a compact single quadrupole MS system designed for low infusion flow rates can be easily coupled to the column outlet of the portable capillary LC instrument. Selected ion monitoring over targeted retention time windows allows for targeted detection of relevant compounds, along with significant improvements in signal-to-noise for the same sample concentrations. However, adding this second detector increases the size and complexity of the overall system, which may be a hurdle to implementation in certain POC environments. As we continue to develop methods for benzodiazepines and other drug classes using compact LC–UV and LC–MS instrumentation (7), we anticipate that the best techniques require a delicate balance between high performance, high throughput, decreased operation cost, small size, and ease of use for healthcare professionals.

FIGURE 1: (a) Capillary LC–UV, and (b) capillary LC–MS (selected ion chromatograms) showing separations of a benzodiazepine mixture with a 0.150 x 100 mm C18 column (1.7 μm fully porous particles) using Axcend Focus LC and Microsaic MiD-4500. Elution order (as well as concentrations and trace color): flurazepam (10 ppm, black), bromazepam (5 ppm, blue), nitrazepam (10 ppm, green), lorazepam (10 ppm, orange), flunitrazepam (5 ppm, purple), clobazam (5 ppm, gold), and diazepam (5 ppm, pink). 40 nL of sample was injected onto column. Mobile phase consisted of water and acetonitrile (with 0.1% formic acid) with a 25–75%B gradient over 7 min at a 1.5 μL/min flow rate.

As our department houses a PhD in Pharmaceutical Chemistry program, our research group also has an interest in pharmaceutically relevant chromatography applications. Recent work has focused on the development of higher throughput approaches to monograph-based separations of over-the-counter (OTC) analgesic drugs (8,9). These techniques showed reductions in both method cycle time and sample waste generation compared to the monograph methods. Although this approach demonstrates the power of modern chromatographic technology, the implementation of these strategies in manufacturing workflows can be difficult due to the use of higher performing ultrahigh-performance liquid chromatography (UHPLC) instrumentation. The production facilities where these large-batch OTC compounds are generated typically rely on methods with 4.6 mm i.d. columns operated on standard HPLC instrumentation, as significant changes to existing methods sometimes requires extensive regulatory paperwork. In these instances, updated compact instrumentation can achieve similar performance to existing commercial instrumentation, but with reductions in overall size and cost. In Figure 2, a miniLC system was used for a combined drug product content and impurity assay for ibuprofen, using conditions based upon a published monograph method (10). As most published monograph methods for OTC compounds were designed for use with similar columns on instruments with comparable capabilities, many pharmacopeial separations could be easily translated to this lower-cost platform. We have only recently begun exploring the use of this platform, and we anticipate it may be useful in a number of other LC applications in our laboratory, including those related to cannabinoid potency testing as part of our department’s new Cannabinoid Chemistry certificate program.

FIGURE 2: Separation of ibuprofen, valerophenone (internal standard), and an ibuprofen-related compound C using a Lucidity miniLC. Per published monograph (10), concentrations were 12 mg/mL, 0.35 mg/mL, and 0.012 mg/mL, respectively. A 4.6 x 100 mm C18 column was operated at 1.5 mL/min for the isocratic separation, using 40:60 water:acetonitrile (+0.4% chloroacetic acid) and a 5 μL injection volume.

A similar miniGC system has also been released, which we are working toward implementing in our ongoing collaboration with the Department of Health & Exercise Science at Rowan University. Various research projects in this school focus on tracking plasma free fatty acid (FFA) levels in patients over time, as specific compounds can often be used as a marker of nutritional intake of specific lipids (11). Typically, samples are collected and sent to off-site testing facilities for FFA profiling by GC–MS following fatty acid methyl ester (FAME) derivatization of the extracted samples.

To save time and money for these measurements, which can both be limited resources in academic research settings, we are developing a GC-flame ionization detector (FID) method with the miniGC system. Preliminary results on a set of five FAME standards are shown in Figure 3. Although MS has advantages over FID in terms of sensitivity and mass identification, the added detector size can make it difficult to implement directly in clinical research spaces, similar to the aforementioned POC environments. To achieve the benefits of both approaches, collected samples can be tested twice: once with the miniGC system directly after the sample is obtained for rapid preliminary screening and later with more routine GC–MS methods in a testing laboratory for confirmation of results. As with the miniLC system, this is one of several areas in which we anticipate using the compact GC instrument, and it is likely that both will also be integrated into our undergraduate curriculum as part of our analytical laboratory activities.

FIGURE 3: Separation of five fatty acid methyl esters (labeled with free fatty acid designation) using a Lucidity miniGC. Compounds were each 1 ppm, with 4 μL injection and 5:1 split ratio. A 30 m Restek MXT-5 column (0.250 mm i.d., 0.25 μm film thickness) was used with a 120–280 

C/min (helium carrier gas, 2 mL/min, 2 min hold at initial and final temperature).

These projects utilizing various compact chromatographic instruments provide just a few examples of ways that such systems can be implemented. There are many applications related to environmental analysis, manufacturing process monitoring, health screening, food and beverage analysis, and more that are being developed on both the systems described here and other small LC, GC, and capillary electrophoresis (CE) instruments that are also in development or already commercially available. Portable and compact spectroscopic devices have advanced tremendously over the past few decades (12), and the potential for the separation science community to pursue a similar path in coming years is becoming increasingly more viable as miniaturized technology continues to advance.

We are grateful to Prof. Dylan Klein (Rowan University) and the teams at Axcend and Lucidity for ongoing collaborations related to the various projects described here.

(5) Substance Abuse and Mental Health Services Administration, 

Clinical Drug Testing in Primary Care. Technical Assistance Publication (TAP) 32. HHS Publication No. (SMA) 12-4668.

(6) National Institute on Drug Abuse, Overdose Death Rates (2021). <https://www.drugabuse.gov/drug-topics/trends-statistics/overdose-death-rates>

(8) G.A. Kresge, J.-M.T. Wong, M. De Pra, F. Steiner, and J.P. Grinias, 

(10) United States Pharmacopeial Convention, 

(12) R. Crocombe, P. Leary, and B. Kammrath, 

 are with the Department of Chemistry & Biochemistry at Rowan University, in Glassboro, New Jersey. Direct correspondence to: 

Compact instrumentation offers important advantages for many workflows, as illustrated by these examples.