Advances in Small Molecule Analysis

 New Adventures in GC–IMS for Nontargeted Screening of Food and Environmental Samples

Essentials of LC Troubleshooting, Part III

Characterizing RNA Modifications in Small-Volume Samples and Single Cells

 Sample Preparation Strategies 

A Tool for Lipid Characterization of HepG2 Cells

SFC Coupled with Drift Time Ion Mobility QTOF Mass Spectrometry 

Shimadzu Scientific Instruments recently finalized the purchase of a new two-story building at its headquarters in Columbia, Maryland. With this purchase, the company’s campus will comprise three separate properties.

The new building, which will be used by managerial and operational staff, reflects Shimadzu’s multiyear growth plan. The additional space provides accommodations for the company’s growing team and allows Shimadzu to relocate its mid-Atlantic regional office to its original place at the company’s headquarters. The original buildings will house extended and enhanced laboratory space, including the Innovation Center and the Applications Development Center, along with the marketing department, warehouse, and more.

With renovations currently under way, SSI plans to transition the workforce into the new building by the end of summer 2022.

Articles

Shimadzu Scientific Instruments recently finalized the purchase of a new two-story building at its headquarters in Columbia, Maryland. 

Shimadzu Scientific Instruments to Expand Headquarters Facilities

Verifying system performance is important when using chromatographic instrumentation for analyzing both known and unknown samples. Typically, system suitability tests (SSTs) are used to verify performance, which involves running an established method and comparing the results to pre-established acceptance criteria. As two-dimensional liquid chromatography (2D-LC) becomes used more widely and in regulated laboratory environments, development and implementation of SSTs will be critical for successful routine use of the 2D-LC technique.

Although I have not written in the past about system suitability tests (SSTs) for the “LC Troubleshooting” column, they were mentioned several times in the past by John Dolan, the previous “LC Troubleshooting” columnist. The keyword “system suitability” was used in 11 prior “LC Troubleshooting” articles, which speaks to the importance of SSTs in the routine implementation of conventional one-dimensional liquid chromatography (1D-LC). As discussed by John many times, one benefit of regularly running SSTs is that the test results can provide early indications of a problem that is developing, which can be acted on by troubleshooting and solving the problem before it develops into a full-blown failure and results in instrument down time. However, I am not aware of any prior description of the development of a generic SST for two-dimensional LC (2D-LC) (although some are definitely expressing interest in this [1,2]), which we continue to see move in the direction of regulated laboratories, especially in the pharmaceutical industry. For this installment of LC Troubleshooting, I asked Dr. Yehia Baghdady, a Senior Scientist in Chemical Process Development at Bristol Myers Squibb, to share his experiences so far related to the development and implementation of a SST for routine use of 2D-LC for peak purity checks of small molecule separations in his laboratory. I’m hopeful that sharing these ideas and experiences will kick off a broader conversation around this topic in the community.

One of the most attractive features of 2D-LC in the context of pharmaceutical analysis is the utilization of orthogonal (that is, complementary) selectivities in the first (1D) and second dimension (2D) separations. This feature is particularly valuable for the separation of structurally similar impurities that tend to be coeluted with the main compounds of interest in the pharmaceutical industry, such as active pharmaceutical ingredients (APIs), synthetic intermediates, and starting materials (SMs) (3–6). In these challenging separation scenarios, the peak capacity and resolving power of conventional 1D-LC is often insufficient—even for small molecules where the molecular complexity is lower compared to the challenges encountered in the analysis of large biomolecules.

Despite the recent increased availability of commercial 2D-LC instruments, 2D-LC technology is still not considered to be ready for routine use in quality control (QC) laboratories for small molecule in the same way that 1D-LC is (1). Transferability and robustness across different laboratories have not yet been demonstrated on the global scale, and 2D-LC also requires special hands-on experience, equipment, and software that are not widely available like they are for 1D-LC. Additionally, from a regulatory perspective, one or two independent 1D-LC methods are usually sufficient to provide the data needed to meet the analytical target profile of a small molecule pharmaceutical product. As a result, to the best of our knowledge there are no published articles in the literature providing guidelines about how to develop a periodic 2D-LC system suitability test (SST) capable of ensuring the quality of generated results and triggering early alarms for the need to replace a column or fix the instrument components before running real samples. Having a generic SST in place is important to enable routine use as well as to ensure consistent and desirable performance of 2D-LC as a whole integrated system.

Role of System SSTs for Chromatography Methods

 Chromatography General Chapter <621> provides guidance for the implementation of chromatographic methods in the pharmaceutical industry (7). It states:

“System Suitability Tests are an integral part of gas and liquid chromatographic methods. They are used to verify that the resolution and reproducibility of the chromatographic system are adequate for the analysis to be done. The tests are based on the concept that the equipment, electronics, analytical operations and samples to be analyzed constitute an integral system that can be evaluated as such.”

Usually, analyte mixtures used in SSTs for conventional 1D-LC are designed to contain analytes that can be resolved with good peak shapes and acceptable symmetry or tailing factors (8,9). The situation with 2D-LC is different in the sense that some additional requirements need to be met. At a minimum, the mixture must contain two analytes that are well separated in the first dimension, but it is also helpful to have additional compounds that are both coeluted in the first dimension and separate in the second dimension. The behavior of these particular compounds can be used to evaluate and monitor the performance of both separation dimensions at the same time. In addition to the implementation of this 2D-LC SST mixture to monitor system performance, the separation of peaks in the second dimension can help to initially adjust system parameters to improve the performance of the 

D separation before utilizing the 2D-LC system in routine pharmaceutical analysis. That is to say, selecting and examining the effect of various 2D chromatographic conditions, such as injection volume (volume of sampling loops), column dimensions, gradient, and flow rate on the peak shape, efficiency, and resolution, when collected 

D fractions of coeluted analytes are transferred to the second dimension.

Selecting proper SST test analytes is essential to ensure the reliability and accuracy of the data generated by the 2D-LC system. Because the system is comprised of two dimensions integrated together through an online interface (single or multiple valves), the probes should be sensitive to the performance of both dimensions. We selected test analytes to fulfill the following criteria:

Good UV absorbance (because the scope here is for 2D-LC systems with UV detectors only)

Commercially available at reasonable cost;

Span a range of hydrophilicity and hydrophobicity that reflects the range of properties that might be encountered in future, real samples;

Most importantly, respond differently to the selectivities used in the two- dimensional reversed-phase separation (for example, a pair of analytes were coeluted in the first dimension, but is separated in the second dimension).

With these criteria in mind, a four-component mixture was designed such that two peaks are observed in the 

D separation, and each of the two peaks contains a pair of coeluted compounds. The structures of these molecules are shown in Figure 1, and representative chromatograms are shown in Figure 2. The first early eluting peak contains a coeluted pair of hydrophilic and highly polar compounds, whereas the late eluting peak contains a pair of coeluted hydrophobic compounds.

FIGURE 1: Structures of the SST test analytes (paraxanthine, theophylline, ketoprofen, and β-estradiol). Properties were calculated using PerkinElmer ChemDraw Professional software (v.16.0.1.4(77))

D chromatograms for 0.5 μL injection of SST mixture on a commercial multiple heart-cutting 2D-LC system (Agilent). 

D chromaographic conditions: column 50 mm × 2.1 mm × 1.9 μm Poroshell EC-C18 (Agilent); solvent A: 0.05% trifluoroacetic acid in water:acetonitrile (95:5); solvent B: 0.05% trifluoroacetic in water:acetonitrile (5:95); gradient elution program: 1-25-60-100-100-1-1%B in 0-0.5-0.51-1.0-2.0-2.01-4.0 min; flow rate: 1.0 mL/min; column temperature: 40 °C; detection: 220 nm. 2D chromatographic conditions: column: 100 mm × 4.6 mm × 1.8 μm Bonus RP (Agilent); solvent A: 0.05% trifluoroacetic acid in water; solvent B: 0.05% trifluoroacetic acid in water:acetonitrile (5:95); Gradient elution program: 0-0-95-95-0-0%B in 0-1.0-5.5-6.0-6.1-10.0 min; flow rate: 2.5 mL/min; column temperature: 40 °C; and detection: 220 nm. The identities of the major 

D peaks are (in order of elution): paraxanthine, theophylline, ketoprofen, and β-estradiol.

The two hydrophilic compounds are structurally similar analogues that are difficult to separate, whereas the two hydrophobic compounds were chosen to be coeluted under the conditions of the 

D gradient. Generic chromatographic conditions (that is, flow rates, gradient slopes, and solvents) are used for both dimensions, and the two stationary phases used have complementary chemistries. The first is a traditional C18 column and the phase is used as a starting point in development of reversed-phase (RP) methods in our laboratory (that is, our platform method). The second is a polar-embedded RP column that is known to have selectivity highly complementary to most C18 columns (10,11).

The SST criteria are established to represent the minimum acceptable 2D-LC system performance rather than typical performance levels. This ensures that the predefined acceptance criteria are neither too wide—which would prevent detection of unexpected system problems—nor too narrow, which could trigger unnecessary alarms. The acceptance criteria we have settled on for this SST are as follows:

1. The number of peaks within the selected integration time window—two 

D peaks in the 0.3–0.9-min window, and four 

D peaks in the 2.0–3.0-min window for peaks 1a and 1b, and 4.0–5.0 min for peaks 2a and 2b;

2. The relative standard deviation (RSD) of retention time (

) and peak area <2% for triplicate injections;

4. A USP resolution >1.5 for peaks in the second dimension.

We monitored the performance of our developed SST with respect to 

 and resolution of the more challenging hydrophilic pair over the period of one year as shown in Figure 3 and Table I. These data show consistent performance of the 2D-LC system for its intended purpose as a whole integrated system, and they show the convenience of this developed SST over an extended period of use.

D chromatograms obtained for peaks 1a and 1b using the SST method at several intervals over a period of one year. Conditions were the same as in Figure 2.

Several 2D-LC SST failures could be attributed to various causes such as problems with the autosampler, interface valves, pumps, column aging, and mobile phase preparation errors. The aforementioned acceptance criteria are sensitive to these errors and may trigger early alarms that prevent the acquisition of unreliable data that lead to inaccurate results and the need to retest samples. Figure 4 shows an example of SST failure in our laboratory where the 

D performance was out of specification. Figure 4 shows 

D chromatograms from two SST injections that illustrate a sudden significant difference in performance. With respect to the acceptance criteria, it is clear that the peak number check fails to meet the required number within the specified integration time window because of the large shift in 

 of both peaks (blue trace in the chromatogram, where each peak represents a pair of coeluted peaks).

D chromatograms from cases (a) where the system was operating properly, or (b) where a small leak in the 

D flow path caused a significant shift of the 

D peaks out of their respective sampling windows. The failure of the SST triggered a repair of the 2D-LC to fix the leak.

Investigating the cause of this problem resulted in the identification of a small leak in the pump B head, which delivers the organic solvent component of the mobile phase. The leakage was too small to trigger the built-in leak sensor of the pump. Therefore, if the SST did not reveal this issue, it would have passed undetected with negative consequences for the reliability of the 2D-LC result. In this context, a difference in 

D separation performance can result in coeluted impurities that otherwise separate, or vice versa. A notable point to mention here is that the peak shape was also another indicator of poor performance, which could be captured by either adopting peak efficiency (

) as an additional SST acceptance criterion or by the visual examination of the chromatogram. The peak shape (broader peak) and 

 for the coeluted hydrophilic pair was more affected than the later one because a small difference of the delivered gradient has a significant effect on the initial low fraction of organic solvent in the mobile phase (1%) that elutes polar analytes.

In this installment of “LC Troubleshooting,” we described the development and implementation of a SST for multiple heartcut 2D-LC. Such SSTs are routinely used for conventional LC systems to verify that the performance of the LC system is suitable for use in analyzing pharmaceutical samples. However, there has been little discussion of SSTs for 2D-LC in the literature to date. The 2D-LC SST described here is intended to serve as a starting point and will likely become more sophisticated over time as we learn more about the criteria needed for the most effective use of the SST. Initial results from the regular use of the SST over a period of one year both demonstrated consistent performance of the 2D-LC method and identified one instance where the system performance was not suitable because of a small leak in the 

D pump that was subsequently repaired to restore system performance.

The authors would like to thank Qinggang Wang for his feedback and suggestions while preparing this article.

https://doi.org/10.1016/j.chroma.2017.02.074

(6) Q. Wang, B.L. He, and J.G. Shackman, 

https://doi.org/10.1016/j.jpba.2020.113730

(7) General Chapter <621> “Chromatography,” in 

 (United States Pharmacopeial Convention, Rockville, MD, 2022).

(8) M. Klarqvist, T. Leek, A. Babapour, and N. Falk, 

(9) I. Mutton, B. Boughtflower, N. Taylor, and D. Brooke, 

https://doi.org/10.1016/j.chroma.2011.04.033

https://doi.org/10.1016/j.chroma.2009.06.048

(11) R.K. Lindsey, B.L. Eggimann, D.R. Stoll, P.W. Carr, M.R. Schure, and J.I. Siepmann, 

https://doi.org/10.1016/j.chroma.2018.09.018

 is Senior Scientist in the Chemical Process Development group at Bristol Myers Squibb, in New Brunswick, New Jersey.

 is the editor of “LC Troubleshooting.” Stoll is a professor and the co-chair of chemistry at Gustavus Adolphus College in St. Peter, Minnesota. His primary research focus is on the development of 2D-LC for both targeted and untargeted analyses. He has authored or coauthored more than 75 peer-reviewed publications and four book chapters in separation science and more than 100 conference presentations. He is also a member of 

’s editorial advisory board. Direct correspondence to: 

As two-dimensional liquid chromatography (2D-LC) becomes more widely used, system suitability tests (SSTs) become even more important.

Development of a System Suitability Test for Two-Dimensional Liquid Chromatography

An ultrahigh-pressure liquid chromatography–mass spectrometry (UHPLC–MS) research prototype instrument was built to improve the resolution power and the usability of conventional LC–MS hyphenated instruments for routine analyses in pharmaceutical applications. The improved characteristics of this UHPLC–MS system include: 1) the dramatic reduction of post-column sample dispersion; 2) the adoption of vacuum jacketed columns (VJC) for the reduction of undesirable radial temperature gradients across the column diameter; and 3) the presence of a column outlet end nut heater to refocus the distorted peaks prior to analyte ionization. The benefits of each of these added features are analyzed with a rigorous approach from a peak broadening perspective. A 2x improvement in peak capacities recorded with this prototype UHPLC–MS system compared to a standard system (Acquity UHPLC I-class/Xevo TQ-S) is illustrated for the gradient separation of seven small pharmaceutical compounds using a 2.1 mm x 100 mm column packed with sub-2-μm core-shell particles (1.6 μm Acquity UHPLC Cortecs C18 column).

Hyphenated liquid chromatography–mass spectrometry (LC–MS) systems have become the most widespread and routine separation detection techniques in metabolomics, proteomics, and lipidomics, as well as in the pharmaceutical and agricultural industries (1–10). The move from LC–MS to ultrahigh-pressure liquid chromatography (UHPLC)–MS during the 2000s after adopting small volume columns (2.1 mm i.d., 5–10 cm long) packed with very fine particles (sub-2-μm) has revealed the resolution limit of standard LC–UV and LC–MS hyphenated instruments (11–17). In gradient elution, the observed loss of peak resolution relative to the expected performance of the column alone is essentially because of the large post-column sample dispersion (18). The transport of the analyte from the LC column outlet to the electrospray ionization (ESI) source usually occurs via several lengthy connecting tubes and a divert (infusion) valve, which together generates a significant amount of sample dispersion relative to that caused by the column itself. Peak capacity is then severely reduced unless a solution is found to eliminate or at least minimize post-column dispersion (13,16,17).

The practical problem encountered in conventional UHPLC–MS instruments is that the position of the column oven in the LC instrument stack is remote from the ESI source of the mass spectrometer. Therefore, the UHPLC-to-MS connecting tube dimensions are unsuitable for UHPLC columns to perform at their best. For instance, the Acquity UHPLC I-class/Xevo TQ-S hyphenated system is equipped with a 60 cm x 100 μm tube connecting the column outlet to a divert/infusion valve and a 75 cm x 125 μm tube connecting this valve to the ESI source: overall, they account for a total post-column dispersion variance close to 13 μL

 (small molecules, 1 mL/min). In contrast, the dispersion variance of a 2.1 mm x 100 mm column packed with 1.6 μm core-shell particles is only of the order of 3 μL

 in gradient elution for a retention factor approximately 1 at elution. In practice, it amounts to observing a peak capacity that is approximately half that theoretically expected from new generations of UHPLC columns.

This work proposes a solution by redesigning the interface between the UHPLC instrument and the mass spectrometer. In the first part of this article, a research prototype UHPLC–MS instrument is built. Its specific features are described to illustrate the main problem of excessive post column dispersion while maintaining the integrity of the column performance. In the second part, each modification of the conventional UHPLC–MS instrument is justified from a sound and quantitative approach. Finally, it is illustrated from a concrete pharmaceutical separation problem how much gain in peak resolution and sensitivity the users can benefit from the prototype system relative to conventional UHPLC–MS instruments.

Seven pharmaceutical compounds (acetominophen 10 μg/L, valine-tyrosine-valine 2.5 μg/L, leucine-enkephalin 2.5 μg/L, sulfadimethoxine 1 μg/L, verapamil 0.6 μg/L, reserpine 1.9 μg/L, and terfenadine 0.6 μg/L) were prepared in a mixture of acetonitrile and water (75/25, v/v) and injected under a gradient condition in a 2.1 mm x 100 mm Acquity UHPLC Cortecs C18 1.6 μm column (Waters). The LC system is the Acquity UHPLC I-class equipped with a binary solvent manager and a fixed loop sample manager (Waters). The vacuum jacketed columns were outfitted in house with custom vacuum sleeves. The injection volume, the flow rate, and the inlet eluent temperature were set at 0.3 μL, 0.6 mL/min, and 50 °C, respectively. Two solvent bottles (A and B) were prepared: solvent bottle A contained 0.1% (v/v) formic acid in water, and solvent bottle B contained 0.1% (v/v) formic acid in acetonitrile. The volume fraction of B was programmed to increase linearly from 2% to 98% over 3 min. The analyte detection was performed under the multireaction monitoring (MRM) mode of the Xevo TQ-S mass spectrometer (Waters). The dwell time, the capillary voltage, the source temperature, the desolvation temperature, the desolvation flow rate, and the cone flow rate were fixed at 3 ms, 3.0 kV, 120 °C, 600 °C, 1000 L/hr, and 150 L/hr, respectively, for all compounds. All the other MS detector details specific to the analyte (cone voltage, masses of precursor, and product ions) are given in Table I.

In this series of isocratic experiments, the same column and UHPLC system as those described above were used, except the column outlet was connected to the optical TUV detector (250 nL volume, 254 nm wavelength, 40 Hz sampling rate) using a 15 cm x 75 μm connecting tube. The sample mixture is a solution of acenaphthene (0.2 g/L) and octanophenone (0.1 g/L) prepared in a 25:75 (v/v) mixture of water:acetonitrile, which was also the solvent composition used as the mobile phase. The injection volume, the flow rate, and the inlet eluent temperature were set at 0.5 μL, 0.6 mL/min, and 50 °C, respectively.

In this work, the radial temperature profiles (from 

 = 1.05 mm) expected across the packed bed diameter at the column outlet 

 = 10 cm) were simulated under a steady-state temperature regime by considering the most realistic design and structure of the vacuum jacketed column (VJC) as shown in Figure 2. All the modeling and post-analysis were done using Ansys Fluent 2020 R2 software.

Briefly, a minimum element size of 75 μm was selected for the packed bed zone and features under 5 μm were not featured. A total of 6,940,547 nodes and 14,984,108 elements were generated. The model is based on a pressure-based steady-state solver with double precision and considers gravity to resolve natural convection. A coupled solver was used for solving pressure-velocity coupling of the Navier-Stokes momentum, Navier-Stokes energy, and the continuity equation. Based on its bulk superficial velocity and Reynold’s number, a laminar viscous model with viscous heating was used for the eluent mixture (acetonitrile:water 50/50, v/v). The thermal profile inside the packed bed zone was modeled assuming an energy source term for the eluent mixture without modeling the actual details of the macroporous zone. The viscous heat that was generated was calculated from the total pressure drop, the volumetric flow rate, the fluid inlet temperature, and the thermal expansion coefficient of the eluent. The surrounding air was modeled as an incompressible ideal gas. The inlet boundary condition is set by the inlet superficial linear velocity of the eluent at a fixed temperature of 50 °C. The post-column heater was set at a uniform and constant temperature boundary condition, which was increased from 60 °C to 75 °C in subsequent simulations. Table II lists all the necessary physicochemical parameters assumed in the calculation.

Overall Description of the Novel Research Prototype UHPLC–MS System

The key motivation underlying the proposed design of the UHPLC–MS research prototype system is to eliminate most of the post-column sample dispersion occurring from the column outlet to the divert (infusion) valve and the ESI source. Figure 1 shows schematics of the standard and modified systems (left) and photography of the research prototype system (right). The chromatographic column (2.1 mm x 100 mm, 1.6 μm Cortecs C18 superficially porous particles) was placed on a prototype column holder fixed directly onto the atmospheric pressure ionization (API) source enclosure. The post-column tubing assembly of the modified UHPLC–MS system was optimized to minimize the post-column dispersion. Overall, the post-column dispersion variance is reduced from approximately 13 μL

 (for a 60 cm x 100 μm tube + a divert (infusion) valve + a 75 cm x 125 μm tube) to approximately 0.3 μL

 only. The gain in performance is discussed quantitatively in the next section.

FIGURE 1: Schematics of the (a) standard and (b) modified configurations of the LC–MS systems and (c) photography of the modified system. The key modifications of the stan- dard system consist of eliminating the column oven, drastically reducing post-column sample dispersion, wrapping the column in a vacuum jacket, and placing an end nut heater at the column outlet.

The injection valve of the I-class Acquity UHPLC system is now connected to the column inlet via a 60 cm x 120 μm i.d. Peek tube in addition to an active eluent preheater (APH). The relatively large precolumn dispersion of the APH (~6 μL

) is not a severe issue in gradient elution because of the sample focusing at the column head. The eluent temperature at the column inlet can still be controlled over a wide range from room temperature to 90 °C. The anticipated problem of placing the column outside the standard air oven compartment (the oven temperature is usually equal to the inlet eluent temperature) is the cooling of the column wall because of heat exchange with the surrounding air at room temperature. Consequently, the lack of control of the column wall temperature and the loss of column performance because of the column-to-laboratory temperature mismatch requires a solution to avoid the formation of undesirable radial temperature gradients (19–22). Therefore, the column was wrapped in a vacuum jacket (see Figure 2), described in great detail in two previous special issues of 

 (23,24). The benefit of the VJC is that the heat delivered at the column inlet (25 °C < Tinlet < 90 °C) can no longer be dissipated by heat exchange between the column wall (hot, T ≥ 25 °C) and the surrounding air (cool, room temperature), so the overall column temperature can be controlled.

FIGURE 2: Three-dimensional (3D) model of a VJC column left in still-air condition. This model simulates the steady-state temperature profiles along and across the entire column volume, including the packed bed volume (2.1 mm x 100 mm). The numerical simulation has accounted for all geometrical details of the different actual elements.

However, small residual heat leaks are detected at the column ends and negatively affect the column performance (24). Therefore, an outlet end nut heater is placed at the outlet of the column to reverse the heat flow direction from outside to inside the column. The anticipated effect is to refocus the tailing peaks and recover the full column performance. The benefit of the outlet end nut heater maximizing column performance will be demonstrated and explained in detail in the next section (using an infrared [IR] camera and simulation of the temperature profiles across the packed bed).

The Rationale Behind the UHPLC–MS System Modifications

In this section, it is justified from scientific arguments (analysis of the peak volume variance, IR surface temperature profiles, simulation of the column temperature profiles, and explanation of the observed change in peak asymmetry) why the configuration of standard LC–MS systems had to be modified. It is explained how the gradient performance of current LC–MS systems is improved every step of the way by 1) reducing the post-column sample dispersion; 2) wrapping the column in a vacuum jacket; and 3) delivering heat locally to the column outlet end fitting using an end nut heater.

Figure 3 justifies why the post-column modifications are critical in LC–MS when operating a narrow-bore 2.1 mm i.d. x 100 mm long column packed with 1.6 μm Cortecs-C18 core-shell particles. Each solid-colored curve represents all the possible combinations of post-column dispersion (

-axis) and retention factor, kelution, at elution (

-axis), leading to the same apparent gradient peak capacity equal to a fraction, 

 < 0.98), of the maximum theoretical gradient peak capacity expected when the post-column dispersion is strictly equal to zero. Assuming that the gradient compression factor is close to 1 (that is, small molecules) and the retention factor at elution is 1, then a standard UHPLC–MS system with a post-column sample dispersion equal to 13 μL

 ~0.44. Therefore, the gradient peak capacity observed is no more than 44% of the maximum peak capacity. Reducing the post-column sample dispersion from 13 μL

 (see the vertical blue arrow) increases p from 0.44 to 0.95: the observed peak capacity is now equal to 95% of the maximum peak capacity or a relative increase of 116% compared to that observed for the standard UHPLC–MS system. Nevertheless, in contrast, Figure 4 reveals experimentally that the peak capacity increases from 117 (reference LC–MS system configuration: “Standard”) to only 187 (60%, modified “No sleeve” configuration) with reduced post-column sample dispersion. This less-than-expected performance gain is explained by the fact that the eluent temperature cannot be maintained at 

 = 50 °C along the entire column length because of heat losses towards the external environment. This problem calls for additional modification of the instrument.

FIGURE 3: Plots (solid-colored thick lines) of the fraction 

 = 32 to 44, 55, 76, 91, 95, and to 98%) of the maximum peak capacity theoretically expected as a function of the post-column dispersion (

-axis). The 2.1 mm x 100 mm column is packed with 1.6 μm Cortecs-C18 particles (

 = 40,000). The two horizontal dashed lines represent the post-column dispersion variance of the standard (13 μL

) LC–MS systems. The vertical blue arrow indicates the expected and theoretical gain, 95/44 = +116%, of the peak capacity after modifying the standard LC–MS system shown in Figure 1.

FIGURE 4: Showing the VJC configuration performance comparison (

 = 50 °C). Variation of the experimental gradient peak capacity as a function of the four system configurations investigated in this work: 1) “Standard” → Classical LC–MS system; 2) “No sleeve” → Modified LC–MS system without VJ sleeve and end nut outlet heater; 3) “With sleeve” → Modified LC–MS system with VJ sleeve but without end nut outlet heater; and 4) “With sleeve and opt outlet T” → Modified LC–MS system with VJ sleeve and end nut outlet heater at optimum temperature (70 °C). The gradient peak capac- ity’s maximum relative increase is 249/117 = +113%.

Bringing the column outlet near the API source enclosure leaves the heated column (

 = 50 °C) in a still-air environment at room temperature.

The column temperature cannot be maintained uniform at the temperature set by the active eluent preheater at the column inlet. The temperature difference between the column walls and the surrounding air drives a heat flux from the column body towards the laboratory air. Therefore, radial temperature gradients are formed across the column diameter and negatively affect its performance. To cope with that problem, the column was wrapped in a vacuum jacket to prevent the heated eluent from cooling off as it flows further down along the column length. The principle of this ideal vacuum jacket column has been presented and explained in several previous communications (25,26). Not only is the eluent temperature maintained constant (at low flow rates, no viscous heating) along the column length, but it also preserves the integrity of the column performance when viscous heating becomes significant (high flow rates and pressure drops). The amplitude of the radial temperature gradients across the column inner diameter is minimized, and the column efficiency remains close to its theoretical maximum.

Figure 4 shows that the peak capacity increases from 187 (“no sleeve” configuration) up to 209 (“with sleeve” configuration) after the column is wrapped with the vacuum jacket. The relative gain of peak capacity increases to 79%, which is closer to 116% (as expected theoretically) than the 60% reported in the absence of a vacuum jacket. The remaining gap to be covered is explained when looking at the surface of the VJC using an IR camera.

The IR image in Figure 5 is a 2.1 mm x 100 mm stainless steel (SS) column packed with 1.6 μm Cortecs-C18 particles installed in the "with sleeve" UHPLC–MS system configuration. The inlet temperature is kept free at room temperature (~23 °C), the flow rate of pure water was fixed at 0.65 mL/min, and the pressure drop was recorded close to ∆

 = 12,000 psi. The heat capacity of water at room temperature is 

-K, and its coefficient of thermal expansion is α = 3.1 × 10

FIGURE 5: (a) Evidence of heat leaks because of viscous heating (

 = 12,000 psi, 100% water) at the column outlet revealed by an IR camera image. (b) End nut heater 

 = 50 °C). Experimental gradient peak capacity is measured as a function of the outlet end nut heater temperature (from “off” or passive to 40, 50, 60, 70, and 80 °C). Note the optimum peak capacity for 

Accordingly, if the column is strictly operated under adiabatic conditions, the expected increase, ∆

, of the water temperature from the column inlet to the column outlet is expected to be ∆

 = +18 °C. The red color at the column outlet end fitting revealed by the IR camera is an indication of heat leaks. It is noteworthy that the heat somewhat diffuses back towards the column inlet along a short section of the vacuum jacket. This IR camera image confirms that the whole column is not entirely thermally insulated and is still exchanging some heat with the surrounding laboratory air environment. The same phenomenon occurs at the column inlet when the imposed inlet temperature is above laboratory temperature. The overall result is a measurable loss of column performance caused by the presence of undesirable radial temperature gradients at both the inlet and the outlet regions of the column. The mechanism underlying this performance loss was previously proposed in a short communication (24).

A physical solution to this problem is proposed and consists of placing an end nut heater at the column outlet in direct contact with the exposed SS surface of the outlet end fitting. The anticipated effect is to refocus the distorted peak shape as much as possible. The graph in Figure 5 considers the case where the temperature of the inlet mobile phase is fixed at 50 °C. The experimental section gives all the experimental details regarding the gradient conditions and the measurement of the reported peak capacity. The temperature, 

, imposed by the outlet end nut heater was then increased stepwise from room temperature (“off” or passive) to 40, 50, 60, 70, and 80 °C. The most remarkable result is that the observed peak capacity passes through a maximum (249) for 

 ~60–70 °C. The gain of peak capacity relative to that observed for the standard UHPLC–MS system (117) is now equal to +113%, close to the maximum of +116% expected theoretically. Overall, this is because of 1) the drastic reduction of the post-column sample dispersion from approximately 13 μL

 and 2) the elimination of the negative effect of radial temperature gradients on column performance. The proposed explanation is as follows: when 

 is not sufficiently high (<60 °C), the temperature of the bed in the inlet and outlet regions of the column is more prominent in the center than in the wall region, and the loss of column performance is maximum. When 

 is optimum (~70 °C), the wall temperature is higher than the bed temperature at the column outlet (that is, the direction of the heat flow is reversed ature of the bed in the inlet and outlet from outside to inside). The initial peak distortion occurring at the column inlet is somewhat compensated at the column outlet according to a refocusing phenomenon (27–29), leading to nearly symmetric peaks. Finally, if 

 is too high (>75 °C), the heat flow imposed in the outlet region of the column is too large and overcompensates for the initial peak tailing (the peaks are then fronting). This mechanistic interpretation is well supported by 1) the calculation of the radial temperature profiles at the column outlet (Figure 6), according to the simulation approach described in the method section, which reveals that the amplitude of the radial temperature gradient is minimized for 

 ~70 °C and 2) from the evolution of the peak asymmetry (from tailing to symmetrical, and to fronting) observed under isocratic elution when increasing 

FIGURE 6: Calculation of the radial temperature profiles across the diameter (2.1 mm) of the packed bed at the column outlet (

 = 10 cm) for three different outlet end nut temperatures (

 = 50 °C. Note the quasi-flat temperature profile when the optimum outlet end nut temperature is set at 70 °C.

FIGURE 7: Experimental variation of the peak asymmetry (at 5% peak height) of (a) acenaphthene and (b) octanophenone eluted under isocratic conditions (see details in the experimental section) as a function of the outlet end nut temperature (

 = 50 °C. Note the progressive evolution of the peak shape from tailing to fronting when increasing the heat flux from the column outlet wall to the packed bed. Quasi-symmetric peaks are observed at the optimum temperature of 70 °C.

In this section, we illustrate the practical advantage of performing gradient elution with the modified UHPLC–MS system. The experimental section details the experimental conditions (column, gradient, flow rate, nature and concentration of the samples injected, and temperatures). In particular, Figure 8 compares the observed peak shapes (MS detection, MRM mode, and the total ion count) of three of the seven analyte products (the precursor ions are verapamil, reserpine, and terfenadine), which are recorded under the same four UHPLC–MS configurations as those discussed in the previous section (see Figure 4). After complete system modifications (from “standard” to “with sleeve 70 °C outlet”), it is remarkable that the peak widths are virtually reduced by a factor of two for all the compounds injected irrespective of their elution time. The total ion chromatogram in Figure 8 also confirms that the insulation of the column using a VJ and the application of heat at the column outlet participate both to further increase the resolution power and the sensitivity of the very same LC gradient method.

FIGURE 8: Application: LC–MS gradient chromatograms of a pharmaceutical sample mixture (See experimental section and Table I for the gradient conditions) recorded for the same four system configurations as those described in Figure 3. Note the constant reduction of the peak widths of verapamil, reserpine, and terfenadine compounds from the “Standard” to the “No sleeve,” “With the sleeve,” and to the “With sleeve and opt outlet T” system configurations.

In this work, a research prototype UHPLC–MS system was built to significantly improve the resolution performance compared to conventional UHPLC–MS systems. The improved system integration between the column outlet and the API source was made possible by replacing the LC oven with a column support placed directly against the API enclosure. In the absence of the column oven, maintaining the full integrity of the column efficiency consisted of wrapping the column with a vacuum jacket and delivering a well-controlled heat flow at the exposed outlet of the column. At pressure drops of about 12,000 psi, the temperature of the outlet end nut heater should be approximately 20 °C higher than the inlet temperature imposed by the active eluent preheater for maximum column performance. Additionally, the risk of eluent leaks at the column inlet and outlet and poor data reproducibility caused by the improper manual column installation and the aging of column-to-tube connections at very high pressures were avoided by adopting an easy-to-use cam-actuated mechanism for the column installation.

In conclusion, the overall relative increase of the peak capacity observed was quantitatively interpreted from the combination of the drastic reduction of the post-column sample dispersion (13 μL

) along with the elimination of most of the radial temperature heterogeneities (∆

 < 0.3K) across the packed bed diameter by adjusting the temperature of the column outlet (

The authors would like to sincerely thank Thomas McDonald, Michael Fogwill, Joseph Michienzi, Susan Abbatiello, Robert Plumb, and Nikunj Tanna (Waters Corporation) for their constant technical and engineering suggestions and fruitful discussions pertaining to this research project.

Fundamentals of Contemporary Mass Spectrometry

 (John Wiley and Sons, Hoboken, NJ, 2007).

(6) I. Wilson, R. Plumb, J. Granger, H. Major, R. Williams, and E. Lenz, 

(7) D. Guillarme, J. Schappler, S. Rudaz, and J.-L. Veuthey, 

(8) G. Pocsfalvi, C. Stanly, I. Fiume, and K. Vekey, 

(9) F. Jeanneret, D. Tonoli, M. Rossier, M. Saugy, J. Boccard, and S. Rudaz, 

(10) E. Farsang, D. Guillarme, J.-L. Veuthey, A. Beck, M. Lauber, A. Schmudlach, and S. Fekete, 

(11) S. Popovici, W. Kok, and P. Schoenmakers, 

(12) K. Fountain, U. Neue, E. Grumbach, and D. Diehl, 

(13) F. Gritti, C. Sanchez, T. Farkas, and G. Guiochon, 

(16) S. Buckenmaier, C. Miller, T. van de Goor, and M. Dittmann, 

(18) F. Gritti, T. McDonald, and M. Gilar, 

(22) K. Kaczmarski, F. Gritti, J. Kostka, and G. Guiochon, 

(25) F. Gritti, M. Gilar, and J. Jarrell, 

(26) F. Gritti, M. Gilar, and J. Jarrell, 

(28) N. Lambert, S. Miyazaki, M. Ohira, N. Tanaka, and A. Felinger, 

(29) F. Gritti, M. Dion, A. Felinger, and M. Savaria, 

 is a Principal Consulting Scientist in the Instrument/Core Research/Fundamentals Department at Waters Corporation in Milford, Massachusetts.

 is a Research Mechanical Engineer II at Waters Corporation in Milford, Massachusetts.

 is a Principal Mechanical Engineer working for Waters Corporation in Milford, Massachusetts.

 is a Principal Research Scientist at Waters Corporation in Milford, Massachusetts.

 is a Research Fellow in Research and Development at Restek. He also serves on the Editorial Advisory Board for 

 and is the Editor for “Column Watch.” Over the past 20 years, he has worked directly in the chromatography industry, focusing his efforts on the design, development, and application of chromatographic stationary phases to advance gas chromatography, liquid chromatography, and related hyphenated techniques. His main objectives have been to create and promote novel separation technologies and to conduct research on molecular interactions that contribute to retention and selectivity in an array of chromatographic processes. His research results have been presented in symposia worldwide, and have resulted in numerous peer-reviewed journal and trade magazine articles. Direct correspondence to: 

With a new prototype, we explore how to improve the resolution power and usability of LC–MS instruments for routine analysis in pharmaceutical applications.

Improved Performance of UHPLC–MS Hyphenated Systems

Used by chemists and nonchemists alike, gas chromatography (GC) is considered mature and among the most widely used instrumental techniques for chemical analysis. Because instruments have become both more sensitive and easier to use, columns have achieved higher resolution and stationary phases have greater selectivity. As a result, gas chromatographs have taken on a “black box” view. With greater sensitivity, resolution, and advanced data handling capabilities, a new set of experimental uncertainties emerge that may not be apparent to most users, especially those who were not formally trained as analytical chemists. In this installment of ”GC Connections,” we examine these uncertainties in typical GC methods, especially as they relate to quantitative analysis. We look at hidden experimental uncertainty, especially in the glassware used for sample preparation. We also comment on injection and detection with an eye toward understanding the sources of the errors. It is important to understand the experimental error and uncertainty are inherent in all analytical techniques; they can be reduced but cannot be eliminated.

An increasing portion of the chromatographic literature of today describes applications and quantitative analysis rather than fundamental advances in chromatographic techniques and principles. I am not offering an opinion about whether this is good or bad, but it is apparent. Articles describing chromatographic methods that show quantitation at parts per billion (ppb) and lower levels are now commonplace. However, much of this literature shows common mistakes and problems with experimental uncertainty in quantitative analysis. Most commonly, uncertainties, usually in the form of standard deviations, are presented with too many significant digits. Uncertainty should be expressed in the least significant digit. The uncertainty then determines the number of significant digits in the result regardless of the number of digits provided by the data system. Often, I see both uncertainties and quantitative results presented with too many significant digits.

In addition to this first challenge, the basic reporting of results often confuses the presentation of both the experimental result and the uncertainty. Classically, results larger than 10 and smaller than 0.1 should be reported using scientific notation. This guideline is often stretched to 0.01–100, but it should not be stretched further. Strict adherence to this rule by itself reduces confusion in result reporting and significant figures.

An additional challenge relates to the common use of the standard deviation and relative standard deviation (RSD) as a figure of merit for the precision of chromatographic results. As we know from basic population statistics, one standard deviation from the mean indicates that approximately 68% of results should be expected to be in that range. The true experimental uncertainty is larger, typically around two standard deviations, which would include approximately 95% of the results, or three standard deviations, which would include about 99.7% of expected results. However, most quantitative analytical chemistry experiments do not generate enough results for population statistics, so these generalizations do not hold. Classically, as taught in quantitative and instrumental analysis texts for decades, a 95% confidence interval about the data is best used as the experimental uncertainty, which for small populations of data would be significantly wider than one standard deviation. In much of the chromatography literature, this additional step is not performed. In short, much of the literature underestimates experimental uncertainty and overestimates significant figures.

This observation is not to denigrate the work of the many scientists developing and optimizing gas chromatography (GC) methods. Because GC has become increasingly popular over the years, it has gone from a technique largely performed by formally trained analytical chemistry specialists to a much broader range of scientists, who may not have had formal training in quantitative analysis and analyzing experimental error and uncertainty. In the rest of this installment, we examine some common cases where experimental uncertainty arises in GC methods.

Even simple “dilute and shoot” methods have hidden experimental uncertainties. We start with this case because nearly all other sample preparation techniques and methods involve dilution in the preparation of samples and standards. Many analysts make the incorrect assumption that volumetric glassware is perfect. Figure 1 shows a close-up look at a typical “Class A” 100 mL volumetric flask, with the class indication circled. For any volumetric glassware, it is best to use Class A glassware and avoid any glassware that does not indicate class or has the markings worn off. If you look closely, you can note the uncertainty value of ±0.08 mL provided in the printing on the flask. Although the uncertainty seems small, the rules for propagation of errors tell us that each additional dilution step will add to the experimental uncertainty of the result.

FIGURE 1: Close-up photograph of a 100 mL Class A volumetric flask.

Table I shows the uncertainties involved with some Class A volumetric flasks and transfer pipets. It illustrates one of the interesting problems in analytical method development. Because we are pressured to reduce the use of solvents, smaller volumes introduce higher relative experimental errors in each step. Table I shows that there is flask-to-flask and pipet-to-pipet experimental uncertainty involved with volumetric glassware that must be considered when developing methods. Drawing a sample to the mark in a pipet or filling to the mark in a flask may not deliver the exact volume stated on the device. To this end, experimental procedures for gravi- metrically verifying the volume delivered by a pipet or contained in a flask have been published by the National Institute of Standards and Technology (NIST) (1).

Consider the experimental uncertainty involved in a 1:100 dilution of a pre-prepared stock standard solution by two different procedures. In the first procedure, a 1 mL class A transfer pipet is used to deliver 1 mL of the stock solution into a 100 mL class A volumetric flask and the flask is filled to the mark with the dilution solvent. In the second procedure, a 1 mL class A transfer pipet is used to deliver 1 mL of the stock solution into a 10 mL class A volumetric flask that is filled to the mark with the dilution solvent. Using a second 1 mL class A transfer pipet, 1 mL of the diluted solution is then transferred to a second 10 mL Class A volumetric flask, which is then filled to the mark with the dilution solvent. In procedure 1, a total of approximately 100 mL of dilution solvent is used; in procedure 2, the amount of dilution solvent is reduced by 80% to approximately 20 mL. Table II shows the propagation of errors comparison of procedures 1 and 2. Detailed equations and discussion of propagation of errors is not provided here but can be referenced in nearly any textbook on analytical chemistry or instrumental analysis (2). In that chapter, I share a specific example of a propagation of error analysis applied to a pharmaceutical analysis method. Table II shows that the serial dilution procedure increases the uncertainty from 0.6% to 0.9% over the single dilution, which is an increase of 50% in the uncertainty.

As seen in Table II, the serial dilution procedure, which most analysts would prefer today because it uses far less solvent, has significantly higher experimental uncertainty, and this experimental uncertainty would then be added to any uncertainty in the stock standard. Note that when making extremely low concentration standards, which is a common need with the extremely sensitive methods and instruments of today, the experimental uncertainty involved in using even the most precise available glassware to prepare standards and samples in multiple dilution steps can lead to relatively large uncertainties that may reduce the number of significant figures in the experimental results. As a result, it is likely that any determinations at sample concentrations lower than parts per million (ppm) level should be reported with no more than one or two significant figures.

The inlet and injection process in GC is well-known to provide hidden uncertainty, as discussed in two recent “GC Connections” installments and a classic book (3–5). As discussed above, as pipets and sample delivery system volumes get smaller, relative experimental uncertainty in the delivered volume increases. Most microliter volume syringes are accurate to approximately 1% of their nominal maximum volume. A typical 10 μL syringe has graduations representing 0.1 μL. Interestingly, it is common to inject 1 μL of liquid using a 10 μL syringe, providing a nominal error of up to 10% in the accuracy of the delivery. Furthermore, the graduations on the syringe barrel do not account for the internal volume of the syringe needle, which is approximately 0.6 μL. Therefore, our 1 μL injection using a 10 μL syringe may be an injection of 1.5–1.7 μL, depending on the accuracy of the syringe.

With the use of an auto-injector and proper maintenance, a syringe can remain highly reproducible for hundreds or possibly thousands of injections. Syringe manufacturers provide quick guides on how to take care of and perform maintenance on syringes (6) that include suggestions for extending syringe lifetime. With the high precision of auto-injectors, users can typically expect injections with less than 1% RSD in the resulting peak areas from injection to injection. Difficulty can arise when the syringe is changed; you can expect peak areas to vary by several percentage points up or down from the original syringe. With effective calibration, and either internal or external standard, this change may not be noticed unless working at or near the limit of detection (LOD) or limit of quantita- tion (LOQ), where a few percent of reduced injected sample volume might move results lower than the LOD or LOQ.

Uncertainty in Detection and Quantitation

In a recent installment, we discussed several hidden challenges in measuring the LOD for an instrument or as part of the method validation process (7). We saw that the classical International Union of Pure and Applied Chemistry (IUPAC) calculation for LOD includes terms only related to uncertainty in the measured signal, not in the calibration curve. We saw an alternate calculation, based on propagation of errors, for determining the LOD that includes terms for uncertainty in both the slope and 

-intercept of the calibration curve. Earlier in this column, we discussed uncertainty in simple “dilute and shoot” procedures, which are similar to the procedures used to generate calibration curves.

In general, greater increases in experimental uncertainty from calculations occur when subtraction and division are used in equations and formulas. In both cases, the calculation result becomes smaller while the uncertainty becomes larger. Table III illustrates this principle with some simple calculations, in which the values 1.100 x 10

 ± 0.2 are combined by addition, subtraction, multiplication, and division. Note that both initial values would be seen as highly precise. As seen in Table III, the original data has a relative uncertainty of 0.2%. When the data points are multiplied or divided, the uncertainty is determined from the relative uncertainties, so the final uncertainty is the sum on a relative basis for both. Since experimental uncertainties are additive for addition and subtraction, adding the two data points results in a decreased relative uncertainty as the result increases faster than the uncertainty. However, subtracting them results in a much greater relative uncertainty, since the result is now smaller and the uncertainty larger. In this case, the four significant figure original data is reduced to three in the result. The relative experimental uncertainty increases from a fraction of a percent to nearly 3% in the subtraction case. When I examine GC methods with unsatisfactory reproducibility, the first places I look for the source of the problem are calculations and glassware choices, followed by injection and detection.

Error analysis and the consideration of experimental uncertainty may seem like a chore. However, it is one of the most important aspects of method development, optimization, and validation. GC instruments and data systems are highly precise, and they generate raw data that may have three, four, or more significant figures. In the past, we would look first at potential instrumental challenges when troubleshooting and optimizing problems with precision and accuracy. Today, I look first at the glassware and calculations, followed by the instrument. Chromatographers should be cautious and recognize that there are hidden uncertainties in almost all quantitative chromatographic methods that may increase experimental uncertainty, reduce the number of significant figures, and make the data coming from the data system look more precise and accurate than it really is.

NISTIR 7383: Selected Procedures for Volumetric Calibrations (2109 ed)

 (National Institute of Standards and Technology, Gaithersburg, MD, 2019).

(2) G.D. Christian, P.K. Dasgupta, and K.A. Schug, 

 (John Wiley and Sons, Hoboken, NJ, 2013), pp. 81.

Split and Splitless Injection for Quantitative Gas Chromatography: Concepts, Processes, Practical Guidelines, Sources of Error, 4th, Completely Revised Edition

 (John Wiley and Sons, Hoboken, NJ, 2008).

. https://www.hamiltoncompany.com/ laboratory-products/support/documents/care-and-use-guide. (accessed April, 2022).

 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: 

Hidden uncertainties in quantitative methods may make data look more precise and accurate than they really are. Take particular care when using dilution, which can increase experimental uncertainty.

Is the Solution Dilution? Hidden Uncertainty in Gas Chromatography (GC) Methods

Per- and polyfluoroalkyl substances (PFAS) are a large group of anthropogenic chemicals that have been applied in a wide range of industrial, commercial, and domestic products since the 1950s. Because of their toxicity, persistence, and bioaccumulation potential, PFAS have become global environmental pollutants. Besides the environment, the food chain represents another source of exposure, and the risk to consumers related to the presence of PFAS in foods has recently become of increased interest. In this respect, whole milk, infant formula, and ingredients used in infant formula production represent important foodstuffs that require sensitive methods with reporting limits at low parts per billion levels or lower for multiple PFAS. This article summarizes optimization experiments and validation of a complete workflow, including sample preparation and a liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for determination of sixteen priority PFAS analytes listed by the U.S. Food and Drug Administration (FDA).

This method for PFAS analysis in milk and infant formula is robust, reliable, and reproducible, with scope to expand the list of PFAS in the future.

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