This year is the 25th edition of the International Symposium on Advances in Extraction Technologies (ExTech) and the conference will be held in Tenerife (Canary Islands, Spain) from 18–21 July 2023. Here’s a glimpse of what attendees can look forward to.

The International Symposium on Advances in Extraction Technologies (ExTech) is an important event series in the growing fields of sample preparation, extraction technologies, and sample clean-up techniques. This worldwide conference was started in 1999 by Professor Janusz Pawliszyn (University of Waterloo, Canada), and, since then, the symposium has been held annually in different cities around the world.

This year is the 25th edition and the conference will be held in Tenerife (Canary Islands, Spain) from 18–21 July 2023.

The organizer of the conference this year is the University of La Laguna (ULL, Spain), with Professors Verónica Pino and Javier Hernández-Borges acting as chairwoman and co-chairman, respectively.

Tenerife is a Spanish island with a volcanic origin and is located in the Atlantic Ocean, about 100 km off the coast of Africa. In the centre of the island, Mount Teide rises as the highest mountain in Spain (3718 m above sea level), and is the highest volcano in the Atlantic Ocean islands. There is a diverse variety of beaches in Tenerife, from golden sand to volcanic black, and mild temperatures (10–30 °C) across the whole year.

ExTech 2023 will be held at Pirámide de Arona Conference Centre, which belongs to the Mare Nostrum Resort. The conference centre, which is located in Playa de Las Américas (Arona), in the south of Tenerife, is one of the largest auditoriums in Europe and is equipped with different rooms and outdoor areas where the conference and related events will be held. There are many shopping centres, restaurants, and the best sandy beaches all to be found nearby.

The ExTech 2023 programme will highlight a wide range of technologies based on analytical separations and will cover recent improvements in analytical (micro)extraction, sample preparation techniques, and their hyphenation with chromatography, mass spectrometry, and related techniques.

The symposium is structured over four consecutive days starting with a full-day course on microextraction. This course will be followed by three days of plenary lectures, keynote lectures, oral communications (for both young and senior researchers), and vendor seminars. Professor Janusz Pawliszyn, Professor Stig Pedersen-Bjergaard (University of Oslo, Norway), Professor Jared L. Anderson (Iowa State University, USA), and Professor Marisol Cárdenas (University of Córdoba, Spain) are some of the highly recognized researchers that have confirmed their attendance and who will present plenary lectures. The full list of confirmed speakers can be found here: 

Poster sessions and vendor exhibitions will be hosted during the conference. To see a full list of the sponsors and collaborators of ExTech2023 visit: 

The scientific programme will be combined with a number of different social events, including a welcome cocktail, a gala dinner, and a trip to Mount Teide.

Please note the following important dates:

Deadline for poster presentations: 1 June 2023

The registration fee includes full access to the conference and exhibition, coffee breaks, and all social activities (including the gala dinner).

Articles

Events

The 25th edition of the International Symposium on Advances in Extraction
Technologies (ExTech) will be held in Tenerife (Canary Islands, Spain) from
18–21 July 2023. Here’s a glimpse of what attendees can look forward to.

ExTech 2023 Event Preview

Waters Corporation (Milford, Massachusetts, USA) has entered an agreement to acquire Wyatt Technology (Santa Barbara, California, USA), a company known for light scattering and field-flow fractionation (FFF), for $1.36 billion in cash. The deal is expected to be completed in the second quarter of 2023.

With the acquisition, Waters seeks to expand its offerings in biopharmaceutical development, particularly for newer modalities like cell and gene therapies. Approximately 80% of Wyatt’s revenue derives from tools for the analysis of large molecules. Wyatt scientists first commercialized online multi-angle laser light scattering instruments more than 40 years ago. Over the years, the company has added complementary technologies, such as well-plate-based dynamic light scattering and FFF for separating nanoparticles in solution. These techniques are used across biopharmaceutical discovery, product development, manufacturing, and quality assurance/quality control (QA/QC) to determine the critical quality attributes of novel therapeutics such as cell and gene therapies, vaccines, and proteins, as well as synthetic polymers and nanoparticles.

Waters estimates the market for bioanalytical characterization for new modalities, including cell and gene therapies, at $1.8 billion, with a projected annual growth of 10–12%.

Udit Batra, the president and CEO of Waters, noted that the two companies have similar goals. “We share a common mission to harness our technology and deep scientific expertise to increase the availability and affordability of life-changing therapies,” he said in a statement. “We look forward to welcoming the Wyatt team to the Waters family.”

Wyatt chairman and founder Philip Wyatt agrees. “For decades, we have seen first-hand how closely Waters’s and Wyatt’s scientific heritage, ethos, and values have been aligned,” he said in a statement. “Becoming an integral part of Waters is a natural way for us to expand our business dramatically.”

Wyatt is a privately held family company with 2022 revenues of approximately $110 million, and a global workforce of more than 200. Waters was founded in 1958, and has more than 8200 employees worldwide, with operations in more than 35 countries, including 14 manufacturing facilities.

Waters Corporation has purchased Wyatt Technology, expanding both parties' reach in biopharmaceutical development and creating better healthcare technology for all.

Waters Corporation Purchases Wyatt Technology in Billion-Dollar Deal

Shimadzu Corporation (Kyoto, Japan) has opened the Shimadzu Tokyo Innovation Plaza at KING SKYFRONT in the Tonomachi district of Kawasaki City, Japan, as a new location for the analytical and measuring instruments division. It will promote innovation for developing new analytical and measuring instrument applications, and offer state-of-the-art laboratory spaces to build relationships with research institutions and customers around the world.

Shimadzu opened its healthcare R&D centre for healthcare-related research in 2019 and opened a future collaboratory facility at the technology research laboratory site in 2022. The Shimadzu Tokyo Innovation Plaza will serve to strengthen Shimadzu’s software R&D capabilities for analytical and measuring instrument applications and specifying analytical conditions.

News

With Shimadzu Corporation's new location, the company hopes to innovate their research and technological efforts.

Shimadzu Opens Japanese Innovation Hub

Although the columns are the least expensive part of a gel permeation chromatography/size-exclusion chromatography (GPC/SEC) system, the quality of the results of a GPC/SEC analysis crucially depends on the performance of the column or column set applied. Low-performing columns reduce resolution. Even the addition of sophisticated and costly detection devices, such as online light scattering or viscosity detectors, cannot overcome the limitations resulting from poor column performance. The lifetime of a column is influenced by a variety of variables, such as column handling, the type of material injected, pressure drops, and back pressure, as well as the required resolution. As it is difficult to predict how long a column can be used for a particular application, column performance should be checked regularly. Determination of the number of theoretical plates provides an easy and cost-effective way to routinely control column performance.

Number of Theoretical Plates as a Measure of Column Performance

Gel permeation chromatography/size-exclusion chromatography (GPC/SEC) has become the method of choice for molar mass determination of macromolecules. To separate a macromolecular sample, a suitable combination of column material and mobile phase must first be identified, to ensure interaction of the analyte with the stationary phase is eliminated. In addition, the pore size distribution of the column filling must be chosen to match the hydrodynamic size distribution of the samples to be analyzed (1,2). Finally, the particle size must fit the anticipated separations. To reduce the risk of stress-induced elongation and degradation, larger particles should be applied when analyzing very high molar masses, while for the separation of oligomers, small particles will help to achieve high resolution.

While the pore size and pore size distribution of the packing determines the average volume by which two molar masses are separated, that is, the slope of the calibration curve, the resolution is also influenced by peak broadening occurring during the chromatographic experiment. Peak broadening is influenced by a variety of sources within the system. These include the cell volume of the detector, bad capillary connections between the different parts of the system, the injection volume, as well as in-column band broadening. In-column band broadening results from unequal pathways or unequal velocity streams of the molecules passing through the column.

A quantitative measure of peak broadening is the number of theoretical plates of the column or column combination. Typically, the number of theoretical plates at the time of production is provided on the manufacturer’s column certificate.

However, depending on the treatment of the columns, as well as on the type of samples and matrices injected, loss of column performance will occur over time. As the performance of a column changes during its lifetime, columns are regarded as consumables that need to be replaced once performance is not sufficient for the desired application.

Figure 1 shows the effect of band broadening (number of theoretical plates) on the separation of polystyrene oligomers. Clearly, the resolution of the different low molar mass oligomers decreases with the decreasing number of theoretical plates. This complicates not only quantitation of the different peaks but also affects determination of molar mass averages.

Thus, it is important to ensure that columns are in a suitable condition for the desired separation task. Plate count determination is well suited for this purpose. Regularly controlling column performance is a recommendation for GPC/SEC users, and it is also mandatory to national and international norms (3,4,5). Analysis in accordance with these norms often requires the column to have a minimum number of theoretical plates.

Calculating the Number of Theoretical Plates

Plate count can be conveniently determined by injecting a monodisperse low molar mass compound, determining elution volume and estimating the peak variance. To account for the fact that peak broadening increases with the length of the column, the number of theoretical plates of a column or column combination in GPC/SEC is usually normalized to 1 m column length (

 and σ are the elution volume and variance in units of volume, while 

Instead of the variance, the peak width at half peak height (

) are often used, as these are usually easier to measure than the variance itself. Whether 

 must be used depends on the norms that are applied. For example, ISO 16014-1 (3) requests using 

, while ASTM norm D 5296 – 97 (5) uses 

While application of equation 1 does not present a general problem, it is convenient to have routines for plate count calculations directly available in the data acquisition software. In addition, different equations should be implemented and associated with the respective norms. This allows the evaluation method required by the respective norm to be easily chosen, avoiding confusion and erroneous application of incorrect equations.

Figure 2 shows an example of how a plate count calculation might be set up in a data acquisition software. If signals from different detectors are acquired simultaneously—as is often the case in GPC/SEC—the choice of detector signal to be used for the band broadening calculations should be easily accessible. By selecting the norm, the correct equation is automatically applied, and the calculated results are directly compared to the requirements of the norm.

Good Practice of Tracking Column Performance

While plate count is usually assumed to characterize column performance, this is not completely true. As mentioned above, a variety of sources affect band broadening and, thus, the resulting number of theoretical plates. However, if there are no changes to the instrumental setup and experimental conditions, a loss in overall plate count can be regarded as loss of column performance and thus deceased resolution.

It is therefore good practice to check column performance after receiving a new column to ensure that no damage occurred during shipment and to document the initial condition. This test should be performed according to the test conditions supplied on the column certificate. Mobile phase, test analyte, flow rate, temperature, and column loading affect the number of theoretical plates, complicating comparison of the specified test results with own measurements if identical test conditions are not followed. However, if the experimental conditions are followed, leaving only differences in broadening resulting from tubing and instrument, a reasonable agreement between the results on the certificate and your own measurement should be achieved. This is sufficient to prove that the columns are in a suitable condition after arrival.

Once the plate count is determined for the new column or column combination, the shipping solvent can be replaced by the solvent used in the subsequent analysis. The replacement of solvent should follow the procedure recommended in the column manual to reduce the risk of column damage during this step. Once the column is equilibrated in the new solvent, column performance should be checked again, using suitable conditions for the eluent applied in the actual GPC/SEC analysis (see Table 1). The obtained number of theoretical plates now serves as a reference to which all subsequent plate count determinations can be compared. Plate count should be checked regularly and compared to the reference value to trace loss of column performance. Once the plate count has decreased by more than approximately 20%, a column replacement should be considered, especially for high resolution analysis.

It should be mentioned that plate count control does not necessarily require a separate measurement. If GPC/SEC is performed in the presence of an internal flow marker (6)—as requested in certain norms—the flow marker peak present in each run can be used to track column performance.

While the plate count measurement on column arrival should be performed using the conditions on the column certificate, plate count tracking should be done in the eluent applied for the actual GPC/SEC analysis, to prevent frequent solvent exchange.

Typical test conditions may use an injection volume of 20 μL (or less, if possible), whereas concentration should be adapted to the number of columns applied. For a single column, a concentration of 0.2 g/L usually provides a suitable chromatogram, while for two and three columns, concentrations of 0.5 g/L and 1 g/L might be used. The test material depends on the eluent and detector applied. Test materials that have been proven useful for refractive index (RI) detection in typical GPC/SEC eluents are presented in Table 1.

It should be mentioned that the number of theoretical plates is only one criteria for suitable analytical conditions. It informs only about the general ability of a column, column combination, or instrumental setup to be suitable for performing analyses. However, the number of theoretical plates does neither give information on whether the combination of stationary and mobile phase is suited for running a particular application, nor does the plate count inform on whether the pore size and pore size distribution are suited for the molar mass range to be analyzed.

GPC/SEC columns are consumables prone to loss of performance due to band broadening.

Increasing band broadening diminishes resolution.

Determining theoretical number of plates is an effective tool to ensure that the column is still applicable for the desired separation.

Different norms request different formulas for determination of plate count.

Appropriate test conditions should be applied depending on the GPC/SEC eluent used.

(1) Held, D. Select the Right Columns for Your Molar Mass Range. 

(2) Radke, W.; Held, D. Separation Range and Resolution. 

Plastics — Determination of Average Molecular Weight and Molecular Weight Distribution of Polymers Using Size-Exclusion Chromatography — Part 1: General Principles

 General Chapter 2.2.46. Chromatographic Separation Techniques (EDQM, Strasbourg, France, 2023).

Standard Test Method for Molecular Weight Averages and Molecular Weight Distribution of Polystyrene by High Performance Size-Exclusion Chromatography.

(6) Radke, W.; Held, D. Flow Marker—An Easy Concept to Increase Reproducibility. 

 studied polymer chemistry in Mainz, Germany, and Amherst, Massachusetts, USA, and is head of the PSS contract analysis department. He is also responsible for instrument evaluation and for customized trainings. PSS is now part of Agilent.

Tips & Tricks

Determining a theoretical number of plates is an effective tool to ensure that the column is still applicable for the desired separation.

Tips & Tricks: Checking the Performance of Your GPC/SEC Column

Commission regulation (EU) 2020/2388 amends Regulation (EC) 1881/2006 lowering maximum levels for a selection of perfluoroalkyl substances in food of animal origin to 0.2 µg/kg. This article describes automated solid-phase extraction (SPE) based on a weak anion-exchange sorbent and performed as an additional clean-up step and combined with liquid chromatography tandem mass spectrometry (LC–MS/MS). Cartridge wash with organic solvents reduced matrix effects considerably and quantification limits of 0.01–0.05 µg/kg were reached. Validation for meat, egg, and fish was performed in accordance with the EURL guidance document for per- and polyfluoroalkyl substances (PFAS) in food and feed.

The special physicochemical properties of per- and polyfluoroalkyl substances (PFAS) make them well suited for many household and industrial applications, as well as for a wide range of consumer products. PFAS have enjoyed widespread use, and their unique chemical properties make them difficult to break down. PFAS are ubiquitous. The lack of environmental degradation in combination with high solubility in water has resulted in a global distribution. PFAS are found not only in the environment but also in food and animal feed, in humans, and in wildlife. PFAS are toxic, and acute or long-term exposure could have detrimental health effects. Authorities worldwide are regulating their use and emissions into the environment (1,2). In addition, food and drinking water must be monitored for their presence.

An earlier publication in this magazine (3) demonstrated the potential of online solid-phase extraction (SPE) for the determination of PFAS in water in the context of the EU Drinking Water Directive (EU 2020/2184). Online SPE relies on small cartridges that can be eluted directly onto the high performance liquid chromatography (HPLC) column, enabling quantitative transfer of analytes to the analysis system. Extraction and enrichment of PFAS analytes from only 1 mL water allows quantification limits below 1 ng/L for all compounds listed in the directive (4). SPE improves the analysis not only based on the concentration factor but also by eliminating accompanying matrix compounds from the extract. The clean-up effect increases if the sorbent in the SPE cartridge differs from the one used in the analytical column. By using weak anion-exchange (WAX) resins, the SPE cartridges can be very efficiently washed with organic solvent after loading the sample.

This work investigates the possibility of reaching the low PFAS levels required by the EU commission regulation 2020/2388 (5) using online SPE–liquid chromatography–mass spectrometry (LC–MS) instead of direct injection when analyzing food extracts of animal origin. The fully automated sample preparation method used did not add to the overall analysis time once the first sample was injected into the HPLC system.

The automated system consisted of a MultiPurpose Sampler (MPS Robotic Pro, Gerstel) and an online SPE system (SPE

, Gerstel) coupled to an LC–MS/MS system (1290 Infinity II Pump and LCMS 6495C, Agilent Technologies). SPE elution was performed using 0.25% ammonia in methanol delivered from a separate isocratic HPLC pump (Infinity II 1260 Iso Pump, Agilent Technologies). The eluate was merged with the starting level buffer from the binary analytical pump in a valve fitted with a T-rotor located inside the SPE

system. The analytical column used for the online SPE–LC–MS/MS process was a 3 × 100 mm, 2.7-µm Poroshell 120 EC-C18 (Agilent Technologies). For direct injection, a 2.1 × 50 mm, 1.8-µm Zorbax Eclipse Plus C18 column (Agilent Technologies) was used. Between the binary pump and MPS, a 4.6 × 50 mm, 2.7-µm Poroshell 120 EC-C18 delay column (Agilent Technologies) was installed. For the extract cleanup, Gerstel SPE

 online SPE cartridges (Polymer Wax, Gerstel P/N 018804-023-00) were used.

All standards (Table 1) were purchased as solutions from Wellington Laboratories (distributed by Campro Scientific). Mixtures of isotopically labelled PFAS were used as internal standards for extraction and injection. Food samples (egg, meat, and fish) were processed in the following way: A 5 g sample, fortified with internal standard for extraction, was extracted twice with acetonitrile under alkaline conditions. After phase separation with sodium chloride, the combined organic phase was acidified with formic acid and frozen overnight. A first cleanup with dispersive SPE using MgSO

 and graphitized non-porous carbon was followed by evaporative concentration to 0.3 mL, and, after addition of internal standard for injection, brought to a final volume of 1 mL. Calibration in the range of 0.025–5 ng/mL (internal standards at 1 ng/mL) corresponds to 0.005–1 µg/kg in food.

The online SPE workflow consisted of initially conditioning the cartridge, first using 0.25% ammonia in methanol, then methanol, and finally water. After injection of the sample into the loop, it was loaded onto the cartridge using water, and the cartridge was then washed. These steps were all performed by the high-pressure dispenser (HPD) unit of the SPE

. Direct injection was performed using a second injection valve equipped with a 2 µL sample loop. One method with and one without cartridge wash were used to compare the extract clean-up efficiency. After the elution phase was completed, the chromatography was started and the binary pump delivered a gradient flow of 0.6 mL/min, employing water with 0.1% formic acid and methanol with 0.25% ammonia and 0.05% formic acid.

Detection was made in dynamic multiple reaction monitoring mode (dMRM). For each target compound and each isotope labelled internal standard, two MRM transitions were chosen, one quantifier and one qualifier (except perfluorobutanoic acid [PFBA] and perfluoropentanoic acid [PFPeA], for which only one transition had sufficient intensity).

In online SPE, elution is usually performed using a gradient delivered by the analytical pump. The WAX cartridges used in this work were eluted with ammonia in methanol delivered by a separate (isocratic) HPLC pump. The eluate was subsequently merged with the mobile phase at the starting level buffer strength delivered by the binary analytical pump. The chromatography on the analytical column was based on a reversed phase separation, with molecular interactions that were very different from the ionic interactions with the WAX cartridge. This allowed larger sample amounts to be injected without encountering matrix effects. An injection volume of 25 µL was used compared to 2 µL for direct injection. As a result, not only were the signals increased by a factor of 10 to 13 compared to direct injection but signal-to-noise ratios were also improved on the same scale. The example in Figure 1 shows mass traces for perfluorooctanesulfonic acid (PFOS) in egg resulting from direct injection and online SPE injection of the same extract. As can be seen in the qualifier trace, interferences were reduced in intensity with a retention time shift.

Acidic compounds were retained on the WAX cartridge by ionic interactions, which meant that the cartridge could be washed with organic solvents, resulting in the removal of most low and medium polar matrix components. Wash cycles with 300 µL of a mixture of 50:50:1 (v/v/v) acetonitrile–acetone–formic acid, 300 µL 0.01% formic acid in methanol, and 300 µL acetonitrile were used, respectively. Figure 2 shows total ion chromatograms with and without cartridge wash, demonstrating a considerable clean-up effect.

To investigate the matrix effects, method calibrations based on the individual sample types were performed in an identical manner and compared to method calibrations obtained from standards in solvent in the range of 0.05–1 ng/mL (corresponding to 0.01–0.2 µg/kg in food, based on a 5 g sample). All solutions were analyzed both by direct injection and online SPE, and both with and without cartridge wash. Some analytes showed considerably larger peak areas when cartridge wash was performed, indicating that matrix induced ion suppression was a factor.

Matrix calibration is not always possible and most often a solvent-based calibration is used, including a correction based on internal standards. If an isotopically labelled analyte is available, the relative response can be determined independent of possible matrix effects. Whenever the internal standard is only similar to the analyte, the relative responses can differ, and proper quantification is not necessarily possible. An example is perfluorohexadecanoic acid (PFHxDA), which was quantified using 

-PFTeDA. The calibration curves obtained for the three matrices were all different and they all differed from the calibration curve based on solvent standards (Figure 3, left). Washing the cartridge before elution reduced matrix effects and, as a consequence, the slopes of the obtained calibration curves were similar (Figure 3, right).

According to the EURL guidance documents (6), the limit of quantification (LOQ) represents the minimal concentration for which all quality criteria are met. Spiked samples at different concentration levels were analyzed in replicate to determine trueness and repeatability. Recovery of internal standards must be in the range 30–140%. As can be seen in Table 2, without cartridge wash the recovery of some compounds was very low (

-8:2 diPAP) due to matrix effects. The cartridge wash improved the recovery rate of these internal standards considerably, resulting in reduced variations. (Non-ionic analytes were removed from the cartridge during the wash procedure and could therefore only be analyzed without using cartridge wash.)

For a successful validation, repeatability and trueness must both be below 20%. As an example, validation results for egg using online SPE with and without cartridge wash are shown in Table 3. (More validation data can be found in reference 7.) As can be seen, for some compounds the validation was only possible when a cartridge wash was included. Most compounds were validated at levels as low as 0.01 µg/kg, with a few at 0.05 µg/kg. Due to blank values in the solvents used, for PFBA and PFPeA the LOQ was found to be lower without cartridge wash. N-Ethylperfluorooctanesulfonamide (N-EtFOSA) was validated at 0.5 µg/kg without cartridge wash.

Quantification limits were calculated for egg, meat, and fish based on determination with online SPE without and with cartridge wash. LOQs with cartridge wash were 0.01 µg/kg for most compounds, which was lower than the levels obtained without cartridge wash, and much lower than the levels reached by direct injection. Blank values introduced by the solvents used increased the LOQ for PFOA to 0.02 µg/kg and for PFPeA to 0.05 µg/kg. Without cartridge wash, the blank values for PFBA were lower, allowing a quantification limit of 0.05 µg/kg. LOQs of 0.5 µg/ kg were achieved for N-EtFOSA without cartridge wash, except when analyzing fish samples, in which N-EtFOSA was not quantified in the expected concentration range.

Online SPE–LC–MS/MS combined with the presented method enabled automated cleanup of food extracts and determination of PFAS compounds in the ng/kg range. Due to the clean-up effect of online SPE, the quantification limits compared to direct injection were significantly lower. The organic wash of the cartridges prior to elution effectively removed matrix interferences and improved the accuracy of the results. The method accuracy and trueness were demonstrated for different food types of animal origin (egg, meat, and fish). The main benefits compared to traditional SPE are simple sample handling, very low solvent consumption, and excellent reproducibility.

ECHA: European Chemical Agency, Per- and polyfluoroalkyl substances (PFASs).

https://echa.europa.eu/hot-topics/perfluoroalkyl-chemicals-pfas

United States Environmental Protection Agency, Perand Polyfluoroalkyl Substances (PFAS).

(3) Brandsch, T. Determination of PFAS in Water According to EU 2020/2184 and DIN 38407-42 Using Online SPE–LC–MS/MS. 

(4) Brandsch T.; Lerch, O. Determination of PFAS in Water According to EU 2020/2184 and DIN 38407-42 Using Online SPE–LC–MS/MS. 

(5) Commission Regulation (EU) 2022/2388 of 7 December 2022 amending Regulation (EC) No 1881/2006 as regards maximum levels of perfluoroalkyl substances in certain foodstuffs. 

https://eur-lex.europa.eu/eli/reg/2022/2388/oj

 EURL for Halogenated POPs in Feed and Food, Guidance Document on Analytical Parameters for the Determination of Per- and Polyfluoroalkyl Substances (PFAS) in Food and Feed. 

https://eurl-pops.eu/news/guidance-document-pfas/guidance-document-pfas

(7) Sauer, C.; Pleger, C.; Frenzel, T.; et al. Determination of PFAS in Food of Animal Origin Using Online SPE Cleanup and LC-MS/MS. 

is head of Department 2.5 at the Landesuntersuchungsanstalt für das Gesundheits-und Veterinärwesen (LUA) in Saxony.

is employed as a certified food chemist in Department 2.5.

is a food chemist and worked as part of her scientific thesis at LUA Saxony.

 holds the chair of Food Science and Consumer Goods at the Technical University Dresden.

 is head of automated sample preparation in the Innovation and Technology Department at Gerstel.

 works as an application scientist at Gerstel in the field of automated sample preparation for LC–MS.

Online SPE–LC–MS/MS combined with the method presented enabled automated cleanup of food extracts and determination of PFAS compounds in the ng/kg range.

Online Ion-Exchange Solid-Phase Extraction Cleanup for PFAS in Food of Animal Origin

Mineral oil hydrocarbons (MOH) are widely used as lubricants and may contain carcinogenic and mutagenic impurities. Hence, food safety authorities require that ingredients, finished products, and packaging materials be tested. Comprehensive analysis of MOH utilizes a combined liquid (LC) and gas chromatography (GC) procedure, which is challenging and time-consuming. This article demonstrates that automated headspace-selected ion flow tube mass spectrometry (SIFT–MS) analysis has potential to screen large numbers of packaging samples—over 220 per day—for the volatile MOH fraction, providing a rapid indication of packaging material contamination. Moreover, SIFT–MS can simultaneously quantify benzene contamination—addressing this recently identified need for personal care products (PCPs).

Polymers are synthesized by polymerization of low-molecular-weight organic compounds, and therefore monomer residues and other volatile by-products can be trapped in the polymeric material. Recycled polymers may contain additional volatile impurities that have migrated into the material during prior use and/or that were generated through the recycling process. Determination of the identities and levels of volatile impurities is important for manufacturers planning to use recycled polymeric materials in packaging materials—whether of pharmaceutical products, foods, or personal care products (PCPs)—since they can migrate through the polymer into the product.

For food contact materials (FCMs), the so-called “MOSH and MOAH” analysis (mineral oil saturated hydrocarbons and mineral oil aromatic hydrocarbons, respectively) for mineral oil hydrocarbon (MOH) content is widely utilized because packaging is suspected of being a major source of these impurities (1). MOH is an extremely complex mixture of hydrocarbons and tends to elute from standard chromatographic analyses as a broad band, rather than as individually resolved components (1,2), so the test reports total MOSH and total MOAH content for hydrocarbons in the C

 range. Highly sophisticated, automated sample preparation and analysis solutions comprising both liquid (LC) and gas chromatography (GC) steps have been developed with a throughput of up to two samples per hour (Figure 1). This article explores the potential application of selected ion flow tube mass spectrometry (SIFT–MS), a direct-injection MS technique, for pre-screening polymer packaging materials for volatile MOSH and MOAH based on the demonstrated ability of SIFT–MS to analyze headspace samples at a throughput of 12 samples per hour (3) (Figure 1). Furthermore, headspace-SIFT–MS analyzes benzene at high sensitivity as part of the same analysis, addressing one facet of the emerging need to reduce benzene content in PCPs (4). In this study, high-density polyethylene (HDPE) and polypropylene (PP) systems are evaluated as representative polymeric systems.

The SIFT–MS technique is described in detail elsewhere (5). Briefly, rapidly switchable reagent ions (H

) were utilized for gas-phase soft chemical ionization of trace volatile organic compounds (VOCs) in air and headspace. Real-time, high-throughput analysis was achieved because SIFT–MS is chromatography-free. Selectivity was achieved through the combination of multiple ionization mechanisms and mass spectrometric detection. A SIFT–MS instrument was used in this work (Voice200

Automated headspace-SIFT–MS analysis (3) was achieved using a multipurpose autosampler (MPS Robotic Pro, Gerstel). Headspace was sampled using a 2.5-mL headspace syringe (heated to 150 °C) and subsequently injected at a flow rate of 50 μL/s into the SIFT–MS instrument’s autosampler inlet (heated to 150 °C) via a self-sealing septumless sampling head (Gerstel). Since the nominal sample flow into the SIFT–MS instrument is 420 µL/s, a make-up gas flow (ultra-high purity nitrogen) was also introduced through the sampling head.

In this study, full-scan data were collected for each sample in a single analysis within 40 s using all three positively charged reagent ions. For both MOSH and MOAH components, headspace concentrations for compounds with carbon numbers up to C

 were calculated from these data using a method described recently (6). Briefly, the benzene alkyl derivatives were targeted as representative of the MOAH class. The naming convention employed here for aromatic species refers to the number of carbons in the side chains. For example, the total concentration measured for the sum of ethylbenzene and the xylene isomers is referred to as “C

-alkylbenzenes”. The MOSH class was targeted via alkanes containing 10 to 16 carbon atoms (C

). Each measurement represents a total of the alkanes of a given carbon number (for example, “C

Tables 1 and 2 summarize the HDPE and PP samples, respectively, that were used in this study. A variety of virgin and recycled products were analyzed (1 g in 20-mL sample vial; 10 replicates per sample) in randomized order and with interspersed blanks (every 10 samples) for the two data collection events (one for each polymer type). Samples were incubated at 80 °C for 20 min.

Figure 2 summarizes the results obtained from reprocessing SIFT–MS full-scan data obtained for the 14 HDPE and seven PP samples. The MOSH and MOAH components lie within the original acquisition range (up to 250 

). For each type of polymer, the contributions for benzene and the other sub-MOAH aromatics are shown separately. For the alkanes, the C

 contributions for HDPE and PP, respectively, are summed separately (purple in Figure 2) from the other carbon chain lengths (pink) to distinguish between the alkane contributions arising from monomer building blocks (ethylene and propylene) and alkanes from other sources. Volatile MOSH and MOAH concentrations were easily determined using SIFT–MS. Although the recycled HDPE samples generally had the largest MOSH and MOAH concentrations, a PP sample (P-R4) was the worst overall (it corresponded to “worst-case” post-consumer recyclate, whereas P-R3 was “best-case”). For HDPE and PP, respectively, Tables 1 and 2 rank the total volatile MOSH and MOAH emissions. Compared to total volatile emissions, these rankings differ due to the presence of non-MOSH/MOAH volatile residues. Volatile MOSH and MOAH emissions from virgin polymer samples were dominated by the C

 alkanes for HDPE (Figure 2[a]) but show quite different abundances—with the highest emissions from the scientific product (sample H-V4). In contrast, recycled HDPE samples had quite different MOSH/MOAH profiles. First, there was a significant non-C

 presence, which—based on the limited sample set studied here (Table 1)—suggests that these arise from degradation in the cleaning and extrusion process and/or residual contamination from prior use. Aromatic hydrocarbons also appear at significant levels in recycled HDPE. Unless these residues arise from degradation of additives during recycling, their origin appears to be from prior use. The aromatics were present over a broad range of carbon numbers, since the common solvents (C

-alkylbenzenes in mineral turpentine) and higher aromatics (C

-alkylbenzenes; low molecular mass MOAH) both occurred at significant concentrations.

For PP (Figure 2[b]), the distinction between virgin and recycled products was less clear—at least for this limited sample set. In addition to C

 alkane residues, both virgin and recycled PP had significant concentrations of alkanes that were not multiples of the monomer unit (C

). This appears to be as a result of polymer synthesis, so the alkanes do not assist authentication of virgin product. Volatile MOAH residues (C

-alkylbenzenes) occurred in all recycled products and in one virgin product (craft; P-V2). Hence the volatile MOAH analysis may be useful for authenticating high-grade virgin PP versus low-grade virgin and recycled products. Due to benzene’s deleterious health effects, there have been recent concerns about its detection in numerous PCPs (4). In these polymer samples, although benzene content is visible in Figure 2 only for samples H-R5 and H-R7, benzene was present at trace levels in many samples (Figure 3). Only virgin HDPE and one recycled HDPE (H-R6) were essentially free of benzene. The levels in several recycled HDPE samples were high, whereas although all PP samples have benzene residue, concentrations were at the lower end of the recycled HDPE samples. The results obtained for the recycled HDPE samples were of concern since these samples were being evaluated for use in consumer product packaging. It is clear from these data that recycled HDPE, in particular, and recycled PP should be screened for benzene content prior to reuse.

The increased use of recycled plastic in consumer packaging means that increased testing of volatile residues is required. This study has demonstrated that SIFT–MS can rapidly screen polymeric materials for volatile MOSH and MOAH residues. For HDPE, in particular, an increase in MOAH was observed after polymer use and recycling compared to virgin HDPE. With a throughput of over 220 samples per day (not including standards and blanks), automated SIFT–MS analysis has the potential to pre-screen samples for volatile MOSH and MOAH prior to more expensive LC or GC analysis.

Furthermore, SIFT–MS analysis can quantify benzene impurities at high sensitivity, protecting PCPs, as well as pharmaceuticals and food products, from contamination. This study has demonstrated that benzene contamination is a significant risk factor in the use of recycled HDPE and should be addressed through increased testing. Automated SIFT–MS analysis has the potential to provide enhanced quality control through faster analysis and simplified workflows, while supporting sustainability initiatives.

(1) EFSA Panel on Contaminants in the Food Chain (CONTAM). Scientific Opinion on Mineral Oil Hydrocarbons in Food. 

Guidance on Sampling, Analysis and Data Reporting for the Monitoring of Mineral Oil Hydrocarbons in Food and Food Contact Materials

; Bratinova, S.; Hoekstra E., Eds.; Publications Office of the European Union, 2019. DOI:

(3) Perkins, M. J.; Langford, V. S. Application of Routine Analysis Procedures to a Direct Mass Spectrometry Technique: Selected Ion Flow Tube Mass Spectrometry (SIFT-MS). 

(4) Bettenhausen, C. A. Finding Benzene Everywhere We Look. 

(5) Smith, D.; Španěl, P.; Demarais, N.; Langford, V. S.; McEwan, M. J. Recent Developments and Applications of Selected Ion Flow Tube Mass Spectrometry (SIFT-MS). 

(6) Perkins, M. J.; Langford, V. S. Simple, Rapid Analysis of Packaging for Volatile MOSH and MOAH Contaminants. 

 is a principal scientist at Syft Technologies in New Zealand. He joined Syft in late 2002 after completing his Ph.D. in physical chemistry at the University of Canterbury, and postdoctoral fellowships at the Universities of Geneva, Western Australia, and Canterbury. He has over 30 peer-reviewed publications on a wide range of SIFT-MS applications, and has contributed numerous conference papers.

 is a senior applications chemist and SIFT-MS expert at Element Materials Technology (formerly Anatune), based in Cambridge, United Kingdom. Mark graduated from the University of Southampton, UK, with a Ph.D. in electrochemistry. He was with the Malaysian Rubber Board’s UK research centre for 12 years, first as a senior analyst, then as head of the analytical section. He joined Element in early 2015 in a role that supports and expands the analytical capability of SIFT-MS—with a particular focus on autosampler integration and the development of automated test methods.

Cover Story

SIFT–MS analysis has potential to screen large numbers of packaging samples for the volatile MOH fraction, providing a rapid indication of packaging material contamination.

High-Throughput Analysis of Polymers for Benzene and Volatile MOSH and MOAH Residues

This month we interview Petr Vozka from the California State University in Los Angeles, USA, about his work developing methods for analyzing products from plastic waste conversion processes and organic compounds adsorbed on microplastics using two-dimensional gas chromatography (GC×GC).

Vozka, P. Quantitative Analysis of Aliphatic Olefins in Fuels made from Plastic Waste by Comprehensive Two-Dimensional Gas Chromatography. Paper presented at the 14th Multidimensional Chromatography Workshop, Liege, Belgium, 2023.

 is an assistant professor of analytical chemistry in the Department of Chemistry and Biochemistry at the California State University, Los Angeles, USA. He is also the director of the Complex Chemical Composition Analysis Lab (C

AL). His research focuses on characterizing complex chemical mixtures via state-of-the-art techniques, such as two-dimensional gas chromatography (GC×GC) and high‑resolution mass spectrometry (HRMS). His primary focus is on developing methods for analyzing products from plastic waste conversion processes and organic compounds adsorbed on microplastics. He has one patent, six military reports, 25 journal publications, and over 30 research presentations, which include 10 invited lectures and invited presentations. He was invited as a keynote speaker to the 14th Multidimensional Chromatography Workshop in 2023.

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Features

Rising Stars of Separation Science: Petr Vozka

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