Analytical chemistry is an important tier of environmental protection and has been traditionally linked to the assessment of the environmental quality status of systems. Although essential, analytical chemistry may also contribute to further environmental problems mainly due to the high energy demands and large quantities of hazardous substances that may be used or generated throughout an analytical procedure. These two distinct and contradictory roles of analytical chemistry were highlighted by Paul Anastas a year after the introduction of green chemistry (1), when the concept of green analytical chemistry (GAC) was defined as an emerging area, relevant to the research arena and commercial sector. At that time, traditional sample preparation methods were identified as a major source of the total negative impact of analytical methodologies on the environment and their replacement with contemporary ones was considered central in settling greener analytical methods. Indeed, early sample preparation methodologies were tedious, time-consuming, and, more importantly, expended large quantities of resources that resulted in the generation of hazardous laboratory waste.

In 2013, the concept of GAC was formulated in the form of 12 principles that expressed the willingness to care for the environment and human safety as part of the development and application of analytical procedures (2). The introduction of GAC aimed to redefine and reevaluate analytical methods by addressing safety of solvents/reagents, toxic laboratory waste generation, workers’ safety, and energy efficiency. In the formulation of GAC, the first principle suggested applying direct analytical techniques to avoid sample preparation and also concluded that any “green” action taken during the sample preparation step (for example, minimal use of energy, safety for operator, use of non-toxic reagents or reagents from renewable source) would have a negative impact on accuracy, precision, selectivity, sensitivity, and detectability of the analytical process. This was not a well‑reflected assumption, especially when considering the analytical performance of mature and green sample preparation technologies available at that time (for example, the solventless and reagentless solid-phase microextraction [SPME]). The use of direct analysis may be a straightforward approach to address problems related to sample preparation. However, to meet sensitivity needs and overcome matrix-related problems, the use of sophisticated, expensive, and energy‑consuming instrumentation is required that generally shifts the environmental impact from sample preparation to the determination step. More importantly, direct analysis is not always an option and a step of sample cleanup, analyte enrichment, or analyte conversion into a form suitable for analysis is commonly needed. In other words, sample preparation remains a key step in analytical procedures.

The first principle of GAC was commonly misinterpreted and created the false impression that omitting the sample preparation step is a green approach, fully neglecting the “green” technological advances in the field. The “exclusion” of sample preparation from GAC also created a gap by not considering cases where direct analysis was not an option. Instead of neglecting this step, efforts should have been devoted to fully defining sample preparation within the context of green chemistry and GAC. Over the years, redefining sample preparation to address sustainability issues and promote the practice of green sample preparation (GSP) has become a necessity. After all, green chemistry was never about what to stop 

doing, but was always about invention and the things one can do better.

Earlier this year, the concept of GSP was proposed (3). It was formulated in the form of 10 principles that represented a road map towards the development of overall greener analytical methodologies (Figure 1). This set of principles represented the optimum number of characteristics needed to describe the inner structure of the GSP concept, its properties, and function mechanism. The 10 principles were not isolated but formed an integrated system of design (Figure 1), where improvements achieved by aligning to the fulfilment of a given principle could synergistically help to reduce the deficiencies associated with other interconnected principles. GSP set goals that were common to GAC but also had several distinctive and innovative features. In every case, the GSP approach put sample preparation at centre stage and translated greenness based on the needs and requirements of sample preparation.

The aspects considered by GSP included the use of safe solvents/ reagents; materials being reusable and from renewable, recycled sources, minimizing waste generation and energy demand; minimization of samples, chemicals, and materials; procedure simplification and automation; operator’s safety; and preparing a high number of samples per unit time. Based on the advances in sample preparation, several contemporary and mature sample preparation technologies align with the principles of GSP and fulfil the requirements for greening this key step in analysis. It is equally important to note that the adoption of these methods in the laboratory not only aligns with the principles of GSP but also assists in improving the analytical characteristics of the overall method. The latter contrasts with the GAC approach that faces the challenge of reducing the environmental impact of methods without negatively impacting the analytical efficiency of the method, that is, sensitivity, selectivity, accuracy, precision, robustness, and, in turn, the quality of the analytical information obtained.

Current environmental challenges are of a global scale, highlighting the urgent need to align with pollution abatement and the principles of sustainable development. Analytical chemists face increasingly complex interrelated problems both on-site and at the laboratory and the application of environmentally benign analytical practices has become a critical factor to consider. The adoption of contemporary sample preparation practices with a low environmental impact should therefore be a priority for all researchers, practitioners, and routine analysts. Greening analytical methods is directly connected to greening the sample preparation step. In other words, there is no green like more green.

This article is based upon work from the IUPAC project No 2021-015-2- 500 “Greenness of official standard sample preparation methods” and work from the Sample Preparation Study Group and Network, supported by the Division of Analytical Chemistry of the European Chemical Society.

2) A. Gałuszka, Z. Migaszewski, and J. Namieśnik, 

3) Á.I. López-Lorente, F. Pena-Pereira, S. Pedersen- Bjergaard, V.G. Zuin, S.A. Ozkan, and E. Psillakis, 

is full professor in water chemistry at the School of Chemical and Environmental Engineering, Technical University of Crete, Greece.

is a professor in the Department of Pharmacy, University of Oslo, Norway, and Department of Pharmacy, University of Copenhagen, Denmark.

is a full professor of analytical chemistry at Ankara University, Faculty of Pharmacy, Department of Analytical Chemistry in Turkey.

Articles

In this extended special feature to celebrate the 35th anniversary edition of LCGC Europe, key opinion leaders from the separation science community explore contemporary trends in separation science and identify possible future developments.

Separation Science: The State of the Art: Analytical Chemistry: There is No Green Like More Green

In 2017 I had the privilege of taking part in a panel discussion focused on gas chromatography (GC) led by Pat Sandra to celebrate the 30th 

anniversary and “The State of the Art”. Top experts in GC were asked to comment about the current developments, limitations, and future perspectives of GC and related techniques (fast‑GC, micro-GC [μGC], heart-cutting multidimensional GC, and comprehensive two‑dimensional GC [GC×GC]) (1).

On multidimensional GC and, in particular, about GC×GC, I was probably the most optimistic about the actual strength of the technique for the investigation of complex samples and its potential for providing answers to complex questions. At that time my feeling was that we were in an “induction” period, with “many chromatographers approaching the technique and evaluating the potential benefits it could bring to their applications” (1). Moreover, I was fully convinced—and still am now—that all the efforts required to optimize a GC×GC method are worthwhile because the advances in data processing open up new possibilities to fully exploit the available data. The payback for these efforts is a new perspective on Nature’s complexity and a better understanding of complex phenomena. These thoughts were recently put in words by Phil Marriott—one of the top experts in the field; I suggest interested readers get inspiration from his contribution, which is well summarized by this statement: “If you are not using GC×GC, you will never know what you are missing!” (2).

After five years, if we consider the place and the space GC×GC has taken in many applications, we can say that things went in the right direction and my optimistic thoughts 

were rewarded. Out of this induction period, we are experiencing an “exponential” evolution in hardware and software development. Many of the criticisms of the technique in the past have been overcome or solved, and workflows have been developed and automated to solve specific problems. These solutions have been possible because of the synergies between all the key players: academia, private companies, and instrument manufacturers. Application problems have been turned into drivers for new hardware development and more intuitive software solutions.

Instrument manufacturers, directly or with their solution partners, offer a full portfolio of hardware tools. Thermal modulation, with or without cryogenic fluids (CO2 or liquid N2), represents the gold standard in terms of efficiency and resolution (3). Available solutions cover “fully equipped” instruments or “add-on” modulators for the upgrading of existing one-dimensional (1D)-GC to GC×GC platforms. Moreover, for high-throughput analyses in control or industrial laboratories, flow modulation with different principles of operation (differential-flow modulation [4] and multi-mode modulation [5]) offers suitable performance, robustness, reliability, and cost-effectiveness. With software-assisted procedures, even the translation of methods from thermal to flow modulation is possible (6), facilitating the application transfer from R&D to control laboratories.

Mass spectrometry (MS)—high or low-resolution—is the most common detector in combination with GC×GC. Providing orthogonal information about analyte identity and amount present, it is fundamental for the accurate interpretation of the chemistry behind many phenomena. In those applications where the confirmatory role of MS is not mandatory, single‑channel detectors such as the flame ionization detector (FID) are optioned, providing a wider linearity range of responses and quantification options without the need for external calibration, for example, by response factors (7).

However, hardware advances and market consolidation of the GC technique should be accompanied by equivalent efforts in the data processing. If the advantages of comprehensive two-dimensional (2D) chromatography are clear to most GC users—improved efficiency, resolution, separation power, ordered retention logic—the change of mind required for data processing and interpretation— from profiles to fingerprints—has been the barrier some could not overcome.

As a passionate user and convinced supporter of GC×GC, I must say that the key to unlocking the deserved success of the technique is to help analysts access the data with intuitive and efficient tools.

In my interaction with applied research units in food manufacturing companies, they are often highly resistant to analytical innovation. They are open to new tools if they are related to food safety risks, if a complex measurement is establishing the safety compliance. Food analysis should be fast, simple, informative, and reliable enough to provide answers to multifaceted questions, for example, is my product compliant with the reference? Is my primary material of suitable quality? Is the new processing technology improving sensory acceptability? Is climate change impacting crop quality? Each of these questions refers to complex (biological) phenomena where informative markers and decision-making tools are not just single but complex patterns of analytes.

In this context, which shares common features with many other application areas—such as petroleomics, metabolomics, environmental analysis, and flavour and fragrance—GC×GC represents the innovation we all need(ed) to take a step ahead supporting innovation, safety, and quality of food.

I see great potential in the application of artificial intelligence (AI) concepts and tools at the data processing level, for data mining, and even applied to the global method workflow.

Computer vision, for example, is a field of AI where comprehensive two-dimensional chromatography can take tremendous benefits. It is defined as “a field of artificial intelligence that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs—and take actions or make recommendations based on that information. If AI enables computers to think, computer vision enables them to see, observe, and understand“ (8). Luckily we have software tools that have been developed in full alignment with this definition (9). Pixel-based approaches for prompt visual comparisons, peak-region features, and tile-based Fisher-ratio analysis for fingerprinting are all new data processing tools capable of “seeing” compositional differences and support the “understanding” of discriminant patterns of chemicals between samples (9). As for biometric fingerprinting, pattern recognition algorithms give access to a higher level of information; in forensics, we identify individuals based on a fingertip identification, in analytical chemistry we capture chemical diversity and interpret phenomena.

Another intriguing application of AI is in the sensomic area. The 

concept of sensomic-based expert system (SEBES) (10) has recently been introduced and this predicts key aroma signatures of food without using human olfaction—an AI-smelling machine. In practice, SEBES is a workflow capable of extracting, isolating, and quantifying key food odorants (KFO), those responsible for the sensory features that shape food sensory “identity” (11). By capturing KFO signatures, we enable our systems to smell like a human nose and our analytical workflows to screen for hundreds of samples without any fatigue. Not surprisingly—at least for us—GC×GC is the core platform of SEBES, and it can be fully automated for many food products, for example, extra-virgin olive oil aroma blueprint (12), raw hazelnuts spoilage (13), and cocoa and chocolate aroma quality (14).

In conclusion, GC×GC offers the chance to approach Nature’s (chemical) complexity by more accurately delineating piece by piece all of its parts; we do not need to simplify measurements because we make the way we look at it easier. For this reason “the full potential of GC×GC was probably not clear at its introduction, but its widespread adoption in different areas and the infusion of strategies and concepts from other disciplines, have definitely highlighted its central role of missing technique: from a technique that did not exist…to a technique that was missing” (15).

Finally, I would like to thank my mentor, Carlo Bicchi, for his inspiration and scientific contribution to multidimensional GC.

1) P. Sandra, S. Lehotay, H.-G. Janssen, C. Cordero, F. David, and J. Hinshaw, 

3) P.Q. Tranchida, G. Purcaro, P. Dugo, L. Mondello, and G. Purcaro, 

4) J.V. Seeley, N.J. Micyus, S.V. Bandurski, S.K. Seeley, and J.D. McCurry, 

5) J.V. Seeley, N.E. Schimmel, and S.K. Seeley, 

6) C. Cordero, P. Rubiolo, S.E. Reichenbach, A. Carretta, L. Cobelli, M. Giardina, and C. Bicchi, 

7) F. Stilo, E. Gabetti, C. Bicchi, A. Carretta, D. Peroni, S.E. Reichenbach, C. Cordero, and J. McCurry, 

8) What is Computer Vision?, (n.d.): https:// www.ibm.com/topics/computer-vision (accessed 25 October 2022).

9) F. Stilo, C. Bicchi, A.M. Jimenez- Carvelo, L. Cuadros-Rodriguez, S.E. 
Reichenbach, and C. Cordero, 

10) L. Nicolotti, V. Mall, and P. Schieberle, 

11) A. Dunkel, M. Steinhaus, M. Kotthoff, B. Nowak, D. Krautwurst, P. Schieberle, and T. Hofmann, 

12) F. Stilo, E. Alladio, S. Squara, C. Bicchi, M. Vincenti, S.E. Reichenbach, C. Cordero, and H.R. Bizzo, 

13) S. Squara, F. Stilo, M. Cialiè Rosso, E. Liberto, N. Spigolon, G. Genova, G. Castello, C. Bicchi, and C. Cordero, 

14) F. Magagna, A. Guglielmetti, E. Liberto, S.E. Reichenbach, E. Allegrucci, G. Gobino, C. Bicchi, and C. Cordero, 

15) F. Stilo, C. Bicchi, S.E. Reichenbach, and C. Cordero, 

is full professor of food chemistry in the Dipartimento di Scienza e Tecnologia del Farmaco, University of Turin, Turin, Italy.

is a retired professor of pharmaceutical biology at the University of Turin.

Separation Science: The State of the Art: Multidimensional Gas Chromatography Moves Forward

The development of multidetection field-flow fractionation (FFF) has made a global impact on the research and development of advanced separation and analysis of novel, supramolecular, and complex polymers. Owing to their multiple functionalities and applications in advanced nanotechnology, the accurate and reliable characterization of advanced materials is essential for both the material design and development processes. As highlighted in Figure 1, the utility of FFF, namely asymmetrical-flow FFF (AF4), hollow-fibre-flow FFF (HF5), and thermal FFF (ThFFF), has been instrumental in extending the frontiers for the separation and analysis of supramolecular and complex polymers (1). These FFF subtypes have the ability to separate at low‑shear conditions as a function of distinct separation force-fields across a flat ribbon-like channel with a laminar and parabolic solvent flow-profile. Examples of force-fields are a thermal gradient and a cross-flow stream, applicable for ThFFF and AF4/ HF5, respectively.

Essential AF4/HF5 research avenues focus on the deep understanding and elucidation of structural transformations within complex macromolecular samples depending on different parameters, such as molar mass, cross-linking, pH, and concentration. Here, we are using the power of multidetection to provide a large amount of information within a single measurement. We consider a variety of parameters that describe the molecular shape in dilute solutions, such as the scaling or Mark-Houwink exponent, as well as the ratio of the hydrodynamic radius (

g) (shape parameter). Additionally, apparent density, which is molar mass-dependent, aids in validating the conformational data. Particularly noteworthy is the AF4-5D (quintuple detection consisting of multi-angle light scattering [MALS], dynamic light scattering [DLS], refractive index [RI], UV, and viscometry) applicable for evaluating the internal folding process of single-chain nanoparticles (2). Here we demonstrate that increased internal cross-linking density results in higher compactness.

Continuously improving AF4 protocols for in-depth vesicle characterization (polymersomes [3] and exosomes [4]) are of the utmost importance to understanding structural transformations dependent on loading or modification processes. Here, it is possible to get quantitative and qualitative information, as well as the locus of the encapsulated drug or protein, which helps in optimizing the loading or modification processes. AF4 elucidates the intra- and intermolecular interactions between various types of fragile nanostructures (the combination of polymers, proteins, nanoparticles, and/or enzymes) and their conformational effects (5).

A single measurement can provide even more information when coupling state-of-the-art quintuple-detection to ThFFF. In addition to molar mass, size, shape, apparent density, and intrinsic viscosity, we can also separate according to microstructure, topology, and composition owing to the thermophoretic properties of the analytes.

Regarding ThFFF’s capability in the characterization of polymers, great advances have been made to transform 

from an empirical trial‑and‑error procedure to a targeted theory‑based method, including retention predictions (6). Furthermore, ThFFF has evolved its potential to act as a complementary tool for branching or topology characterization, as shown recently for aromatic-aliphatic polyester (7) and chain-walking polyolefins (8). This sets the basis for ThFFF to be a promising branching characterization tool for polyolefins.

ThFFF has also shown its potential in the characterization of polymeric nanoreactors (9). A new trend in the development of ThFFF is the characterization of metal-polymer hybrids for subsequent exploitation of their plasmonics as highly sensitive electromagnetic probes for investigating size, shape, and composition dynamics with higher resolution. When exposed to electromagnetic irradiation, metal nanoparticles exhibit highly sensitive and intensive plasmonic behaviour as a function of shape, size, and composition, and this is analyzable with higher reliability using advanced UV–vis spectroscopy coupled to ThFFF.

2) J. Engelke, S. Boye, B.T. Tuten, et al., 

4) S. Lathwal, S.S. Yerneni, S. Boye, et al., 

5) B. Kaupbayeva, H. Murata, K. Matyjaszewski, et al., 

6) M. Geisler, L. Plüschke, J. Merna, et al., 

7) W.C. Smith, M. Geisler, A. Lederer, et al., 

8) M. Geisler, W.C. Smith, L. Plüschke, et al., 

9) U.L. Muza, G. Greyling, and H. Pasch, 

is senior scientist at the Polymer Separation Group and leader of Field-Flow Fractionation and Thermoanalysis, Center Macromolecular Structure Analysis, Leibniz- Institut für Polymerforschung Dresden e.V., Germany.

is a Marie Sklodowska-Curie Actions_ Individual Fund_Fellow (postdoctoral) at the Polymer Separation Group, Center Macromolecular Structure Analysis, Leibniz-Institut für Polymerforschung Dresden e.V.

is a postdoc at ThieleLab Group, Department Nanostructured Materials, Leibniz-Institut für Polymerforschung Dresden e.V.

is leader of the Polymer Separation Group, head of Center Macromolecular Structure Analysis, Leibniz- Institut für Polymerforschung Dresden e.V., and SASOL chair in Analytical Polymer Science at Stellenbosch University, South Africa.

Separation Science: The State of the Art: Field-Flow Fractionation: Extended Frontiers to Supramolecular and Complex Polymer Materials

Columns packed with chemically optimized stationary phase particles are the workhorse of liquid chromatography (LC) analysis. Despite the decades of work spent in optimizing particle manufacturing and column packing procedures, we still lose about 50–60% of their separation potential to the random nature with which these particles are being packed. What if we could three-dimensionally (3D)-print these particles in ordered packing layers?

It is by now very well-known that the infamous eddy dispersion wastes more than half of the number of theoretical plates 

that state‑of‑the‑art high performance liquid chromatography (HPLC) columns would be able to produce. This has been demonstrated in a number of computational studies studying the band broadening in ordered sphere packings, as these represent the ultimate degree of eddy dispersion elimination (1,2). Roughly speaking, reduced plate heights can be reduced from around h = 1.9–2 (fully particles) to around 0.8–1.0 near the optimum, while at 4× the optimal flow rate of the random packed bed gains already amount up to a factor of 3 to 4.

A first solution to produce chromatographic beds with a perfectly ordered structure are pillar-array columns (3). These are produced using state-of-the-art micromachining to produce silicon pillar arrays that are subsequently electrochemically anodized to produce a mesoporous outer shell. Because of their high efficiency, pillar-array columns have rapidly 

grown into the column of preference for many key players in the proteomics area (4,5). Limitations of the production method are the small scale of the produced micro‑arrays, typically only suitable for the nano-flow format, although recently some new designs targeting the micro- and capillary-flow regimes have been proposed. Because the etching process is unidirectional, only 2.5D-beds (pillar arrays) can be produced. This implies the top and bottom surfaces of the channel inevitably induce an extra velocity gradient, extending its effect across the entire channel depth. This in turn generates an additional degree of dispersion not present in 3D beds. In addition, and more importantly, the number of available stationary phases is limited, since pillar-array columns are currently a single-vendor product. This poses a considerable hurdle to their widespread use, as analysts—especially those in the pharmaceutical industry—have many good reasons to stick to the stationary phase and even the specific brand their original methods have been developed with.

The above implies there remains a strong impetus to produce ordered 3D beds, preferably making up a monolithic body of a suitable mesoporous material (silica, some polymer types). When contemplating the possibility of producing ordered 3D packings, the first technology that comes to mind is 3D-printing. However, most of the available 3D-printing methods (filament printing, stereolithography, digital light processing, inkjet/polyjet [i3DP] printers) do not offer the required ultra-small printing resolution (which is needed to produce a packing structure suitable for analytical chemistry, see below). Up to this point, 3D-printing in liquid chromatography has therefore been limited to printed devices targeting, at best, the preparative‑scale (6), where packing structure sizes in the 20 μm range are on the verge of being competitive. Other 3D-printing projects have been even more modest and only aimed at printing the exterior column housing (7). The only 3D-printing approach enabling the sub-micrometre printing resolution required for analytical liquid chromatography is two-photon polymerization (2PP) (8). As this approach requires the simultaneous 

absorption of two instead of only one photon to activate the photo‑initiator molecules, and, as the probability for such an event is only high enough in the central portion of the focal spot, resolutions below the wavelength of the light can be achieved. Using tailored monomer mixtures, voxel (=”volumetric pixel”) sizes as small as 200 nm can be printed using 2PP, which is small enough to print structures with 0.6 μm through-pores without suffering from excessive pore-to-pore shape and size differences. This pore size is comparable to the through-pore in a 2 μm particle-packed column, as is needed to be competitive with these columns. However, these very small voxel sizes inevitably also come at the expense of very low volumetric printing speeds. In a recent study (8), we showed the main drawback of this approach is that the printing process is inherently slow, requiring several 100’s of hours (!) to just print a structure with the dimensions of a typical nano-LC column (75 μm internal diameter [i.d.] cylindrical tube with length L = 15 cm). Another limitation is the available 2PP‑optimized printing resins. These are mostly of the acrylic type, and are hence difficult to derivatize, let alone amenable to forming a mesoporous structure. The ideal 3D-printed bed for liquid chromatography should be made of mesoporous silica, but the direct printing of ceramic structures is up to now limited to filament printers, which come nowhere close to the required resolution.

An ideal 3D-packed bed could be realized by developing a technology that can deposit entire layers of (chromatographic) spherical particles at the same time. This would speed up the printing process tremendously and produce structures made with suitable material. An approach to realize this (Figure 1) is under investigation in PrintPack, a research project funded via an Advanced ERC Grant. In its first realization (9), we managed to produce uniform monolayers using a two-step process. First, we assembled two-dimensional (2D)‑sphere arrays by suspending the particles in an electrostatic cell and simultaneously attracting them using a vacuum‑driven flow onto a silicon membrane perforated by an ordered array of through-pores and subsequently brushing away the inevitable excess particles in a single or double sweep with a dense brush while maintaining the vacuum to keep the bottom layer of particles in place (Figure 2). As can be noted from Figure 2, this approach allows error-less ordered sphere particle monolayers to be produced. In the next step, we could demonstrate that the monolayers can be flawlessly transferred onto a second substrate, provided this is made of an elastomeric material, for example, carbon tape or polydimethylsiloxane (PDMS). The project’s next phase will target contacting the layer of particles with a (sub-micrometre) thin layer of photocurable glue, and then deposit the particle layer onto a stack of previously deposited layers with the glue layer facing downwards (Figure 1[b–c]). Subsequent illumination with UV-light would then fix the particles in their position, followed by the release of the vacuum-assembly tool holding the particles during the assembly process. As already demonstrated, this can be realized by making use of the reversibility of the vacuum‑driven holding mechanism, that is, by applying an overpressure instead of an underpressure.

Although many hurdles are still to be overcome, for example, putting the produced arrays in perfect‑fitting and high-pressure‑resistant housing and finding ways to handle the polydispersity of some commercial HPLC particle types, it is believed this particle assembly and deposition process holds the promise that in the future one would be able to build perfectly ordered monolithic particle beds, offering twice the efficiency of our current randomly packed columns.

The funding from the ERC Advanced Grant “PrintPack” is gratefully acknowledged (No. 695067).

1) M.R. Schure, R.S. Maier, D.M. Kroll, and H.T. Davis, 

2) F. Mattheuse, S. Deridder, and G. Desmet, 

3) W. De Malsche, H. Gardeniers, and G. Desmet, 

5) J. Stadlmann, O. Hudecz, G. Krššáková, C. Ctortecka, G. Van Raemdonck, J. Op De Beeck, G. Desmet, J.M. Penninger, P. Jacobs, and K. Mechtler, 

7) [V. Gupta, S. Beirne, P.N. Nesterenko, and B. Paull, 

8) F. Matheuse, K. Vanmol, J. Van Erps, W. De Malsche, H. Ottevaere, and G. Desmet, 

9) W. Van Geite, I.S.M. Jimidar, K. Sotthewes, H. Gardeniers, and G. Desmet, 

is a full professor in the Department of Chemical Engineering, Vrije Universiteit Brussel, Belgium.

is a PhD researcher in the Department of Chemical Engineering, Vrije Universiteit Brussel.

is a post‑doc, Mesoscale Systems group, Twente University, The Netherlands/Department of Chemical Engineering, Vrije Universiteit Brussel.

Separation Science: The State of the Art: The Future of Column Packing Technology

Reusable plastic water bottles are popular, especially during sport, due to their lightweight and impact‑resistance properties. However, little is known about the migration of compounds from plastic into the drinking water, as a wide variety of intentionally added substances (IAS) are used in the production of plastic. Furthermore, an unknown number of nonintentionally added substances (NIAS) contribute to the chemical complexity. NIAS are often unknown themselves (1), and can be introduced during the production as impurities, as well as breakdown or transformation products (TPs) caused by multiple stressors such as sunlight, physical use, or elevated temperatures (2).

Bisphenol A (BPA) is one of the chemicals of concern in plastics, and products are nowadays sold as BPA‑free. However, BPA has been replaced by bisphenol S and F, which have been shown to be carcinogenic as well (3). The new prioritization and identification of the regrettable substitutions will take additional time for risk evaluation before they can be phased out. Thus, a more broad screening of known and unknown compounds such as nontargeted screening (NTS), not yet included in regulations or databases, is needed.

In this study, we investigated the chemical migration into drinking water stored for 24 h in new bottles, used bottles, and bottles washed in the dishwasher. NTS by liquid 

chromatography–high-resolution mass spectrometry (LC–HRMS) was performed to identify these compounds. The experiment was designed to be as close as possible to typical consumer use. The chemical composition of the stored tap water was investigated after each migration step and compounds were prioritized based on systematic changes in peak intensities across the treatments. The entire study is published in the 

Nontarget Screening for Prioritization of Chemicals

Using the NTS approach, hundreds of chemicals were analyzed migrating out of the plastic from new and used sports plastic bottles. After a dishwasher cycle of the same bottles, thousands of additional, dishwasher soap-related, compounds migrated into drinking water stored for 24 h. In Figure 1, the 2000 compounds detected in the new bottles are shown in a heat map that shows the origin of the chemicals. Around 100 plastic-related compounds from the new purchased bottles were flushed away after washing the bottles in the dishwasher (a). However, another 50 compounds (b) were still in the drinking water after the dishwasher but were removed after additional flushing. One hundred and seventy-five compounds were observed to migrate out of the bottles consistently (c), even after flushing the bottles with drinking water.

It is of special concern that the concentration of some of these chemicals was even higher in the drinking water after the dishwasher cycle—indicated by vertical lines with more red colour in the row “after the dishwasher”. Most of the detected compounds were derived from the dishwasher soap, and so were detected after the dishwasher cycle (d) but removed after additional flushing of the bottles. Some of the dishwasher soap adsorbed to the material and could not be flushed away by additional water flushing (e).

Dishwasher Soap Adsorbs More to Plastic than to Glass

Surfactants that originated from the dishwasher soap were removed to more than 90% after additional flushing. However, there were several compounds still adsorbed to the plastic surface. The main detergents, which were responsible for the 60 most intense peaks, were identified as homologous series from polyoxyethylen lauryl (C12) ether and polyoxyethylen (C14) ether. These homologue series contained an increasing number of EO groups, with decreasing retention time as a function of polarity. The homologue series showed a removal trend that correlated with the number of EO groups, therefore the higher the number of the EO homologues in the series, the better the removal after additional flushing. The very polar homologue with the highest molecular mass and most EO groups (C12H26O)+(C2H4O)13 was almost 

completely removed (99% removal of the original intensity left), whereas the most nonpolar homologues (C12H26O)+(C2H4O)4 were on average removed less than 30% after flushing.

The identification of the insect repellent DEET in the plastic bottles was surprising at first glance and shows the strength of NTS. DEET was detected in the water from all plastic bottles, with the highest peak intensity in the older, previously used, bottles. DEET was also detected at low peak intensities in the new bottles but not in the glass bottles nor in the solvent blanks. Therefore, the dishwasher and laboratory blanks could be excluded as a source for DEET. We suspect that DEET, which is a ubiquitous water contaminant (5), has another origin other than its use as an insect repellent. DEET demonstrates the properties of a plasticizer (6), and for that reason it could be introduced in the plastic as a plasticizer itself or it could be formed during the use of the bottles by the degradation of other chemicals. We detected a good correlation between DEET and the plasticizer laurolactam, which has the chemical formula C12H23NO and only 6 H less than DEET. It is possible that some impurities could remain during the laurolactam production process, where there is incomplete desaturation during workup, and therefore a similar compound to DEET could be formed. However, DEET could also have been formed from laurolactam itself during the dishwasher process, with the aid of catalyzing compounds in the plastic (for example, quinones such as anthraquinone).

We detected >400 plastic-related compounds as well as >3500 dishwasher-related compounds by LC–MS NTS. The chemical structure was identified for around 50 prioritized compounds. Most plastic‑related compounds were plasticizers, antioxidants, and photoinitiators. The highest peaks were detected for oligomers suspected to originate from the biodegradable polyester polycaprolactone. The most concerning compounds were photoinitators because of their high potential adverse effects. Irgacure 369 is an amine co-initiator, a group well-known for their endocrine-disrupting effects, and 4-methylbenzophenone has shown carcinogenicity, reproductive toxicity, and skin contact toxicity in animal testing. Anthraquinone is of concern because of its breakdown products that may be toxic and carcinogenic. The dishwashing process enhanced the migration of plasticizers, antioxidants, and photoinitiators into the drinking water. Therefore, the highest predicted toxic hazard was calculated (by Cramer’s rule) for the used plastic bottles that had been filled with drinking water after the dishwasher and without further flushing. The toxicity decreased after additional flushing.

Due to the lack of analytical standards in NTS, no concentration of the identified compounds could be determined. Therefore, the risk of the stored drinking water in these reusable bottles currently remains unknown. More research is needed to identify and quantify more of the unknown unknowns detected by NTS, as well as toxicological tests to assess the relevance and risk of the newly identified compounds. The study raises the question as to whether plastic bottles are suitable for re-use, especially when they are labelled as biodegradable plastic. The study emphasizes that the production of biodegradable plastic bottles does not mean that the bottles are necessarily made of naturally occurring compounds. Instead, it can be speculated that plasticizers will migrate more easily into consumer drinking water when the biodegradable plastic bottles slowly degrade during use.

Other Uses of NTS in Environmental Analysis

NTS have been and are currently used for the analysis of many different environmental and human matrices. One area of research where the use of NTS is in its early phase is for human biomonitoring. Target analysis of endocrine-disrupting chemicals (EDCs) in urine and serum has been applied since the early 2000s. Some of the prioritized EDCs have been phthalates and their metabolites, bisphenols, and parabens, while wide scope NTS analysis has been rare (7,8). In the study by Tkalec (8), an extraction method for human biomarkers in urine was developed and combined with LC–HRMS analysis and a suspect screening and NTS approach, and the workflow was validated by spiking known EDCs.

Another area of environmental NTS that is more developed is wastewater‑based epidemiology. It has been used to screen and prioritize potentially persistent, bioaccumulating, and toxic wastewater contaminants (9) and to investigate removal processes (9–12). The same has been done for advanced oxidation processes (AOP) of groundwater 

to prioritize compounds persistent to AOP processes, as well as TPs created by UV and hydrogen peroxide treatment that cannot be removed by active carbon filters (13).

Many more applications within environmental analysis have been proposed and tested, such as soil, sediment, and biota, showing the wide applicability of NTS for environmental analysis. Key developments are currently within analytical methods alternative to reversed-phase LC–HRMS for more water-soluble compounds (persistent mobile and toxic compounds [PMTs]) such as hydrophilic interaction liquid chromatography (HILIC), supercritical fluid chromatography (SFC), and ion and ion-pair chromatography (IC); workflows for more reliable peak detection, grouping of features, drift correction, and quantification without standards; and compound databases for precursors and TPs. The joint efforts by environmental analytical chemistry and data scientists worldwide have accelerated the development of a first guideline towards standardization of NTS in water analysis, which was published by the German Water Chemistry Society, “Non-Target Screening” Expert Committee (14).

1) L. Zimmermann, M. Scheringer, B. Geueke, J.M. Boucher, L.V. Parkinson, K.J. Groh, and J. Muncke, 

2) K. Bhunia, S.S. Sablani, J. Tang, and B. Rasco, 

Endocr. Metab. Immune Disord. Drug Targets 

7) Ž. Tkalec, G. Codling, J.S. Tratnik, D. Mazej, J. Klánová, M. Horvat, and T. Kosjek, 

8) Ž. Tkalec, G. Codling, J. Klánová, M. Horvat, and T. Kosjek, 

9) K.M. Blum, P.L. Andersson, G. Renman, L. Ahrens, M. Gros, K. Wiberg, and P. Haglund, 

11) J.E. Schollée, M. Bourgin, U.V. Gunten, C.S. McArdell, and J. Hollender, 

12) S. Tisler, N. Engler, M.B. Jørgensen, K. Kilpinen, G. Tomasi, and J.H. Christensen, 

13) S. Tisler, P.L. Tüchsen, and J.H. Christensen, 

14) W. Schulz, T. Lucke, et al., Non-Target Screening in Water Analysis - Guideline for the application of LC-ESI-HRMS for screening (2019): Download at 

http://www.wasserchemische-gesellschaft.de

is an assistant professor in the Analytical Chemistry Group at Department of Plant and Environmental Sciences, University of Copenhagen

is a professor in the Analytical Chemistry Group at Department of Plant and Environmental Sciences, University of Copenhagen.

Separation Science: The State of the Art: Nontargeted Screening in Environmental Analysis: An Example Showing Migration of Chemicals from Reusable Sports Plastic Bottles into Drinking Water

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

At the heart of most chromatographic analyses are the gravimetric and volumetric operations used to prepare samples, standards, and HPLC mobile phases.

Most of us believe we are proficient in these basic laboratory skills but from time to time I like to revisit the skills, theory, and regulatory recommendations for even for most basic operations such as weighing and using pipettes.

I often find that the Standard Operating Procedures we follow tend to be very general and, for the reasons of operational simplicity, do not include the nuance of best practice. These nuances and the latest thinking in good practice are often handled via training courses, which is fine, so long as the training is regularly updated and redelivered to keep us all current.

So, this time I’m going to take a little deeper dive into the requirements for the use of so called “automatic” pipettes.

I’m using myself as a yard stick as we move through the recommendations and good practice, and I’ll be honest and point out (using Note:) those factors I was not aware of or areas where my practice could not always be described as “good!”

I’ve used the following references sources throughout this treatment;

[1] Piston-operated volumetric apparatus — Part 2: Piston pipettes, ISO 8655-2:2002(E)

[2] Piston-operated volumetric apparatus — Part 6: Gravimetric methods for the determination of measurement error, ISO 8655-6:2002

[3] GUIDE TO PIPETTING, Third Edition (2019), Gilson

[4] High Precision Micropipette, Operating Manual, Microlit RBO

[5] Measurement Good Practice Guide No. 69 The Calibration and Use of Piston Pipettes, July 2004 National Physical Laboratory, Teddington, Middlesex, United Kingdom, TW11 0LW

I would say that I make no claim on the correctness of what is written below—it is not advice, simply a personal interpretation on the current guidance and good practice documentation. I’d love to hear from the community if you believe anything in the text is incorrect—I’m always happy to publish corrections and keep my learning journey going!

So, let’s start with choosing the correct pipette for the job and compare and contrast the differences.

In short, an air displacement pipette has a layer of air between the head of the piston and the liquid within the pipette tip. Air pressure is used to force liquid from the tip. Positive displacement pipettes have an integral piston within the disposable tip and the piston is in contact with the liquid being dispensed. Both types are shown schematically in Figure 1.

Schematic diagram of an air displacement pipette (left) and a positive displacement pipette (right) (image reproduced with permission of CHROMacademy, www.chromacademy.com)

The manufacturers recommendations align well when considering which type of pipette to use for which sample type:

I wondered if, like me, you had been using an air displacement pipette for relatively volatile organic solvents or viscous solutions for years.

One pipette tip installation for air displacement pipettes: Rather than pressing the pipette shaft firmly and directly down onto the tip (apparently known as “hammering”), it is recommended that a slight twisting motion is used to create a good seal. Tips in racks are convenient (if more costly) for good practice in pipette tip fitting. For positive displacement pipettes, the above guidance should be followed, but once the tip is installed onto the shaft, the tip should be lifted out of the rack and the piston lowered until a “click” is heard as the piston locks into the pipette body. The plunger should then be pressed to the first stop position. Figure 2 contains an explanation of the various plunger positions of a typical piston pipette.

Schematic diagram of the various stop positions of a typical manual piston pipette (image reproduced with permission of CHROMacademy, www.chromacademy.com)

Air Displacement Pipette – Forward Pipetting mode

a) Set correct volume (variable volume pipettes)

When using a variable volume pipette, some manufacturers recommend the volume is dialed using a clockwise motion as the dispensed volume is controlled by a piston spring. For maximum accuracy, the spring should always be set under tension by turning the thumbscrew clockwise.

Operationally, when reducing the volume, slowly move the volume setting dial to the required volume, but when increasing the volume, overshoot the required setting by 1/3 of a turn and then reduce the volume to the desired setting. In this way, the desired volume is always reached using a clockwise motion. Always hold the volume setting at eye level to avoid parallax error.

b) Aspirate an aliquot of the liquid to be dispensed, allow to equilibrate, and dispense to waste

Holding the pipette vertically, smoothly depress the plunger to the first stop position, immerse the tip of the pipette into the liquid to be aspirated to the depth recommended in Table I, and aspirate the liquid by smoothly and steadily raising the plunger to the rest position.

If the tip is immersed too deeply, the increased hydrostatic pressure may cause too much liquid to be aspirated or liquid droplets to adhere to the outside of the pipette tip which may be transferred to the receiving vessel. If the tip is not immersed deeply enough, then vortexing may occur, or the liquid level may fall below the tip before reaching the top of the filling stroke. In both cases, too little liquid will be aspirated.

Wait two seconds for the aspirated liquid to move up into the tip and to equilibrate the temperature and pressure of the headspace air above the liquid

This step is particularly important in air displacement pipettes due to the changing compressibility of the headspace air above the aspirated liquid due to temperature and vapor pressure changes.

This first aliquot should then be discarded to waste, or if the liquid is to be retained, returned to the original container. Note that any contaminants present on the inside surface of the pipette tip may also be returned to the sample or reagent.

This tip-wetting step can significantly reduce the error associated with pipetting, and acts to reduce any interfacial effects between the liquid being aspirated and the inside surface of the pipette tip. With certain liquid types, or during pipette calibration or testing, some manufacturers and standards bodies call for up to five pre-equilibration and wetting step repeats prior to the first ‘real’ aspiration into a new tip or when volume changes are made to adjustable pipettes.

c) Repeat step b) but retain the aspirated liquid in the pipette tip

Importantly, I have read guidance, and witnessed first-hand, users wiping any excess liquid from the tip of the pipette prior to dispensing the aspirated liquid. I can see no reference to this practice in the Iso guidance, and indeed from experience, the use of adsorbent paper to wipe excess liquid from the outside surface of the tip risks contact with the tip orifice, which will draw out a portion of the aspirated liquid through wicking effects. If the pipette tip is immersed to the correct depth within the sample liquid, then there should be no need for wiping of the tip.

Place the pipette tip gently against the wall of the receiving vessel just above any liquid that may already be within the vessel, at an angle of between 10 and 45o. Note that this should be achieved by tilting the receiving vessel while the pipette remains in the upright orientation.

The angle of contact between the pipette tip and the wall of the receiving vessel is important to ensure that the liquid is dispensed correctly and to overcome any surface tension effects. One should also note that the ISO guidance recommends a contact angle of between 30 and 45o. It is also important to note that the position of the tip should be above the level of any liquid already within the receiving vessel. If the tip is submerged, then highly inaccurate and irreproducible volumes will result. Clearly, it may be necessary to handle the receiving vessel to create the correct contact angle with the pipette. In this case, handling should be kept to a minimum (especially when the vessel is to be weighed), and lint-free gloves should be worn.

Smoothly depress the plunger to the first stop position. Wait one second and then smoothly depress the plunger to the second stop position to purge any remaining liquid from the pipette tip.

In my opinion, this step is one of the most contentious and misunderstood areas of the pipetting technique. Both the guidance and the pipette manufacturers literature recommend the use of the “blow-out” or “purge” feature to dispense all liquid from within the tip, although the ISO guidance does state that this should be done “where applicable.” My question is, when is this step applicable and when is it not? I feel it is best practice to use the purge feature for all pipetting operations and some example data shown later will hopefully justify this comment.

Slowly draw the pipette tip 8–10 mm up or along the vessel wall prior to removal from the vessel and then slowly allow the plunger to return to the rest position and discard the pipette tip.

Again this last step, with particular respect to drawing the pipette tip along the vessel wall, is perhaps an area that is not properly understood. This drawing action is intended to remove any remaining liquid at or around the tip orifice to avoid it being withdrawn by the pipette. Again, some experimentation that I’ve undertaken, will be shown later to highlight the effect of not drawing the tip along the pipette wall. It is also important to note that the plunger should not be allowed to move from the second position prior to the contact with the vessel wall being broken (meaning once the tip is removed from the vessel).

Air Displacement Pipette—Reverse Pipetting Mode

Reversed pipetting is particularly useful when handling liquids with high vapor pressure (such as volatile liquids) or those which are highly viscous. This mode of operation follows all of the guidance that has been discussed above, with some notable exceptions.

a) Prior to aspiration the plunger is depressed to the second stop (purge) position

b) The liquid is aspirated by allowing the plunger to move from the second stop to the rest position

c) The liquid is dispensed by pressing the plunger to the first stop position prior to removal

The “purge” operation is effectively carried out in the aspiration step rather than the dispensing step. During aspiration, an amount of liquid equal to the amount of air used to purge the tip is aspirated, which compensates for the amount of liquid that remains in the tip after the dispensing step.

I have seen no guidance on whether the tip should be drawn along the inner wall prior to removal, in the reversed pipetting mode. I would encourage the reader to undertake their own experiments to decide if this is necessary to achieve the required accuracy when using the reverse pipetting mode.

Again, much of the important guidance has been discussed above, and points around tip wetting, immersion depth and wiping are applicable. However, again, there are some notable exceptions.

a) There is only one stop position on these pipettes. Any second stop is actually an eject position for the tip

b) In the dispense step, the piston is moved to the first stop position. The tip is not touched against the side wall of the receiving vessel and is not drawn along the vessel wall prior to removal

Having established best practice, it is interesting to discuss sources of error and tolerance of the pipetting equipment, as again there is much debate and, frankly, nonsense spoken about the accuracy and reproducibility of these volumetric tools.

ISO 8655-2 has a useful table of permissible errors for a variety of pipette types, and I’ve shown typical examples from a range of pipette volumes in Table II.

These figures are applicable for series of tenfold measurements where systematic error is the statistical deviation and random error is the coefficient of variation.

It should be noted that while the ISO guidance limits for each nominal volume is applicable to every selectable volume throughout the useful volume range of a variable volume pipette, manufacturers often set tighter specification limits for the nominal volume and between the nominal and lower selected volumes.

We have yet to discuss the required adjustments for non-standard environmental conditions or the buoyancy of the liquid used for these measurements, however I thought it would be interesting to see how accurate my newfound pipetting technique was, using deionized water that meets the criteria of ISO 3696. The results and analysis are shown in Table III for an adjustable air displacement pipette of nominal 100 ml volume.

a – the mass of water is adjusted for the Z correction factor: temperature (20.5 oC) and pressure (1.010 kPa) in the laboratory at the time of measurement, taken from ISO 8655-6

So, it would appear that my technique is reasonable, and I have achieved a reasonable performance against the ISO requirements for each volume:

My Systematic Error +0.57 ml (100) / +0.36 ml (50) / +0.35 ml (10), ISO Systematic Error Limit ± 1.5 μl 

(mass to volume Z correction factor insignificant)

My Random Error +0.34 ml (100) / +0.11 ml (50) / +0.43 ml (10), ISO Systematic Error Limit ± 0.6μl 

It is worthy of note, however, that the error associated with dispensed volume at 10 mL would not have met the ISO tolerances had I used a pipette of nominal volume 10 mL. This perhaps suggests that one needs to be reasonable about the fraction of the nominal volume that one dispenses, and I know several laboratories who specify that pistons pipettes should not be used to dispense volumes less than 50% of the nominal volume for precisely these reasons.

I was also interested in finding out the magnitude of error associated with various aspects of incorrect pipetting technique. The ISO guidance suggests a wide range of estimated errors, some of which are shown in Table IV:

From Table IV, it is obvious that the total cumulative error associated with incorrect pipette technique can be very significant. I investigated the errors associated with some specific aspects of poor technique and these results are sown in Table V, all results are from 10 replicate measurements of 50 mL of water adjusted for the 

correction factor using a nominal 100 mL pipette.

As can be seen from Table V, several of the poor techniques resulted in out of specification performance for the dispensed volume limits and all increased the inaccuracies relative to that obtained when using best practice. This is perhaps more salutary when considering that each error was implemented in isolation and that the cumulative error, if several of these poor techniques were combined, could be very considerable.

The reader will notice that I have made adjustments to the “expected” mass of water for these experiments in order to account for temperature and pressure differences between my local environment and the standard conditions used to calibrate (adjust) the pipettes (the 

 correction factor). This takes me onto my final topic in this discussion, that of pipette testing and calibration, which I’m often asked about, typically by end users who wish to carry out verification between annual calibration and maintenance.

There are two procedures which are defined in ISO 8655-6:2002, the Test Procedure for more frequent “checking” of the accuracy and reproducibility of the dispensed volume and a Calibration Procedure which is typically carried out annually by the pipette manufacturer, although it should be said that this can also be carried out by the end user with a little experience and some basic metrology tools. While the full details of the Test and Calibration procedures are outside the scope of this article, I’d like to note several points which are poorly understood.

Assessment of systematic and random error should be made on 10 replicate measurements

Prior to measurement a tip should be wetted 5 times and then discarded to equilibrate the air within the pipette to temperature and relative humidity

A new tip should be installed for each of the 10 measurements and each tip should be pre-wetted once before aspirating the required volume

For measurements below 50mL an assessment of evaporation of the test liquid (water to ISO 3696) should be made by measuring mass loss over the same time period as the 10 test measurements and then dividing this mass loss by 10 and adding the resulting mass to each test weighing

A correction for temperature and pressure (the 

 correction factor) should be made for the mass of water to account for local conditions versus those for adjustment under standard conditions (tables of water mass at various temperature and pressure values can be found in ISO 8655-6)

For variable volume pipettes, the assessment should be made at the nominal volume as well as 50% and 10% of the nominal volume (and all must conform to the ISO 8655-6 limits required for the nominal volume). Note here that the manufacturer may have separate tolerances for the nominal, 50% and 10% of nominal volumes.

Systematic error is defined by the Variance of the 10 replicate measurements and Random Error by the Coefficient of Variation

I hope that this article acts to stimulate pipette users to examine their own practice and to guide them in best practice as defined by an international standards organization as well as the pipette manufacturers. I have certainly picked up many tips during the writing of this article, and I feel much more confident in my own ability to not only pipette more accurately with piston pipette devices, but also to sense when something is not right and to troubleshoot more effectively. To quote Henry Ford, “Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning, stays young.” I feel in the flush of my youth after this salutary learning experience!

The LCGC Blog: How Well Do You Pipette?

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