Next Generation of Chromatographic Columns and Systems: From Theories to Possible Future Practices

A series of theoretical, visualization, and simulation tools that are used to improve the structure and chemistry of the next generation of liquid chromatography (LC) columns is briefly reviewed. The article describes how this combination of visualization and simulation techniques can accurately predict column performance and support method development in a “dry-lab” approach. The potential for the next generation of chromatographic systems and columns to overcome the current resolution and speed limitations of one-dimensional chromatography is also explored. Potential developments include the next generation of narrow-bore columns packed with sub-1-µm particles for “ultra-ultra-high-pressure” liquid chromatography (UUHPLC) up to 7 kbar, high-throughput three-dimensional (3D)-printed technologies for delivering materials with feature sizes smaller than 5 µm, and the next generation of zero extracolumn volume systems for ultrafast gradient LC using 1-cm-long narrow-bore columns for sub-5-seconds routine gradients.

High performance liquid chromatography (HPLC) is more than 50 years old (1) and has established itself as one of the most widely used techniques for separation and analysis. Over half a century, both systems and chromatographic columns have evolved dramatically. This development has mainly been driven by the insatiable search for faster analyses and more efficient columns, leading to the development of smaller fully porous particles (FPPs) (2), sub-3-μm core-shell particles (3,4), and to the application of ultrahigh pressures around 1 kbar (5). In 2020, ultrahigh-pressure (UHP) and ultralow dispersive LC instruments, which were introduced to the separation field 15 years ago to run columns packed with sub-2-μm particles, have not evolved much. They still remain the state-of-the-art technology that sets the limits of the speed-resolution power in unidimensional LC (6). As well as these instrument and column evolutions, the nature of the applications has also changed considerably over the past 50 years. LC now needs to adapt to new separation challenges from growing research areas in biology. From amino acids, peptides, proteins, DNA, monoclonal antibodies (mAbs), virus‑like particles to exosomes, new designs rivalling the conventional porous or superficially porous chromatographic materials are also needed (7).

While trial-and-error, design of experiments (DOEs), and, more recently, artificial intelligence (AI) are frequently used to develop new structures and surface chemistries for targeted purposes, the underlying rules of physical chemistry still have a huge role to play in the design of new technologies in LC. To reduce research and development times in the industry, quality by design (QbD) approaches are preferred to random or statistical methods. However, they require expertise and strong fundamental understanding of the process. Given the complexity of the separation mechanism of complex mixtures, which involves knowledge in both adsorption (thermodynamics) and mass transport (kinetics) in a multiscale system, there is a constant push in the separation community towards bridging the persistent gap between the performance predicted by either statistical models or approximate theories and that observed by the chromatographer in the laboratory.

The first goal of this article is to assess the power of well-known basic theories of chromatography (plate, rate, and stochastic theories) for the development of new chromatographic materials and to pinpoint their limits with respect to the actual phenomena of retention and band broadening taking place in real chromatographic columns. To that end, the advances in the physical reconstruction of the multiscale structure of an entire chromatographic column (macroporous and mesoporous space) combined with fluid dynamics, Brownian, and molecular dynamics simulation techniques (for the determination of actual flow velocity profile, diffusivity, and distribution of the analyte [8]) is discussed and illustrated in the case of size-exclusion chromatography (SEC). The second goal of this work is to report data on the latest progress in the development of “ultra-ultra-high-pressure liquid chromatography” (UUHPLC) using 3-cm-long narrow-bore columns packed with sub-1-μm particles (d_p = 700 nm), three-dimensional (3D)-printed columns based on different technologies, and in ultrafast gradient LC using very short 1-cm-long columns. The potential of these three different techniques in the years to come will be discussed and assessed.

Experimental

For the isocratic runs, the flow rate is set at 0.45 mL/min, the volume fraction of acetonitrile in water is 65%, and the temperature was fixed at 27 ºC. The injection volumes were set at 1 μL and 10 nL when using an Acquity I-Class UHPLC system (Waters) and the reduced volume research prototype system, respectively.

For the gradient runs, the flow rate is set at 2.00 mL/min and the volume fraction of acetonitrile in water increases from 5% to 95%. The two solvent lines containing pure water and pure acetonitrile contain 0.02% (v/v) trifluoroacetic acid (TFA). The gradient times were set at 1.17 min and 0.10 min, the temperatures at 45 ºC and 70 ºC, the flow rates at 1.0 mL/min and 2.0 mL/min, the detection wavelengths at 210 nm and 257 nm, and the injection volumes at 1 μL and 10 nL when using an Acquity I-Class UHPLC system (Waters) and the reduced volume research prototype system, respectively.

Contribution and Limits of Theories of Chromatography for Column Technology Development

Plate Theories: The very first theory of mass transport in a chromatographic column was proposed by Martin and Synge. Their well-known plate theory for a two liquid-phase system (8) saw the birth of partition chromatography and they both received the Nobel Prize in Chemistry for this discovery in 1952. The theory accounts for band broadening by considering a series of plates of

equal height in which equilibrium always applies. By analogy to the distillation process, the smaller the plate height is, the larger the number of chemical fractions to be separated and the larger the column efficiency. However, for either open tubular columns (OTCs) or particulate columns, the notion of plates is remote from the reality because it does not relate directly to the physical parameters controlling analyte dispersion. As a result, the plate theory is merely lumping all the phenomena of band broadening into a single and apparent height, H, which carries no clear physical relevance for the user, and so, the plate theory is not really helpful for column development.

Rate Theories: For the reasons mentioned previously, the so-called rate theories flourished and were hugely successful in the 1950s, the golden decade of chromatography (9,10). Indeed, rate theories considered relevant dispersion parameters (such as the bulk diffusion coefficient D_m, the axial dispersion coefficient D_a, the eluent linear velocity U, the global mass transfer coefficient C_s between the stationary and mobile phase, and the equilibrium constant K) and provided explicit expressions for the peak or breakthrough concentration profiles as a function of these parameters. Both chemists and analysts are now disposing of a solid physical model for performance optimization by selecting the most appropriate combination of speed, axial dispersion (particle size or open-tube column internal diameter [i.d.]), and diffusivity in the stationary phase (temperature, particle size, particle porosity, pore size). Van Deemter (11) was the first to unify the plate and rate theories in 1956. He derived his well-known equation in which H became an explicit function of U and three main coefficients related to longitudinal diffusion (called B), eddy dispersion (called A), and mass transfer resistance in the stationary phase (called C). The plate height H received a physical meaning and became an unambiguous function of D_m, U, d_p, C_s, and K.

Unfortunately, the experience shows that any attempt to fit the van Deemter equation to experimental H versus U data always returned meaningless parameters, for example, diffusion coefficients, which are significantly different from the actual ones (12). This sets the limits of rate theories as being an oversimplification of the actual separation process.

Stochastic Theories: To further bridge the gap between theory and observation, in 1955 Giddings and Eyring elaborated the very first probabilistic or stochastic theory of chromatography (13), assuming random adsorption and desorption events for each individual analyte molecule (such adsorption and desorption events were assumed to follow a Poisson distribution). This early stochastic theory was not fully comprehensive because it did not account for the known sources of band broadening pertaining to natural diffusion and flow heterogeneity in the chromatographic column. This gave birth to what is considered the most elegant theory of band broadening based on the simple one-dimensional (1D) random walk model, which can quantitatively describe all sources of zone dispersion in a chromatographic column including longitudinal diffusion, trans-channel, short-range inter-channel, long-range inter-channel, and trans-column eddy dispersion, as well as mass transfer resistance as a result of finite diffusivity in the stationary phase and to slow adsorption–desorption (14). In particular, this stochastic model revealed that the dispersion of small molecules in randomly packed beds can be significant at high speed, suggesting the design of more ordered structures to minimize flow heterogeneity in the chromatographic column.

Even though there cannot be any better theory of mass transport than the stochastic theory of chromatography, it cannot properly account for all the relevant specificities of LC columns and porous materials. For example, neither the true external geometry of the particles, their actual size distribution, the real flow velocity profile across the diameter of a column, nor the actual internal structure of a mesoporous packing material are properly considered by these theories (15). Yet, these column and particle properties control the chromatographic performance and are highly relevant.

Morphology Reconstruction, Multiscale Imaging, and Simulation Techniques: The gap between the theories mentioned previously and observation is still important today for the lack of an accurate description of the true morphological features of a column and band broadening mechanism. Even the most elaborate rate or stochastic theories ignore some of the most relevant structural features of a chromatographic column pertaining to the macroporous space (mobile interstitial volume), mesoporous space (stagnant internal volume), and to the distribution or density and diffusivities of the solvent and analyte molecules within a single pore. A complete morphological characterization of the column bed is first needed to make physically relevant predictions for the main column properties (retention and efficiency) (16). This task has been supported by the advances in microscopy (optical and electronic), imaging technologies, and computer resources. Focused ion beam scanning electron microscopy (FIB-SEM) (17) or confocal laser scanning microscopy (CLSM, a few nm resolution) (18) are applied for the reconstruction of the mesoporous space while scanning transmission electron microscopy (STEM, a few Å resolution) (19) enables the accurate reconstruction of the mesoporous space inside the particle. Finally, at the molecular level and within a single pore, either Monte-Carlo (20) or molecular dynamics (21,22) simulations are performed to determine the expected density profiles of both solvent and analyte molecules from the pore wall (of various possible surface chemistries) to the centre of a single mesopore. It is striking to see how complex the solvent and analyte density distributions are when visualizing their many ups and downs in their profiles. They underlie the intrinsic heterogeneous nature of the interface between the pore wall and the bulk pore volume.

Once the macroporosity, mesoporosity, and molecular distributions in the column are physically reconstructed, retention (mass distribution) and transport properties (molecular diffusivities, flow distribution, hydrodynamic dispersion)  are both evaluated by combining the Lattice Boltzmann method (LBM) for simulation of fluid flow profiles and a random-walk particle-tracking (RWPT) technique for calculating the effective bed diffusivities and hydrodynamic dispersion of the analyte.

FIB-SEM and STEM microscopies combined altogether with LBM and RWPT approaches provide unprecedented levels of information regarding the chromatographic properties because no system oversimplification is assumed in this approach. They can immediately reveal strengths or weaknesses of any novel structures and surface chemistries selected in research and development. Recently, these techniques have been applied to support method development in size exclusion chromatography (SEC). The macroporous and mesoporous spaces of a 2.1 mm × 150 mm column packed with 1.7-μm fully porous particles were physically reconstructed by FIB-SEM and STEM, respectively. LBM and RWPT approaches were applied to simulate fluid flow and internal/bed diffusivities of polystyrene standards of masses in between 90 and 90 000 Da. These simulations in real bed structures allowed the optimum flow rate (~ 0.04 mL/min), which maximizes the global peak capacity over the entire elution space (see left panel in Figure 1), and the particular flow rate (0.22 mL/min), which ensures a nearly uniform rate of peak capacity (or uniform resolution power) across the entire separation window (see right panel in Figure 1, solid green line), to be determined (23).

Next Generation of Chromatographic Columns and Systems

Ultra-Ultra-High-Pressure Liquid Chromatography (UUHPLC)?: Can we reasonably conceive a major breakthrough in column and system technologies by moving from today’s UHPLC (typically based on 10 cm × 2.1 mm columns, particle size d_p = 2.0 μm, 1 kbar maximum pressure, 0.8 cP average eluent viscosity, and 1 mL/min maximum flow rate) to tomorrow’s UUHPLC after further shrinking both the particle size and the column length by a factor of about three (for example, 3-cm-long columns and d_p = 0.7 μm particles)? If yes, which would then be the maximum required pressure and the most appropriate column internal diameter in UUHPLC? These questions are answered in the following paragraphs based on basic knowledge in chromatographic sciences.

UUHPLC Maximum Pressure: For the analysis of the same class of analyte (same diffusion coefficient), the optimum reduced linear velocity being unchanged in both UHPLC and UUHPLC, the optimum linear velocity is inversely proportional to d_p. Additionally, the pressure drop is proportional to column length and inversely proportional to d_p². Accordingly, the maximum pressure of the UUHPLC system will then need to be around 7 kbar for 3-cm-long columns packed with 0.7-μm particles.

UUHPLC Column Internal Diameter d_c: First, the optimum performance (h_min = H_min/d_p) of slurry-packed columns with 0.7-μm particles is evaluated as a function of the bed aspect ratio, d_c/d_p, by assuming that the thickness of the dense wall region is unchanged around 130 μm (17). The calculations are based on a validated stochastic approach for modelling the trans-column eddy dispersion coefficient (24). The results are shown in the left panel in Figure 2. Good performance (h_min ≤ 2) is expected if the column internal diameter is either larger than 2.6 mm (maximum flow rate needed: 3.9 mL/min) or smaller than 350 μm (maximum flow rate needed: 70 μL/min). From a pump technology viewpoint, delivering 3.9 mL/min at 7 kbar is very challenging, therefore only micro-UUHPLC is likely to be a reality in the near future. Second, and independently of the success of the slurry-packing process and LC pump technology up to 7 kbar, the frictional heating power (P_f = F_vΔP/L) involved at the optimum linear velocity is also evaluated as a function of the bed aspect ratio. The results are given in the right panel in Figure 2. Note a non-monotonous trend because the optimum reduced linear velocity νmin depends on the internal diameter of the column. It varies in between ν_min = 1.5 (poor packing quality due to strong wall effects) to ν_min = 11 (excellent packing quality, bulk dispersion essentially). In practice, the frictional power P_f at optimum velocity should not exceed a few watts per metre, typically 3 watts/m. Otherwise, at higher P_f values, the column efficiency starts to rapidly drop as a result of excessive radial temperature gradients across the column diameter (25–27). Accordingly, UUHPLC will not suffer from nefarious thermal effects if the column internal diameter either lies in between 400 μm and 700 μm or remains smaller than 85 μm.

To summarize, micro-ultra-ultra-high-pressure liquid chromatography mass spectrometry (μ-UUHPLC–MS) up to 7 kbar seems to be conceivable only for 0.35 mm × 30 mm columns packed with 0.7-μm particles. The maximum flow rate permitted should be close to 70 μL/min, which will minimize thermal effects and efficiency loss. The analyte dispersion as a result of the injector should also be minimized because the volume variance of the μ-UUHPLC column will not be larger than 10^-3 μL² for a retention factor k = 1. This constitutes a challenging task in terms of system integration in micro-LC systems. Clearly, no other column internal diameter appears to be suitable for UUHPLC without causing severe efficiency loss as a result of either poor column slurry packing or excessive thermal effects. Therefore, the only solution for successful UUHPLC–MS systems will consist in insulating large internal diameter columns in a high vacuum (10^-5 Torr), as recently demonstrated for narrow-bore columns packed with sub-2-μm particles in UHPLC (27–29).

3D-Printed Columns?: 3D-printed technologies are extremely attractive in the separation field because they enable the fabrication of perfectly ordered beds (structures with minimum zone dispersion) with a high degree of reproducibility. This topic has already been discussed in previous reports (30–33). To summarize briefly, Figure 3 shows different chromatographic structures 3D-printed by UV curing of acrylonitrile-butadiene-styrene oligomers (30), photo/ion lithography (34), and by two-photon polymerization (right panel) (33). It is remarkable that the build volume (100 cm³ → 0.01 cm³ → 10-5 cm³) of the 3D-printed structure increases at about the power 3/2 of the feature size (150 → 5 → 1 μm). This means that it is extremely challenging to rapidly build a large volume of macroporous and mesoporous materials with small feature sizes. Structures with sub-5-μm feature size are currently limited to either nano-LC or micro-LC because the throughput of current 3D-printing technologies is too low (33). It will be one of the important separation science challenges of the next decade to reduce 3D-printing resolution down to a few micrometres with high-throughput capacities.

Accelerated Chromatography with 1-cm-Long Columns?

System Integration: The strong push towards high-throughput LC is constantly coming from the separation and analysis field, and, particularly from the pharmaceutical industry (35). Users desperately need columns and LC systems capable of simultaneously reducing the injector duty cycle time, the dwell time of mixers, the separation time, the column equilibrium time in gradient elution mode, the postcolumn sample dispersion, and the MS data acquisition and processing times while maintaining satisfactory resolution levels. A research prototype system was recently designed and assembled in our laboratory. This system reduces to nearly zero both the dwell volume (< 5 μL) and the extracolumn volume (~ 0.5 μL total system volume, ~ 0.2 μL² total system volume variance) and is designed to operate columns shorter than 1 cm packed with sub-2-μm particles for high-throughput gradient analyses. For the sake of proprietary information, its precise design cannot be disclosed in this LCGC Europe article. Yet, in the next sections, its performance observed under isocratic and gradient conditions will be compared to a UHPLC system with fixed loop injection, 2.8 μL total system volume, 1.6 μL² total system volume variance.

Isocratic Runs: The very same isocratic run (65% acetonitrile in water, room temperature) operated at optimum column performance (at a flow rate of 0.45 mL/min) was performed on the UHPLC system (fixed loop needle injection mode) and on the research prototype system. Figure 4 shows the corresponding chromatograms and confirms a high degree of system integration between the eluent preheater, the injection valve, the column, the oven, and the detector when comparing the average overall column efficiency N (measured for six small molecules five times and an average retention factor k = 1) on a UHPLC system and on the research prototype systems. N increases from 750 to more than 1800 after system integration, meaning that the reduced plate height (RPH), h = H/d_p, decreases by nearly a factor of three from h = 8.3 for the UHPLC system used to h = 3.4 (prototype system). Note that the RPH of a 2.1 mm × 10 cm column packed with the very same material and non-corrected for the extracolumn dispersion of the UHPLC system (2.8 μL total system volume,1.6 μL² total system volume variance) is h = 2.0 (36). The large difference between the measured RPHs for 1-cm-long (h = 3.4) and 10-cm-long (h = 2.0) columns measured on the same system is essentially caused by the presence of the two 0.21 mm × 1 mm frit (0.7 μL void volume, ~ 0.2 μL² volume variance each [37]). The band dispersion caused by the same frits has obviously more impact on short than on long columns. The elution volume, V_R, and the volume variance,
 σ²_bed, of the packed bed alone (intrinsic RPH h_int = 1.2 measured on a 10-cm-long column after removing both frit and system dispersion, total bed porosity 55%, and k = 1) are 38 μL and 0.28 μL², respectively, for a 1-cm-long column. So, V_R = 380 μL and σ²_bed = 2.8 μL² for a 10-cm-long column. Therefore, the overall and observed efficiency, N = V²_R/σ²_total, of a 1-cm-long column with and without frit operated on two different instruments can easily be estimated:

N_{1 cm, frit + UHPLC system} = (38 + 2 × 0.7 + 2.8)²/(0.28 + 2 × 0.2 + 1.6) = 780 and h = 8.0 for the 1-cm-long column mounted on the UHPLC sytem with fixed loop, N_{1 cm, no frit, UHPLC system} = (38 + 2.8)²/(0.28 + 1.6) = 885 and h = 7.1 for the UHPLC system in the absence of frits, N_{1cm, frit + prototype system} = (38 + 2 × 0.7 + 0.5)²/(0.28 + 2 × 0.2 + 0.2) = 1 810 and h = 3.5 for the integrated research prototype system, N_{1 cm, no frit, prototype system} = (38 + 0.5)²/(0.28 + 0.2) = 3 090 and h = 2.0 for the integrated research prototype system in the absence of frits.

The first and third RPH calculations are in very good agreement with the observation (h = 8.3 and 3.4), and the second and fourth RPH calculations reveal that frits have a severe impact on the efficiency of very short columns and that the apparent efficiency of a 1-cm-long column mounted on the integrated research prototype instrument could be improved by over 70% from N = 1810 to N = 3090 if there were no frit at both ends of this short column.

Figure 5 demonstrates that 1-cm- long columns intrinsically suffer from significant sample dispersion caused by the two frits and by border (uneven flow distribution) and wall (uneven flow profile) effects. This causes systematic peak tailing (bottom chromatogram in Figure 5), which almost completely vanishes for longer columns (example: 3 cm, top chromatogram in Figure 5) packed with the same material. For instance, the maximum USP efficiency of a 3-cm-long column measured on the same research prototype “reduced volume” instrument is 11 000 with excellent peak symmetry. However, reducing the column length by a factor of 3 does not reduce the column efficiency by just a factor of 3 as would have been expected for the very same packing quality but by a factor of 5.5 (the maximum efficiency is only around 2000 instead of the expected 3700 plates).

Gradient Runs: Figure 6 compares two gradient chromatograms recorded for the very same gradient run (see insert in the top left corner in Figure 6) except for the system configuration. The top chromatogram was recorded on the above-described standard UHPLC system equipped with a 50-μL mixer, while the bottom gradient chromatogram was recorded on the “reduced volume” research prototype system. The temperature was set at 70 °C to allow the operation of a 1-cm-long column at a maximum flow rate of 2 mL/min (total system pressure around 8000 psi). The gradient time t_g was extremely short and set at only 0.1 min. The sample mixture contained small molecules relevant to pharmaceutical analysis. It is striking to observe that some early eluting compounds (for example, compound 2: sulfamethazine) are not even caught by the gradient front before their elution, even for a dwell time as short as 1.5 s. Most compounds that were not well focused at the column head show very poor peak shape because they were first eluted under isocratic conditions and then eluted under gradient conditions. The average peak width was of the order of 1 s, with quite poor resolution between compounds 3 and 4. This peak deformation can be explained by the fact that compounds 3 and 4 are first eluted under isocratic elution then under gradient conditions after they have been caught by the gradient front. In the end, the analysis time was about 15 s.

In contrast, repeating the very same gradient method but on the “reduced volume” system with nearly zero dwell volume and extracolumn dispersion enabled the run to be completed in just 5 s, with a complete baseline resolution of the six compounds. The average peak width was significantly reduced to only 0.15 s. Overall, Figure 7 illustrates how a chromatographic method initially developed on a standard UHPLC system with a 3-cm-long column can be modified on the “reduced volume” system to shrink the analysis time by more than one order of magnitude while maintaining satisfactory levels of peak resolution for both identification and quantification.

Conclusion

This article has demonstrated that the past and approximate theories of chromatography based on either plate (Martin and Synge), rate (van Deemter), or stochastic (Giddings) approaches can be successfully refined by combining today’s high spatial resolution visualization techniques (FIB-SEM, STEM) and fluid and molecular modelling tools (LBM, MD, and RWPT). Altogether, these techniques enable the nearly exact physical reconstruction of the actual macropore and mesopore space in a chromatographic column and the accurate prediction of their retention and mass transport properties. Though these tools are currently seen as highly sophisticated for the regular chromatography practitioner and researcher and are expert-driven, they will inevitably play an increasing role in the way research will be conducted in the future for the development of new stationary phase chemistries (optimization of selectivity for particular separation problems) and novel macropore and mesopore structures (performance optimization).

This article has also revealed that the next and significant improvement in the performance of narrow-bore columns, similar to that which occurred in the mid-2000s from HPLC to UHPLC, is unlikely to be supported in the next decade by either current 3D-printing technologies (for the lack of spatial resolution and high throughput for small feature sizes) or ultra-ultra-high-pressure liquid chromatography (UUHPLC) up to 7 kbar using sub-1-μm fully porous particle FPP or superficially porous particle (SPP) technology in 3-cm-long column format. The fundamental reasons behind such pessimistic views about UUHPLC are that (i) The resolution power of 400-μm- to 1-mm-i.d. slurry-packed columns will not be sufficiently high as a result of inevitable wall effects (38,39) and (ii) Frictional heating and peak distortions will be too excessive for column internal diameters larger than 1 mm. The possible success of narrow-bore column technology above a few kbar will only rely on the full thermal insulation of the column, as was recently demonstrated by applying a high vacuum (10^-5 Torr) around the column walls (36,37). A major breakthrough in column performance still remains possible without resorting to high-vacuum pumps, but it will be confined to either nano- or at best to micro-LC as demonstrated by Jorgenson with 10-μm- to 150-μm-i.d. capillary columns packed with 1-μm particles (41,42), and by Desmet with 2D-ordered pillar-array columns (32). The remaining barrier for packed column technology will be to adjust the proper agglomeration of sub-1-μm particles and their slurry concentration for optimized packing conditions.

Finally, it has been demonstrated experimentally that the current gradient separation speed applied in the pharmaceutical industry (based on 3-cm-long columns and conventional UHPLC systems) could easily be accelerated by one order of magnitude by adopting a zero-extracolumn-volume system with short 1 cm × 2.1 mm i.d. columns packed with sub-2-μm SPPs at standard flow rates of 2 mL/min and a high temperature of around 70 °C. The remaining limitations in ultrafast gradient LC are related to the long duty cycle of the injector (move needle or vial, draw sample volume, and wash needle), the poor efficiency of short columns (as a result of border and wall effects and frit dispersion), and the low full scan rates (~10 Hz maximum) and large postcolumn dispersion (~2 μL² minimum) of easy-to-use quadrupole-based MS detectors for accurate analyte identification and quantification. These current limitations will set the roadmap for future developments in LC instruments in the years to come.

Acknowledgements

The author acknowledges Michael Fogwill (Waters Corporation Milford, Massachusetts, USA) for designing and assembling the essential pieces of the research protype “reduced volume” UHPLC instrument, and Sebastien Besner (Waters Corporation, Milford, Massachusetts, USA) for preparing the specific optical detection cell used for the research prototype “reduced volume” UHPLC instrument.

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Fabrice Gritti is currently a Principal Consulting Scientist at Waters Corporation, which he joined in 2015. He received his PhD in chemistry and physics of condensed matter from the University of Bordeaux (France) in 2001 and pursued fundamental research in Prof. Georges Guiochon’s laboratory as a Research Scientist at the University of Tennessee Knoxville (USA) until 2014. Dr. Gritti’s main research interests involve liquid/solid adsorption thermodynamics and mass transfer mechanism in heterogeneous media for characterization and design optimization of new liquid chromatography instrument/columns.