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Laser Desorption Postionization Mass Spectrometry

I recall last year’s Pittcon in Chicago, USA. There was talk going around about a novel virus beginning its spread across the world. I don’t recall anyone wearing masks, yet. Handshakes were prevalent, though often reluctantly, and some offered fist bumps instead. Hand sanitizer was everywhere.

In the next week or two, our world changed.

Presumably due to the pandemic, the number of new sample preparation technologies introduced in the past year appeared to be down compared with previous years. Our annual review of sample preparation products covers the previous year. In late 2020, the 

 staff submitted a survey to vendors of sample preparation products. Responses to this survey are compiled in this review and were fewer than in the past, as are new product introductions during the past 12 months noted via direct mailings, e-mail, and other marketing means. Additionally, a keyword search (using the terms “sample preparation equip”, “extraction equipment”, “blend/grind/mix/shake/stir”, “evaporators/evaporation”, “filtration and purification”, and “pipets/pipetters”) of the online Pittcon 2021 vendor list was run, but attending a virtual conference is not the same as physical attendance. Most product introductions were aimed at improved performance of existing technologies or aimed at specific applications. Sorbents and accessories for solid-phase extraction (SPE) led the way, as in previous years.

This review is presented in three sections. First, SPE sorbents and products are discussed. Next, instrument-based sample preparation technologies are presented. Finally, attention is turned to other sample preparation accessories and supporting technologies. To assist the reader with some of the details behind these new products, each section presents a tabular summary of the associated products. In all cases, the new products we uncovered are presented in the annotated table, while the text highlights particularly worthwhile products.

Agilent Technologies focused on specialized sorbents which they used in a variety of application areas. Their Cannabis and Hemp Potency Kits performs the stated application using a 4-mm, 0.45-µm pore regenerated cellulose syringe filter, sample preparation consumables, and liquid chromatography column for potency analysis in cannabis flowers and hemp products. The Agilent BondElut Lipid uses a size‑exclusion and hydrophobic‑interaction sorbent in 1-mL cartridges or 96‑well plates for lipid analysis, lipid profiling, or lipidomics. The lipid analysis products are based on their existing BondElut EMR-Lipid media.

Continuing the theme of novel configurations of SPE, Biotage brought their Mikro Solid Phase Extraction Microelution Plates, featuring hydrophobic and mixed‑mode sorbents, to market. These 96-well microelution plates feature five different media: wettable hydrophobic; wettable hydrophobic plus strong cation exchange; wettable hydrophobic plus strong anion exchange; wettable hydrophobic plus weak cation exchange; and wettable hydrophobic plus weak anion exchange. The combination of the high capacity of the microelution plates and the low elution volume required may lead to an increased concentration of analyte in the elution solvent.

CDS Analytical continued development of their acquisition of the Empore product line. They also feature a 96-well plate with combined reversed‑phase and cation-exchange modes (Empore 6041 SDB-RPS Standard 96-well plate). The same styrene divinylbenzene–sulfonate sorbents are also found in 6-mL two-layer cartridge format. A final new product is the EZ-Trace, a manual, vacuum-controlled extraction workstation. The independent channel design allows precise flow control to prevent cross-contamination, and the workstation is applicable with a number of U.S. Environmental Protection Agency (EPA) methods.

For several years, DPX Technologies has been at the forefront of the pipette tip approach to SPE. This year, they advanced the field even further with the introduction of Tip‑on‑Tip (ToT) technology. ToT utilizes a top conductive tip with a bottom filtration tip, and can be employed in filtration, cleanup, and SPE modes. In the filtration mode, called 

, the sample is aspirated in the upper tip, which is then fitted to the filtration tip, and the sample is dispensed. This mode allows for high-throughput protein precipitation, particulate filtration, or β-glucuronidase removal. Figure 1(a) demonstrates an example of the protein precipitation mode using acetonitrile to crash blood proteins. The cleanup mode is compatible with a number of different sorbent chemistries, including a newly released size‑exclusion chromatography (SEC) product. As with the blood protein precipitation example, one strength of the ToT is its advantages with viscous systems. With applications requiring specific sorbent‑sample interactions, the SPE filtration tip is used. One advantage claimed for this approach is cost-effectiveness relative to alternative methods using magnetic beads. A summary of the SPE mode is shown in Figure 1(b).

Two instruments for SPE workflows were announced this year. Thermo Fisher Scientific launched the fully automated AutoTrace 280 PFAS system for the determination of per- and polyfluoroalkyl substances (PFAS) in drinking water by EPA method 537.1. The simultaneous processing of up to six samples takes 2–3 h, but requires only 15 min of operator intervention. The Waters Otto SPEcialist Positive Pressure Manifold is a programmable, semi‑automated system for SPE using 96-well plates or larger (1, 3, and 6 mL) cartridges. The pressure profile of each channel is tracked to ensure workflow consistency.

Table 1 provides a summary of each of these SPE products.

Automated Sample Preparation Instrumentation

Volatiles analysis, whether headspace sampling or following thermal desorption, was a feature of the sample preparation instruments introduced this year. Agilent Technologies introduced the Agilent 8697 Headspace Sampler, which is claimed to be the first headspace sampler with integrated gas chromatography (GC) communication. Features include a microchannel-based electronic pneumatic control (EPC) module with automatic pressure compensation and valve-based sampling. Sample racks can be exchanged during sample processing. Alternate carrier gases are allowed via an isolated flow path.

The CDS Analytical 7550S system is a stand-alone 72-position thermal desorption autosampler. Sample split, thermal slicing, and programmable tube conditioning are new features of the system.

The Gerstel TED-GC–MS system combines thermal desorption and sample pyrolysis with GC–mass spectrometry (MS). Large sample capacity renders the instrument amenable for the characterization of microplastics by separating thermogravimetric analysis and solid‑phase concentration steps. The system was developed in partnership with the Bundesanstalt für Materialforschung und‑prüfung (BAM) (The Federal Institute for Materials Research and Testing) in Berlin, Germany.

Fritsch Milling and Sizing continued its development of particle milling and sizing equipment. The Pulverisette 11 is a knife mill for the particle size reduction and homogenization of moist, oily, fatty, dry, soft, brittle, ductile, and fibrous samples from a variety of application areas. Capacity for cryogenic grinding and sample volumes from less than 40 mL to 1400 mL are features of the equipment. Dishwasher- and autoclave‑safe sample compartments are other primary benefits of the knife mill. Fritsch also launched the Analysette 22 Next for particle sizing from 0.01 to 3800 μm. A static green laser is a feature of the optical bench and the instrument has minimal moving parts. Measurements can be made in less than 10 s.

The nano Litre Dispense Module (nLDM) is a sample introduction and microarray preparation systems from Schivo Medical. It allows noncontact dispensing from single nanolitre volumes up to full syringe capacities at rates up to 20 Hz. Software control allows precise control of individual droplet sizes. Live cells and solutions of a range of viscosities may be dispensed.

Table 2 provides a summary of these automated sample preparation instruments.

Sample Preparation Accessories and Related Products

The field of sample preparation is so broad, and there are any number of established and emerging technologies identified as sample preparation, that commercial developments and new product introductions are often in seemingly scattered areas. An attempt is made here to unify these varied product offerings.

HPLC Direct launched a line of syringe filters with 4, 13, and 25 mm diameters.

A syringe filter featuring water‑wettable PTFE was developed by Pall. This hydrophilic, chemically inert membrane accommodates aqueous, acidic, basic, and organic solutions for minimal protein binding and low levels of UV-absorbing contaminants. In addition to syringe filters, the material is also used in centrifugal devices, well plates, and membrane devices. Pall also offers AcroPrep 24-well filter plates. The seven mL filter plates offer a variety of membrane options, including 0.2-μm sterile filtration media.

Microsolv Technology introduced polypropylene autosampler vials for chromatography. The two mL vials have no ion extractables to allow compatibility with ion chromatography and capillary electrophoresis.

Smart technology has become pervasive throughout modern devices and is now entering the realm of solid-phase microextraction (SPME). Supleco has developed a new smart chip that monitors fibre stroke count, usage dates, temperature exposure, phase chemistry, and lot number for traceability and increased productivity. The Smart SPME format is compatible with the PAL II GC autosampler.

Table 3 provides a summary of these sample preparation accessories and related products.

As the pandemic slowly winds down and the business community opens back up, it will follow that extraction research will continue and commercial development and marketing will follow. A return to in‑person conferences and visits with sales representatives will help drive awareness. The specific technologies, however, will be a “wait and see”, depending on the technologies and the ability of vendors to quickly commence development activities.

 is a Department Head and Associate Professor at South Dakota State University, USA. His research interests include green chemistry, alternative solvents, sample preparation, high-resolution chromatography, and bioprocessing in supercritical fluids. He earned his Ph.D. in 1990 at Brigham Young University under the direction of Milton L. Lee. Raynie is a member of LCGC’s editorial advisory board.

Direct correspondence to: amatheson@mjhlifesciences.com

Articles

This yearly report on new products introduced in the preceding year, since March 2020, covers sample preparation instrumentation, supplies, and accessories.

New Sample Preparation Products and Accessories for 2021

 sent out a survey in late 2020 and early 2021 asking vendors to supply information on liquid chromatography (LC) columns and accessories launched after Pittcon 2020. Information for this article was obtained over the course of several months, and thus, it is possible that some information has been missed or misinterpreted. The reader is encouraged to check with specific vendor sites for additional products, as well as more detailed information on product usage and attributes.

The vendors that responded to the survey and their new LC products are listed in Table 1. The products vary in targeted analyte type, as well as in their mode of chromatographic operation. The columns can be initially categorized as addressing small molecule or large molecule challenges. Within these categories, the products can be further separated based on specific modes of separation employed, including reversed‑phase LC, hydrophilic interaction liquid chromatography (HILIC), hydrophobic interaction chromatography (HIC), size-exclusion chromatography (SEC), and ion-exchange chromatography (IEC). Chiral columns are treated as a separate category. In addition to new chromatographic columns, accessories related to LC are also addressed. Trends noted throughout the article are based on comparisons to yearly reports since 2016 (1–5).

In the 2020 LC product review, the number of vendors reporting new products as well as the overall number of products showed a sharp downturn over previous years. Table 2 provides a breakdown of products introduced in various categories over the previous five years plus this most recent year. The data suggests that the low numbers observed in the 2020 review was an anomaly, and not the beginning of a downward trend. The number of reporting vendors in 2021 is still low relative to some recent years; however, the number of unique column chemistries released is back on par with the previous five years of data. Please note that many products can be categorized in multiple areas, depending on usage. This is meant to be a basic guide that highlights trends only. Columns targeting reversed-phase analysis of small molecules represent the largest group of newcomers (columns ascribed for peptide and oligonucleotide analysis were grouped with the small molecule columns). Characterization of large molecules often requires the use of multiple modes of separation. The new columns launched over the past year for the analysis of large molecules targeting reversed-phase, SEC, HIC, and IEC reflect that need.

 The product offerings assigned to the small molecule category intended for reversed-phase and HILIC are listed in Table 3. A total of 45 new column chemistries are shown with 43 reversed-phase columns, representing the largest single category in this review. It is clear from the list that superficially porous particles (SPPs) remain a substrate of choice to build phases upon while additional surface chemistries continue to be developed on fully porous particles (FPPs) as well. Continuing trends of recent years, “extended” C18 phases highlight the list where the C18 attributes are enhanced through additional interactions via “polar endcapping”, charged‑surface modifications, or through co‑bonding with other functionalities. Columns specific to HILIC continue to show less activity in comparison to reversed‑phase developments.

Advanced Materials Technologies (AMT) released two phases targeting specific classes of compounds. Halo PAH (polycyclic aromatic hydrocarbons), built on SPP, is described as a tri-functional C18 suggested for use in methods such as EPA 610, EPA 8310+2, and EU 15+1. AMT also launched Halo PFAS (perfluoroalkyl substances), a column suggested for EPA 533, EPA 537.1, and EPA 8327. This latter column is an endcapped octadecylsilane (ODS, C18) also bonded to an SPP support. AMT notes that both columns are “application-assured” through method qualified lot analysis. To complement the PFAS column, AMT has also developed the Halo PFAS Delay Column, which is described as a highly retentive alkyl phase. The delay column, placed upstream of the sample injector, acts to prevent background PFAS contamination from interfering with the PFAS analytes of interest.

Agilent introduced the AdvanceBio Peptide Plus column. Suggested for the detection of oxidized and deamidated peptides, the column is described as an endcapped “charged” C18 constructed on a SPP surface. The column is noted as being optimized for the separation of target peptides, impurities, and post‑translational modifications (PTMs). The AdvanceBio EC‑C18 column, another phase build on SPP supports, features polyether ether ketone (PEEK)‑lined stainless steel hardware. The company promotes the column for the analysis of PTMs of peptides, without the need for passivation for phosphorylated or methionine-containing peptides. The InfinityLab Poroshell 120 CS‑C18, also released by Agilent, represents another charged-surface C18 phase built on SPPs. Described as a “hybrid endcapped C18”, the phase is purported to provide a highly pH‑stable column (pH range 2–11). According to the company, the SPP particle modified to have a charged surface, provides better peak shape for basic compounds, formic acid compatibility for MS, reduced operating pressures, and increased speed of analysis compared to FPP options.

ChromaNik added new stationary phase chemistries to their SunShell (SPP-based) and their Sunniest (FPP‑based) series of columns. SunShell Biphenyl is suggested for polar compounds, isomers, and pesticides. The SunShell C18 is now available in a 3.5 µm particle format, and is noted as a general purpose column. Sunniest Biphenyl, suggested for the same analytes as its SPP partner, provides a FPP-based option.

Fortis Technologies introduced a number of new phases based on SPP supports as well. SpeedCore Aqua is described as a polar-endcapped stationary phase, and is suggested for the extra retention of polar analytes. To provide additional options for retention of neutral, acidic, and basic analytes, the company also introduced SpeedCore C8. SpeedCore BIO Peptide columns, based on a 160 Å SPP, were also developed. C18, C8, and C4 surface chemistries are available for peptide and small protein separations. The company notes that the pore structure has been optimized for peptides and proteins.

Horizon launched a number of new phases in their Aurashell (SPP) and Horizon (FPP) lines. Aurashell Amide 18 is described as an embedded amide group C18 suggested for basic and polar compounds. The company notes improved basic compound peak shapes and enhanced acidic compound retention with this phase. Aurashell C18 Ultra is touted as a “high pH C18”. The company claims improved column durability at elevated pH values. An additional phase in the Aurashell line, Aurashell C18/AR, was also released. This column features a unique C18/Phenyl chemistry that is said to enhance selectivity over conventional C18 phases for compounds containing aromatic functionalities. Horizon Amide 18 represents an embedded amide group C18 built on a FPP support. Similar to its SPP counterpart, this column is noted as improving basic compound peak shapes and enhancing acidic compound retention. The C18/Phenyl chemistry is now also available on a FPP surface with the launch of the Horizon C18/AR phase.

Waters launched a series of columns with the brand name Acquity Premier. Available in C18, phenyl-hexyl, and C18-carbamate, the columns promise to provide maximum separation performance for metal-sensitive analytes. These columns utilize what the company refers to as “MaxPeak High Performance Surface” technology, which they claim significantly reduces unwanted interactions between analytes and metal surfaces. Available in 1.7 and 1.8 µm particle sizes with pore sizes ranging from 100 Å to 300 Å, the columns are suggested for oligonucleotides, acidic peptides, TCA cycle metabolites, phosphorylated compounds, and other metal-sensitive compounds.

Welch Materials launched several new series of columns over the past year. The Boltimate series is constructed on 2.7 µm, 90 Å SPP silica and is available with C18, phenyl‑hexyl, pentafluorophenyl (PFP), and HILIC surface chemistry modifications. The company claims enhanced speed and resolution from this series of columns. The Ultisil series is based on FPP particles ranging in size from 1.8 µm to 10 µm and a pore size of 120 Å. With a number of different stationary phase options available (C18, C8, Phenyl, C4, C3, C1, cyano [CN], PFP, F-C8, and C30), the columns are suggested for small molecule reversed‑phase separations and are noted as durable, workhorse columns. Lastly, the Xtimate series, containing C18, C8, C4, phenyl-hexyl, CN, and Polar-RP surface chemistries, is built on hybrid particles. According to the company website, “hybrid” refers to a unique 5 nm organic/inorganic polymer layer coated on the silica surface. Built on particle sizes ranging from 1.8 µm to 10 µm and with a pore size of 120 Å, the columns are suggested for small molecule reversed-phase separations and for use at extended pH range.

Hydrophilic Interaction Liquid Chromatography (HILIC): 

The introduction of HILIC phases over the past several years has waned. Aside from one HILIC phase released in a series by Welch Materials, the only column launched specifically for HILIC over the past year was Restek’s Raptor Polar X. The proprietary stationary phase, described as a multimodal HILIC/ion-exchange SPP-based column, is suggested for a wide range of polar compounds, including polar pesticides (glyphosate), underivatized amino acids, and ultra-short chain PFAS analysis.

Included with the small molecule listing is a preparative offering from YMC Co. Inc., the YMC‑Triart Prep Bio200 C8. The column is suggested for the preparative purification of insulin and other peptides. The company notes that the C8 phase was designed for maximized loadability, recovery, and resolution of peptides. The company also claims that the wide usable pH range allows for alkaline cleaning-in-place (up to pH 12) to remove adsorbed proteins.

Table 4 provides information on the two columns introduced this year intended for chiral separations. Interest in chiral stationary phases, as indicated by the number of new columns launched, has trended downward since a spike in activity in 2018. See Table 2.

ColumnTek LLC. introduced a new chiral stationary phase (CSP) Enantiocel AA (D) for the enantiomeric resolution of amino acids, hydroxy acids, and amino alcohols. The company claims the column is an excellent chiral stationary phase for the direct resolution of α-hydroxy acids, such as DL-lactic acid. It also shows high utility for the chiral separation of free, underivatized amino acids with excellent peak shape. A new D-penicillamine chiral selector that is tightly bound to the packing utilizes ligand-exchange interaction for chiral recognition.

YMC Co. Inc., launched YMC Chiral ART Cellulose-SZ. The immobilized cellulose tris(3-chloro-4-methylphenylcarbamate) surface provides separations of chiral compounds, cis-trans isomers, and geometric isomers using a wide range of solvents offering greater flexibility for
method development.

New columns introduced since Pittcon 2020 intended for large molecule separations are provided in Table 5. As stated earlier, large molecule analysis often requires multiple modes of separation for full characterization. As opposed to large molecule columns reported in 2020 that were all reversed‑phase based, this year large molecule columns utilizing reversed-phase, SEC, IEC, and HIC were released.

Two reversed-phase columns targeting large molecules were launched over the past year. Interestingly, both of these columns are based on polystyrene-divinylbenzene (PSDVB) particles. Agilent developed a PEEK-lined PLRP-S column. The phase is described as being an “inherently hydrophobic based bead free of silanols and heavy metal ions”. High temperature and pH compatible, the column is suggested for oligonucleotide analysis and other large biomolecules. The company notes that the introduction of PLRP-S in PEEK-lined stainless hardware provides a column for large biological molecules free of non‑selective biologic and metal interactions.

Thermo Fisher Scientific introduced the Thermo Scientific MAbPac
Capillary Reversed-Phase HPLC column. Also based on PSDVB, the company claims the columns yield high sensitivity and high performance characterization of intact proteins for top-down proteomics applications. Additional applications are noted for monoclonal antibodies (mAbs) fragments, antibody-drug conjugates (ADCs), and polyethylene glycol‑added (PEGylated) proteins. The capillary format of the column is claimed to improve sensitivity, and achieve outstanding data results even with smaller sample volumes.

Hydrophobic interaction chromatography (HIC) is a valuable tool used to separate polar variants of proteins and study drug-to-antibody ratios (DAR) of ADCs. Two new columns in this category were released in 2020.

Agilent launched the AdvanceBio HIC column and suggests it for the analysis of mAbs, ADCs, and other recombinant proteins. The company notes that the hydrophobic coating provides new levels of hydrophobicity and selectivity to address these particularly challenging molecules.

YMC Co. Inc. introduced the YMC BioPro HIC HT column. The product was designed specifically for DAR analysis of ADCs, but also excels at HIC separations of proteins and mAbs. The company claims that the optimized butyl surface chemistry exhibits virtually no carryover while the 2.3 µm base particle offers high mechanical stability, enabling analysis at high flow rates, improving productivity by 2–3 times, while maintaining excellent resolution.

 Size-exclusion chromatography (SEC) resolves analytes based on molecular size and is often used as a complementary technique to reversed-phase analyses of proteins. Columns utilized in SEC are often characterized by strict control of pore size and by inert surface chemistry. Control of the pore size dictates how molecules of various sizes can diffuse into the pores while the inertness of the surface limits secondary interactions that may interfere with molecular size separation and determination. Four new SEC columns were introduced over the past year.

Agilent released the AdvanceBio SEC 1.9 µm column intended for protein aggregate, monomer, and fragment separation. The company notes that hydrophilic bonding prevents secondary interactions and protein adsorption. Columns are available in PEEK-lined SS hardware.

PSS GmbH developed the PSS MAB SEC column for analysis of mAbs, fragments and aggregates. The company claims application to a wide molar mass separation range and notes the columns are pre-equilibrated for direct use with light-scattering detection. These columns are also available in an optional bio-inert column hardware.

Tosoh introduced the TSKgel UP-SW Aggregate column for quantitative determination of monoclonal antibody aggregates, high-molecular‑weight (HMW) proteins, and nucleic acids. The company claims the diol surface chemistry results in low sample adsorption. A separation range of 10–2000 kDa is noted.

BioResolve SEC mAb guard and analytical columns from Waters rounds out the new SEC columns for 2021. Targeted towards monoclonal IgG SEC analysis, the diol surface built on a hybrid particle is noted as providing reliable mAb aggregate, monomer, and fragment component resolution.

 Ion-exchange chromatography is another important tool for large molecule analysis. YMC Co. Inc. introduced the YMC BioPro IEX MiniChrom column set. The columns contain screening IEC resins for protein, mAb, peptide, and oligonucleotide purification and polishing. The columns, based on a polymethacrylate surface, are available with sulfopropyl (cation exchange) and quaternary amine (anion exchange) functionalization. The company notes high dynamic binding capacity, together with low non-specific adsorption and excellent recovery.

 Microfabricated columns are included with the large molecule column listing. Several years ago PharmaFluidics launched their first microchip chromatography device containing what the company terms as “perfectly ordered pillar arrays” that are manufactured using lithographic techniques. Since that introduction, PharmaFluidics has released different effective length nanoflow columns and a trapping column to enable fast sample cleanup and enrichment of samples prior to injection on to their analytical columns. This year the company released the µPAC CapLC column that expands the use of ordered pillar array technology into the capillary flow regime. The new product offers flow rate versatility between 1 and 15 µL/min at moderate pressures, which enables short gradient separations. The company claims the columns are ideally suited for applications such as (clinical) proteomics, metabolomics, and biopharmaceutical analyses.

Accessories are important products that facilitate and often enable liquid separations. The lone products introduced in the past year that fit this category are Agilent’s Cannabis and Hemp Potency Kits. The kits contain consumables required for potency (cannabinoid) analysis in cannabis flower and hemp. The company notes added convenience from a single part number kit that includes sample preparation products, sample containment, and high performance liquid chromatography (HPLC) columns and supplies for analysis.

Following the dramatic drop off of products released relating to liquid chromatography last year, it was refreshing and reinvigorating to report an increase of the numbers to near‑normal levels in 2021. The most striking observation from this year is the high activity in small molecule, reversed‑phase column development. Similar to past years, the introduction alkyl phases with extended or alternative selectivity has highlighted new surface chemistry in this category. C18 phases with the incorporation of polar interactions through endcapping alternatives, the addition of co‑functionalities such as phenyl and the use of “charged” surfaces have all been noted in this review. Phases continue to be constructed on both fully porous and superficially porous supports. The use of “hybrid” particles, either surface modified via polymer deposition or by incorporation of organic moieties into the silica framework, continues its upwards trend. It was also refreshing to report completely new lines of columns from several lesser-known vendors. For large molecules, a return to products covering a number of different modes of chromatography, each providing important information towards the full characterization of these complex molecules is noted. Columns for SEC actually outnumbered those developed for reversed-phase modes in this category. Here again, modern particle technologies, such as SPP, hybrid, and polymeric supports, continue to enable new features and increased capabilities for chromatographers to exploit.

 is a director of Research and Development at Restek. He also serves on the Editorial Advisory Board for LCGC and is the Editor for “Column Watch”. Over the past 20 years, he has worked directly in the chromatography industry, focusing his efforts on the design, development, and application of chromatographic stationary phases to advance gas chromatography, liquid chromatography, and related hyphenated techniques. His main objectives have been to create and promote novel separation technologies and to conduct research on molecular interactions that contribute to retention and selectivity in an array of chromatographic processes. His research results have been presented in symposia worldwide.

Our annual review of new liquid chromatography columns and accessories, introduced at Pittcon and other events over the past 12 months.

New Liquid Chromatography (LC) Columns and Accessories for 2021

Limit of detection (LOD) is among the most important and misunderstood analytical variables of merit for both instruments and analytical methods. In this instalment, we review the history and fundamentals for determining and reporting LOD for analytical instruments and methods. We also discuss the International Union of Pure and Applied Chemistry (IUPAC) and propagation of errors methods used for calculating LOD and explain the limitations of the IUPAC method in modern chromatography. We used simulated data to discuss the implications of the calculation method, and talk about the reported LOD values and our understanding of the sources of experimental uncertainty and variability in LOD determinations.

Limit of detection (LOD) is among the most calculated and most misunderstood analytical figures of merit for instruments and methods. We are first exposed to LOD in undergraduate analytical chemistry textbooks. LOD is among the most reported figures of merit in validated methods, literature articles, and advertising literature. The International Union of Pure and Applied Chemistry (IUPAC) defines LOD as “the smallest concentration or absolute amount of analyte that has a signal significantly larger than the signal from a suitable blank” (1). As a result, this statement informs us that LOD can be expressed in concentration or mass units and that the analyte must produce a signal that can be deemed greater than a blank by a statistical test. In practice, a “signal significantly larger” means that the analyte signal should have a value two or three times the blank.

The best way to determine LOD is to measure it directly by preparing standards at appropriately low concentrations and analyzing them on the instrument or running them through the method procedure. Analysts should know that experimental errors involved in the standard preparation and dilution procedure as well as the inherent 33–50% relative variance that is inherent in a measurement where the signal is only two or three times the instrumental noise in the blank will factor into the LOD measurement. This means that LOD values should be reported to one significant digit only. Reporting LOD to more than one significant digit is one of the most common mistakes seen throughout the literature.

LOD is usually calculated rather than measured directly. The classical methods for calculating LOD were developed using spectroscopic and electrochemical instruments in the 1960s and 1970s (2–4). Chromatographers have generally adapted these methods to gas chromatography (GC) and high performance liquid chromatography (HPLC), although there are fundamental differences between spectroscopic and chromatographic instruments.

In 1983, Long and Winefordner provided a review and critical discussion of LOD calculation methods that still provides useful insights nearly 40 years later (5). Their article is still cited as additional reading material for the discussions of LOD found in the instrumental analysis textbooks of today (6,7). More recently, in 2015, Krupcik and others provided a detailed statistical analysis of LOD and limit of quantification (LOQ) calculations in gas chromatography–flame ionization detection (GC–FID) and comprehensive two-dimensional gas chromatography–flame ionization detection (GC×GC–FID) analyses (8). They evaluated methods based on the classical IUPAC method and using signal-to-noise (

) ratios and found significant differences between LOD and LOQ calculated by each method in both GC and GC×GC. The results of LOD determinations are highly dependent on both the calculation method used and on how any standards used for the analysis are prepared. At a minimum, for LOD to be comparable between methods and instruments and repeatable between experiments, the calculation and the standard preparation should be reported in much more detail than is typical in the chromatographic literature.

In the remainder of this article, we focus on a critical evaluation of the classical IUPAC definition for LOD, applied to chromatography, because this is the most widely practiced method. In determining LOD, most authors cite the classical IUPAC calculation equation, shown in equation 1, which states:

 is the limit of detection, usually expressed in concentration units, 

 is the standard deviation of the signal generated by multiple blank measurements, or in the case of a chromatographic analysis, the signal for multiple data points recorded along the baseline, 

 is the slope of the calibration curve, and 

 is usually two or three, depending on the specific LOD definition chosen. This has been a matter of debate over the years. Long and Winefordner recommend 

 = 3 as the lowest value that provides a statistically significant difference between the signal and the noise. I agree with this as LOD should be reported conservatively, as we will see below, and 

 = 3 provides over 90% confidence that the signal is not noise. If performing LOD determinations for method validation in a regulated environment, the definition recommended by the regulating authority should be used.

Before going into more details of LOD calculations, it is educational to look at data showing very low signals and instrumental noise. Figure 1 shows four plots, each with very low signal. Figure 1(a) shows 100 data points of simulated random instrumental noise, generated by the random number generator function in Microsoft Excel. This could be interpreted as 5 s of the noise generated by a flame ionization detector, with no analyte passing through the detector, operating at a sampling rate of 20 Hz. Every 20 values on the 

-axis represents 1 s of data collection. The 

-axis data are random numbers between 0–10. As seen in Figure 1(a), the noise is random. The baseline would be expressed as a signal of 5, the midpoint of the noise, which ranges from 0 to 10.

Figure 1(b) shows a small peak that is 1 s (20 data points) wide with the peak height representing 

 = 2, a common usage in LOD calculations. Note that the peak does not appear symmetrical, as the random noise still comprises much of the signal. This is typical of actual experimental data for analyses performed on samples at or near the LOD. Both peak area and peak height determinations for this peak would have large amounts of experimental uncertainty. This leads to the important point made earlier that LOD should never be reported to more than one significant digit. Any additional claimed precision in an LOD determination is meaningless.

Figure 1(c) shows a 1 s wide peak representing 

 = 3 in equation 1, the recommended value. The peak, while still noisy, looks more like a traditional chromatographic peak. The peak height and peak area are still subject to experimental uncertainty approaching (1/3) or 33%, still making this a one significant digit estimate. One result of this is that the peak height or peak area for small signals, in the same order of magnitude of the noise, should be reported with one or two significant digits, no matter how many digits the data system provides in the peak table. Furthermore, the retention time, reported as the peak maximum, may also be more variable than implied by the number of digits provided by the data system.

Figure 1(d) shows a 1 s wide peak representing 

 = 10 in equation 1, a typical value for LOQ that is often determined when validating a method or when determining analytical figures of merit. This looks more like a useful chromatographic peak and the peak height and area are now subject to experimental uncertainties around 10%, making this a two‑significant digit determination in many cases. However, the peak is still subject to significant impact from the random instrumental noise. LOQ is typically stated as the lowest concentration or mass for which quantitation would be effective and 

 = 10 is often used with equation 1 to determine this value.

Figure 2 is a calibration plot showing sample data, typical of detection limit calculations, and Table 1 shows the 

-data and the statistics for the regression line. The calculations were performed using Microsoft Excel and the statistical calculations were performed using the LINEST function. The 

-intercept of five for the line was chosen from the average baseline values shown in Figure 1 and is illustrative of an instrument with a non‑zero baseline. The slope of 10 was chosen as an illustration and provides data over a range of approximately 50–2000 of our arbitrary units, or about 1.5 orders of magnitude, typical of many calibration curves, and with the lowest point near the LOD. The random number generator function in Microsoft Excel was used to superimpose noise of +/− 5% on each of the 

-data points. The blue dotted line represents the original noise‑free 

‑values, and the grey dots represent the same values with the random noise added. Note that they do not perfectly overlap. We all know that on a calibration curve, the best fit line and the data points do not always match up, yet by using equation 1 to calculate LOD, we assume that they do.

-data with noise. Below these are the statistical results for the slope and intercept, their standard errors and the 

As seen in equation 1, the IUPAC equation is dependent on the amplitude of the baseline noise, which can be measured directly from the baseline of the chromatogram, preferably in a region near the peak of interest and the slope of the calibration curve. For this example, Figure 1(a) was used as the baseline noise. Note that equation 1 does not provide any specification on the region of the calibration curve that is used or its relationship to the ultimately determined LOD. More importantly, there is no accounting for experimental uncertainty in the slope of the calibration curve. The LOD determination is only as good as the instrument and the standards used to measure it.

An alternate approach, discussed by Long and Winefordner and based on similar principles to the IUPAC equation method that employs propagation of errors accounting for experimental uncertainty in the calibration curve or standard preparation, is described by equation 2:

where the propagation of errors method includes terms for experimental uncertainty in both the slope (

) of the calibration curve. The need to include slope uncertainty is clear; this cannot be assumed to be zero. Intercept uncertainty accounts for a non-zero baseline, as does the presence of a term for the amplitude of the baseline itself (

). In short, all experimental values that impact LOD determination are included. Equation 2 reduces to the IUPAC method (equation 1) if the data are background corrected, providing a baseline of zero and the uncertainties on the slope and intercept of the calibration curve are near zero or much lower than the uncertainty on the baseline.

Table 2 shows the results of five LOD determinations using our simple calibration curve simulator, as seen in Figure 2, with the propagation of errors calculation shown in equation 2, with 

) of 5 and standard deviation of the blank (

) of 5. Using the IUPAC calculation in equation 1, the result for LOD would be 1.5 (rounded up to 2 for reporting as one significant digit) for all the determinations because the slope does not change. For this illustration, the standard errors reported from the LINEST function in Excel were used for the uncertainties on the slope and intercept without any further calculations. In all cases, the propagation of errors method provided a LOD equal to or greater than the IUPAC method. In this example, it is easily seen that the uncertainty on the 

-intercept is the major contributor to the increase and that uncertainty on the slope is negligible. This might not always be the case, but it is clear that uncertainties in standard preparation or calibration curve generation contribute to the LOD and should be accounted for, especially in situations such as gas chromatography tandem mass spectrometry (GC–MS/MS) and GC×GC where instrumental noise is likely to be very low.

Thinking back to the context in which the classical IUPAC equation was developed, it is important to consider that hand calculators did not exist and calculators or software that would easily perform any kind of linear regression would not calculate uncertainties on the slope and intercept values determined by linear regression. Those calculations are difficult, time‑consuming, and prone to mistakes, if performed by hand. Further, analogue instrumentation was often much noisier than today’s digital systems, making instrumental noise sources more common than the experimental uncertainty in standard preparation using volumetric glassware. Today, the reverse situation is much more likely. Instrumental noise is much lower, especially when multidimensional detectors such as MS/MS are used, making uncertainty in the standard preparation much more important in the LOD calculation.

There is much more to determining a LOD than simply looking up the IUPAC equation or other formula required by a regulatory body, whether that is examining the noise on a chromatogram, making a calibration curve, determining the slope, or calculating a value. We see that the LOD is dependent on several variables, including the instrumental noise and sensitivity, the uncertainty in the sensitivity and the calculated 

-intercept of the calibration curve. At the very least, for LOD values to be comparable between instruments and methods, the calculation method should be clearly stated and sample calculations, including the uncertainties in the blank and calibration curve, should be provided in method reports or publications.

IUPAC Gold Book, https://goldbook.iupac.org/terms/view/L03540, accessed April, 2021.

G.D. Christian, P.K. Dasgupta, and K.A. Schug, 

 (John Wiley and Sons, New York, USA, 7th ed., 2013).

D.A. Skoog, D.M. West, F.J. Holler, and S.R. Crouch, 

 (Cengage, New York, USA, 9th ed., 2014).

J. Krupcik, P. Majek, R. Gorovenko, J. Blasko, R. Kubinec, and P. Sandra, 

 is the Founding Endowed Professor in the Department of Chemistry and Biochemistry at Seton Hall University, New Jersey, USA, and an Adjunct Professor of Medical Science. During his 30 years as a chromatographer, he has published more than 70 refereed articles and book chapters and has given more than 200 presentations and short courses. He is interested in the fundamentals and applications of separation science, especially gas chromatography, sampling, and sample preparation for chemical analysis. His research group is very active, with ongoing projects using GC, GC–MS, two-dimensional GC, and extraction methods including headspace, liquid–liquid extraction, and solid-phase microextraction. 

Direct correspondence to: amatheson@mjhlifesciences.com

A review of the history and fundamentals for determining and reporting limit of detection (LOD) for analytical instruments and methods. Includes a discussion of the International Union of Pure and Applied Chemistry (IUPAC) and propagation of errors methods used for calculating LOD, and explains the limitations of the IUPAC method in modern chromatography.

Going Low: Understanding Limit of Detection in Gas Chromatography

Dispersion (the broadening or spreading) of analyte zones (peaks) outside of chromatography columns can seriously erode the resolution provided by good columns. Understanding the relationship between the level of dispersion associated with a given instrument relative to the intrinsic efficiency of a given column can help avoid disappointing results, especially when switching to new column technologies. In this instalment, we focus on basic concepts in extracolumn dispersion as a prelude to future instalments that will focus on dispersion in specific elements of high performance liquid chromatography (HPLC) systems.

Even from the very early days of the development of chromatography “systems” that provided for mechanized introduction of samples into the mobile phase flow path, it was recognized that dispersion of analyte zones outside of the separation column could compromise the quality of the separation as measured by resolution (1). During the 400‑bar era of liquid chromatography (LC) that lasted through the mid‑2000s, instrument manufacturers worked to adjust the dimensions of component parts, including connecting tubing and detector elements, so that the impact of dispersion of the analyte zone outside of the column was manageable, and did not seriously affect separation performance in most cases. However, the introduction of instruments capable of separating at much higher pressures (for example, 1000 bar and beyond) starting in the mid-2000s precipitated a dramatic growth in the use of narrower columns (mostly 2.1 mm i.d.) prepared with smaller particles (that is, moving below three micrometres). When used under these conditions, these columns have the potential to produce peaks with much lower volumes (on the order of 10 times or more) compared to those that were typical in the 400‑bar era. These lower volume peaks are, in turn, more susceptible to dispersion outside of the column to a degree that can seriously compromise the quality of the separation. As a result, there has been renewed interest in the topic of extracolumn dispersion (ECD) in the last 15 years, both from instrument manufacturers looking to improve the performance of their instruments along these lines, and from researchers looking to further our understanding of these issues so that we can leverage this knowledge in the development of better methods (2). So, in spite of the fact that ECD has been studied intensively since the very early days of high performance liquid chromatography (HPLC), a lot has changed recently. For this month’s instalment of “LC Troubleshooting”, I have asked Dr. Ken Broeckhoven (fellow LCGC Emerging Leader, and one of the world’s experts on ECD) to join me in writing a multi-part series on this topic where we aim to translate new findings described in the chromatographic literature into terms that can be applied in development and troubleshooting of modern HPLC methods. In this first instalment, we begin by reviewing terms and concepts that are central to the discussion, and quantify the effects of ECD on the performance of separations executed using columns of different dimensions and prepared with particles of different sizes. In subsequent parts of this series, we will go into more detail discussing how different parts of HPLC systems (for example, injectors, detectors, and connecting tubing) contribute to the overall dispersion that ultimately impacts the quality of a separation. We are hopeful that an improved understanding of these factors will help users identify situations where ECD may be unnecessarily compromising the quality of their separations, and identify a viable path to remedy this type of situation.

Given that the pace of change in the HPLC column market has been rapid recently, and that the turnover of HPLC instruments in laboratories is relatively slow, it is commonplace for users to try out a new column technology using a relatively old instrument. Sometimes this works just fine, and sometimes it does not. We would really like to avoid situations where the apparent column performance does not measure up to expectations, not because the column doesn’t work properly, but because the influence of the instrument on the outcome obscures the actual column performance. Many column manufacturers have recognized the seriousness of this problem, and invested substantially in the development of educational material, tutorials, trainings, and software (such as method transfer calculators) to help users avoid bad experiences with new column technologies.

We recognize that many practicing chromatographers think in terms of chromatograms. To get acquainted with the problem we’re discussing here in a quantitative way, we have prepared the simulated chromatograms shown in Figure 1, which illustrate the impact of ECD typical of an older HPLC instrument on the quality of separations obtained with relatively older or newer column technologies. Panels a and b show simulated chromatograms for isocratic separations of a hypothetical five-component mixture of compounds with retention factors ranging from 0 to 8.5. Panel a shows the separation of the mixture using a 150 mm × 4.6 mm i.d. column packed with 5 µm particles, operated at a mobile phase flow rate of 1 mL/min, where we assume that there is absolutely no influence of dispersion outside of the column on the observed chromatogram (that is, ; this is completely hypothetical, but useful to support discussion). The separation is good with a minimum resolution of 1.5 for both compound pairs 1–2 and 3–4, and the analysis is complete in about 12 min. Now, for a separation on this time‑scale, one of the potential advantages of moving to a column with a smaller particle size is that the same resolution achieved with larger particles (panel a) can be achieved in a shorter time, provided that the pressure required to drive the separation using smaller particles can be generated by the pump. Panel b shows what such an improvement could look like. We see that moving to a shorter column packed with smaller particles yields the same resolution in a much shorter time provided that the flow rate is similar to what was used for the column with larger particles. Again, this assumes there is no impact of the dispersion outside of the column on resolution, and it is critically important to recognize here that this degree of improvement can only be realized if a much higher pressure is available.

Things become more interesting when we consider cases where dispersion outside of the column does impact resolution. By comparing panels a and c, and b and d, we can see that the magnitude of the impact of ECD is strongly influenced by the column in use. In the case of the long column with large particles, the level of ECD chosen here (which reflects the characteristics of a “good” system from the end of the 400‑bar era; see more discussion below) does not affect the resolution of the 3–4 peak pair at all. There is a very small effect on the resolution of the 1–2 peak pair, but this level of change certainly would not be detectable by eye. In other words, separations involving long columns and large particles tend to be relatively unaffected by dispersion outside of the column. In panel d, however, we see a completely different outcome. If we take the shorter, narrower column packed with smaller particles and carry out the separation using the same instrument characterized by an extracolumn variance of 30 μL2 as in panel c, the system has a devastating negative impact on the quality of the separation. The resolution of the 3–4 peak pair decreases by 23%; the loss of resolution for the 1–2 peak pair is so bad that it is no longer even clear if there are actually two peaks present at that point in the chromatogram.

So, coming back to the title of this instalment, a perfectly good column can be robbed of its performance potential as a result of using it in an instrument that is not well suited to modern column technologies. In the remainder of this article, and in the other parts of this series, our aim is to provide an update on recent research results that inform our understanding of how different instrument parameters contribute to the level of ECD exhibited by different systems. We can then use this knowledge to troubleshoot problems originating from these effects, and build better methods from the start. Readers interested in learning much more about details related to this topic are referred to the recent review article by one of us (2), as well as contributions on the topic in

Extracolumn Dispersion: Measuring It, and Adding It

is that it is calculated as the square of the ratio of the retention time (or volume) to the peak width (in time or volume units to match the retention measurement). If the peak is symmetrical and has a Gaussian shape, then the simplest calculation of the efficiency relies on the standard deviation (σ) of the Gaussian, shown in Figure 2(a). It is common to measure the peak width at half of the peak height (w

). In the case of a Gaussian peak the relationship between w

 and σ is straightforward and thus σ can be calculated from w

. When peaks are perfectly symmetrical, determining σ by measuring the peak width at 50% of the height (w

) will yield exactly the same σ number. However, as the peak becomes more asymmetric, the w50 value will underestimate the true peak variance, and thus using w

 provides a more conservative measure of the variance. More rigorous determination of the peak variance of asymmetric peaks requires the use of statistical moments, which comes with its own challenges. Readers interested in learning more about these details are referred to a recent review of many issues related to ECD (2).

One of the simplest approaches to determining the level of total ECD involves replacing the column with a zero‑dead‑volume union and injecting a sample. The width of this “system peak” can then be determined using one of the methods discussed above. The most critical step in assessing the impact of the ECD on the observed column efficiency is recognizing that it is the variances (σ

) of system and column peaks that are additive, not the widths (that is, σ, determined by any of the methods above). The process of estimating the impact of the extracolumn variance on the observed column efficiency is shown graphically in Figure 2. The standard deviations of the system and column peaks are first measured or calculated, the variances for each component are calculated, and then they are added together. The resulting variance expected for the observed peak can then either be used as is, or converted back to a peak width.

Impact of Extracolumn Dispersion on Observed Column Efficiency over a Range of Conditions

In Figure 1, we illustrated the effect of one level of extracolumn variance on the resolution provided by two columns of very different dimensions. It is also instructive to examine the magnitude of this effect over ranges of retention factors, column dimensions and particle sizes, and extracolumn variance levels. The results of this kind of calculation provide a kind of map that one can use to estimate the seriousness of the effect of the extracolumn effect when approximate values of retention factor, extracolumn variance, and column dimensions are known. Whereas in Figure 1 we used the resolutions of specific peak pairs to quantify the loss of performance, in the following discussion we will use the loss of column efficiency as a metric, because it provides a more generalizable view of the problem.

There are a number of ways one could approach these calculations that vary in the level of rigour and accuracy required, but we have taken the following approach to arrive at the numbers shown in Figure 3. We start by estimating the inherent efficiency of the column (

) (that is, without extracolumn effects) from the column length (

). In our case here we have assumed that the reduced plate heights for fully porous particles (Figures 3[a] and 3[c]) are 2.0, and 1.5 for superficially porous particles (Figure 3[b]). A more rigorous approach would require an estimate of the flow rate (

 through something like a van Deemter curve. We also note here that the following calculations and discussion are only relevant to isocratic separations. In future instalments we will discuss how things change in the case of separations that use gradient elution.

Once we have the column efficiency, we can calculate the standard deviation of a peak at any retention factor as long as we know the column dimensions and have an estimate of the total porosity of the column. A reasonable estimate for the total porosities (ε

) of columns packed with fully and superficially porous particles is 0.5 (10). First, the column dead volume (

) is calculated from the physical dimensions of the cylinder and the porosity.

) can be calculated for a compound with retention factor 

, and finally the peak standard deviation from the retention volume and the column efficiency.

Now, with the expected peak standard deviation in hand, and an estimate of the extracolumn variance(σ

), we can calculate the standard deviation that will be observed at the detector (σ

due to additional dispersion outside of the column.

) is then calculated by rearrangement of equation 4. Note that here we assume that 

 is unaffected by the system volume outside of the column. This most definitely is an approximation, and a more rigorous approach would not rely on this assumption, but this is a minor issue in the context of the parameters chosen here and the focus of this discussion.

Finally, the percent loss of column efficiency is calculated as:

A series of results from this type of calculation are shown in Figure 3 for three different columns and three levels of extracolumn variance, over a range of retention factors from 0 to 10. The three columns selected are very different, and represent: a) large columns (150 mm × 4.6 mm i.d.) packed with large particles (5 µm) that are still often used in legacy methods that were developed in the 400‑bar era; b) long (150 mm), narrow (2.1 mm i.d.) columns packed with superficially porous particles of intermediate size (2.7 µm) used for modern, high efficiency separation; and c) short (30 mm), narrow (2.1 mm i.d.) columns packed with sub-2-µm particles used for very fast one-dimensional (1D) separations, or as the second dimension column in two-dimensional (2D)-LC separations. The three levels of extracolumn variance selected represent the level of dispersion found in good instruments from the end of the 400‑bar era (30 µL

), “off‑the‑shelf” configurations of modern ultrahigh‑pressure liquid chromatography (UHPLC) instruments (10 µL

), and highly optimized configurations of UHPLC instruments aimed at minimizing extracolumn dispersion (2 µL

There are many useful observations we can make in reviewing these results. First, as discussed above, the performance of large columns like that shown in panel a is relatively insensitive to reasonable levels of extracolumn variance. Even with the largest variance of σ

, the maximum efficiency loss for any compound with 

 > 1 is only about 5%. Using this type of column in an instrument with lower extracolumn dispersion is not very helpful from the point of view of the observed efficiency (

obs), unless one is dealing with very low retention compounds with 

 < 1 (which is important in size‑exclusion chromatography [SEC], for example).

Moving to the results shown in panel b for the 150 mm × 2.1 mm i.d. columns packed with 2.7 µm superficially porous particles, we see that using this type of column in an instrument from the 400‑bar era will result in efficiency losses of more than 30% for compounds with 

 < 5. This obviously would be a serious disappointment for someone trying a column like this for the first time. Moving to an off‑the‑shelf UHPLC instrument helps quite a bit, but even in this case the efficiency loss for compounds with 

 < 1 is more than 50%. Realizing the full potential of this column requires some optimization of the UHPLC instrument. Reducing the extracolumn dispersion to 2 µL

 enables realization of more than 90% of the actual column efficiency for compounds with 

Out of the scenarios considered here, the results in panel c show that using short, narrow columns packed with sub-2-µm particles in instruments without careful attention to the level of extracolumn dispersion will lead to disastrous results. Even with a highly optimized UHPLC system, 80% of the actual column efficiency is only reached for compounds with 

 > 4. With columns of these dimensions we must be very careful to manage our expectations for performance by taking into account the characteristics of the instrument surrounding the column.

In this instalment of “LC Troubleshooting”, we have reviewed some of the basic concepts relevant to the consideration of extracolumn dispersion (ECD) that occurs in HPLC systems, and the impact of this dispersion on the apparent performance of columns of different dimensions and efficiencies. As columns become smaller, and as they are packed with smaller particles, attention to the minimization of ECD associated with the instrument becomes more important. Not considering this can result in very poor apparent column performance that has nothing to do with the actual column performance, and everything to do with robbing the column of its inherent efficiency by dispersion of the analyte zone that occurs outside of the column.

Here, we have talked about ECD from the point of view of an entire instrument. In upcoming instalments we will dig into the details of dispersion that occurs in different elements of these systems, including injectors, detectors, connecting tubing, and when post‑column flow splitting is used, as well as differences in the treatment of ECD when gradient elution is used.

 (Marcel Dekker, New York, New York, USA, 1966), pp. 205–270.

K. Broeckhoven, J. De Vos, and G. Desmet, 

K. Broeckhoven, D. Cabooter, and G. Desmet, 

 received his Ph.D. in 2010 from the Vrije Universiteit Brussel (VUB), in Brussels, Belgium. Following post-doctoral research at VUB and work as a visiting researcher in the separation processes laboratory at ETH Zurich, in Switzerland, he became a research professor at VUB in 2012. He was subsequently promoted to Assistant Professor and then to his current position as an Associate Professor in 2017.

 is the editor of “LC Troubleshooting”. Stoll is a professor and the co-chair of chemistry at Gustavus Adolphus College in St. Peter, Minnesota, USA. His primary research focus is on the development of 2D-LC for both targeted and untargeted analyses. He has authored or coauthored more than 70 peer‑reviewed publications and four book chapters in separation science. He is also a member of LCGC’s editorial advisory board.

This instalment focuses on basic concepts in extracolumn dispersion (ECD) that occurs in high performance liquid chromatography (HPLC) systems, and the impact of this dispersion on the performance of columns of different dimensions and efficiencies.

Where Has My Efficiency Gone?  Impacts of Extracolumn Peak Broadening on Performance, Part 1: Basic Concepts 

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.

Most readers will be familiar with the major gas chromatography (GC) variables, setting them into our data acquisition software, and reading them from our SOPs or laboratory work instruction methods on a regular basis. Generally speaking, those variables are not in scope here, other than to consider the lesser-understood effects of some of them.

Instead, I’d like to concentrate on variables that can really impact our chromatography, but may be on hidden, supplementary, or advanced pages of our software, or may appear on the main software acquisitions menus, but are poorly understood or rarely altered. These variables are often not specifically referenced in laboratory methods documents or, if they do appear, are poorly understood. While some of these variables appear to be esoteric, I’ve seen all of these either ruin otherwise perfectly good chromatography or confound users during method troubleshooting.

Autosampler syringe plunger speed and needle depth


Most autosamplers will give the option to change the speed of the plunger within the syringe barrel, both during sample aspiration and injection into the GC. When dealing with viscous samples, the plunger speed is usually set to a slower speed to avoid cavitation of the sample within the needle, and consequently, variable sample amounts being aspirated. The syringe needle depth may also need to be adjusted when dealing with very low sample amounts, vials with different shapes, or multiphasic samples, for example, where the top layer of a biphasic solvent mixture needs to be sampled. The speed of sample ejection into the inlet may also need to be altered with narrow bore inlet liners or some modes of cool on column injection.


Certainly not the most exciting of topics within the GC arena, but wash solvents are highly important, nonetheless. Wash solvents should be chosen on their ability to solubilize the analytes of interest and not just the sample matrix. This fact is often overlooked when choosing appropriate solvents. The solvents should be highly miscible with the GC injection solvent and, where possible, two wash solvent bottles should be used: one “dirtier” and one “cleaner” bottle. The trick is to wash the syringe prior to sample aspiration in the cleaner solvent and then post-injection, wash first in the dirtier solvent followed by a rinse in the cleaner solvent. Where three wash solvent positions are available, then the third solvent should be reserved for the pre-sample aspiration wash only. It’s also a good idea to leave wash-solvent bottles uncapped because any sample residue from the outside of the syringe needle can potentially contaminate the septum or needle guide from the bottle tops, and be resolubilized into the next sample, causing carryover. Always try to aspirate the wash solvent and discard to waste three times in each operation to ensure that the syringe needle does not penetrate any liquid in the waste bottle—meaning, empty the wate bottle regularly! Having a table of conditions within the method that stipulates the wash regime is a great way to highlight the importance of this variable.

Paying attention to the wash-solvent regime will help to improve your quantitative reproducibility by cutting down on carryover from injection to injection.


Again, not the most inspiring of topics, however, one that can be very important in determining peak shape, especially in splitless injection. I realize that most written methods will cite the injection solvent to be used, and this parameter may be reliant upon sample extraction or manipulation operations from a previous step in the analytical workflow. I cite the importance of the injection solvent here because less experienced GC users may not be aware of just how important the selection of injection solvent is. Injection solvent expansion volume plays an important role in carryover with both split and spitless injection. If the injected liquid volume results in a gas volume that exceeds the liner volume under the operating conditions employed, this will potentially contaminate the inlet and associated tubing, which may result in carryover into subsequent injections. Interested readers can look up the phenomenon of “backflash” for more information. In splitless injection mode, the solvent plays a major role in focusing analytes at the head of the analytical column, and so peak shape in the splitless mode, especially for less volatile analytes, will rely on the compatibility of the injection solvent polarity with that of the GC column stationary-phase material. Incompatibility will lead to shouldering and splitting analytes peaks.


The septum purge gas flows directly beneath the under face of the inlet septum and serves to carry any outgassing products and contaminants away from the septum material. It also has a role in controlling the degree of mass discrimination (relative discrimination between high- and low-boiling analytes), depending upon the configuration of the liner. While most modern GC systems will control the septum purge flow, it is encouraging to know what this setting is, and to manually check the flow prior to analysis. It wouldn’t be the first time that I’ve seen an electronic flow (or pressure) controller to be reading the incorrect value, and this problem can be very difficult to troubleshoot unless one knows to look for it! Stating the required value (typically just a few mL per minute) improves awareness for less experienced staff.


This the time at which the split vent is opened after sample injection in splitless injection mode. I only sporadically see the time associated with this variable written into analytical methods, which is surprising because it can critically affect baseline quality, peak shape of the solvent, and early-eluting analyte peaks as well as the quantitative reproducibility of early-eluting analytes. Ideally, the splitless time is empirically optimized such that the vast majority of all analytes have entered the column, and only the lingering excess sample solvent is ejected by opening the split valve. The optimization involves measuring the peak height (or area) of early eluting analytes while lengthening the splitless time. Too short a splitless time and the analyte peaks will continue to grow as the splitless time is lengthened, the peak area will eventually reach a constant value, and the ideal splitless time (typically 0.25 to 1.25 min post injection) is that which is associated with the second constant peak height or area measurement. Whenever specifying a splitless time, it is necessary to also specify the split flow rate or split ratio. A high split ratio is preferred to ensure that the excess sample solvent vapors are quickly ejected from the inlet to avoid an oversize and tailing solvent peak.


In split and splitless injection it is sometimes advisable to apply a higher inlet pressure during the sample introduction phase to reduce backflash (inlet contamination due to overspilled sample vapor) or to increase injection volume for increased sensitivity. The inlet pressures and flows, as well as the time for the increased pressure phase are very important in determining the quantitative accuracy of the method, and these parameters are typically empirically optimized, based on recommended manufacturers settings. The phasing of the pressure reduction with any splitless time is also crucial. It is good practice to lay out all of these variables in a table within the method and to optimize them carefully to avoid poor analyte peak shapes and very poor quantitative reproducibility, especially for early eluting analytes.


This is the time between the GC oven setpoint being reached and detected by the oven thermocouple and the instrument registering a “ready” state to begin the next injection in the sequence. This seemingly innocuous parameter is often ignored but can influence the selectivity and resolution of early-eluting compounds, and I’ve also known it to affect to the quantitative reproducibility. Essentially, just because the air within the GC oven has reached the setpoint temperature to begin the next analysis, the same is not necessarily true for the carrier gas flowing through the column, due to the thermal lag created by the capillary column walls and stationary phase. This is especially true for larger bore (internal diameter) columns and those with thicker stationary-phase films. If the carrier flowing through the column has not reached thermal equilibrium with the air within the oven, the temperature gradient effectively begins at the wrong temperature. This can affect critical processes governing analyte focusing and separation, resulting in irreproducibility. Always pay attention to this parameter and extend the equilibration time, if necessary, to correct any issues with peak shape (typically peak broadening of later eluting analytes) or retention time and resolution of earlier eluting analytes.

Initial oven temperature (splitless injection)


While all methods will cite the initial oven temperature within the temperature program, I wonder if we take the time to properly consider the importance of this parameter in splitless injection methods? To overcome gross peak broadening caused as the analyte slowly enters the column from the splitless inlet (analyte transfer typically occurs at the carrier gas flow rate), the analytes must be focused at the head of the GC column. This is usually achieved by condensation of higher boiling analytes and solvent trapping of the lower boiling analytes. Both processes are directly affected by the initial column temperature, and the general recommendation is that the initial oven temperature is 10–20 oC below the boiling point of the sample injection solvent to avoid peak broadening and shouldering. The time for which the initial oven temperature is held can also be crucial in determining peak shape in splitless injection and is typically empirically optimized. Do all your splitless methods follow the rules? Note that the column Equilibration Time (above) can also play a role in determining the peak shape in splitless injection and should also be empirically optimized.

Initial oven temperature and hold time (split injection)


Contrary to splitless injection, the mechanisms in split injection rely on faster analyte transfer from the inlet to the GC column and rapid onset of analyte migration through the capillary column. Any processes that retard the analyte progress risk the deposition and subsequent broadening of the analyte in the stationary phase film. Therefore, low initial oven temperatures and extended hold times at the initial temperature can affect both the peak shape and selectivity in split injection. These variables are sometimes highly influential of the quality of the separation and sometimes much less so, however, due consideration should be afforded during method development and troubleshooting.

GC column dimensions, carrier gas linear velocity, and head pressure


It’s good practice to cite not only the carrier gas type and flow rate but also the inlet pressure and resulting linear velocity of the carrier in your written methods. If the column dimensions or carrier gas type are accidently incorrectly entered into the instrument acquisition method, then the resulting required carrier head pressure and linear velocity of the carrier will be incorrect, and retention times will vary from those of the reference chromatogram or previous data. Knowing and, critically, checking the instrument head pressure and carrier gas linear velocity can be an excellent troubleshooting tool. The correct linear velocity and head pressure values can be read from the instrument prior to being written into the acquisition method during method development or validation.

Constant carrier gas pressure versus constant flow


Most modern GC instruments will offer the ability to maintain constant carrier gas flow by automatically increasing the head pressure applied during the temperature program. This avoids long elution times and broad peaks in the latter part of the chromatogram. One should ensure that the correct carrier mode is set in the instrument method, otherwise large discrepancies in retention time and peak shape will occur between the analysis obtained and reference chromatograms within the method, or previous chromatograms obtained under the correct carrier gas flow mode.

Variable FID makeup (constant column + makeup flow)

I’d like to concentrate on variables that can really impact our chromatography, but may be on hidden, supplementary, or advanced pages of our software, or may appear on the main software acquisitions menus, but are poorly understood or rarely altered. These variables are often not specifically referenced in laboratory methods documents or, if they do appear, are poorly understood. 