Flow Field Thermal Gradient Gas Chromatography

A hyper-fast gas chromatograph coupled to an ion mobility spectrometer with high repetition rate and flow-optimized ion source to resolve the short chromatographic peaks

By combining the high selectivity of a gas chromatograph (GC) with the high sensitivity and decent selectivity of an ion mobility spectrometer (IMS), GC-IMS have become increasingly popular in many applications. However, most GC suffer from long analysis times. In contrast, an hyper-fast GC allows for extremely fast analysis in the tens of seconds while reaching comparably high resolution. In turn, coupling such hyper-fast GC with IMS requires sufficiently high repetition rate of recording full IMS spectra to resolve the short GC peaks. Therefore, we present a drift tube IMS with 100 Hz repetition rate. Key is a small effective detector volume combined with short drift length. Therefore, the ion source of the IMS combines a small reaction region with an extended field-switching ion shutter and optimized gas flows. To resolve even the shortest GC peaks with a full width at half maximum of 100 ms, a short drift length of just 41 mm was used, achieving a measurement time of 10 ms per spectrum and hence ten data points across the shortest GC peak. To avoid condensation of the sample, the entire IMS was heated isothermally to 120 °C. Despite short drift times and high temperatures, the IMS still reaches high resolving power of Rp = 60. The hyper-fast GC-IMS reaches low detection limits in the low ppbV range. For demonstration, ketone mixes and three different hop varieties were analyzed in <30 s.

A fast thermal desorption unit for micro thermal desorption tubes, Part I: Development of the system and proof of concept measurements with hyper-fast gas chromatography

A system consisting of a thermal desorption unit (TDU) and micro thermal desorption tubes (μTD-tubes, 1.4 mm I.D., 10mg Tenax TA) for fast desorption of analytes was developed for the efficient combination of hyper fast gas chromatography with thermal desorption. The fast desorption is achieved by a significantly reduced thermal mass compared to conventional thermal desorption tubes. Therefore, extremely fast heating and cooling cycles are possible. Proof of concept measurements combining the new setup with a flow-field thermal gradient gas chromatograph (FF-TG-GC) and FID detection show good precision and linearity with R2≥0.995 in the analysis of an n-alkane mix (C8-C20). Thermal desorption occurs within 12s. The impact of reduced μTD-tube dimensions on desorption time, full width at half maximum (FWHM), breakthrough volumes, tube flow rates ergo linear velocities, porosity and back pressure is discussed.

Ultrafast Gas Chromatography-Tandem Differential Mobility Spectrometry: Toward A New Generation of On-Site, Real-Time Trace-Explosives Detection

In the defense and security sector, rapid detection of trace quantities of threat materials is paramount. Traditional instrumentation typically relies on standalone ion mobility techniques due to being inexpensive, portable, and highly sensitive. However, these techniques face limitations when handling complex samples, suffering from low resolving power (often less than 100) and ion-suppression effects, which can lead to false-positive and false-negative results. Here, we present a foundation to the solution through the hyphenation of the flow field thermal gradient gas chromatograph (FF-TG-GC) developed by HyperChrom with a tandem differential ion mobility spectrometer (DMS-DMS) developed in-house at New Mexico State University. The FF-TG-GC demonstrates the ability to separate a variety of nitroaromatic compounds of explosive significance in 20 s using a nitrogen carrier gas, highlighting the potential to offer selectivity advantages without substantially compromising high-throughput demands. These selectivity advantages are illustrated by the successful application of the FF-TG-GC-DMS-DMS to the detection and identification of single-nanogram loadings of 18 explosives and related substances in the presence of interfering materials, such as lactic acid, musk, and diesel. Furthermore, the system is capable of mitigating in-source ion-suppression effects by chromatographic separation of target analytes from background interference prior to ionization.

Development of a Multiplexing Injector for Gas Chromatography for the Time-Resolved Analysis of Volatile Emissions from Lithium-Ion Batteries

Multiplex sampling, so far mainly used as a tool for S/N ratio improvement in spectroscopic applications and separation techniques, has been investigated here for its potential suitability for time-resolved monitoring where chromatograms of transient signals are recorded at intervals much shorter than the chromatographic runtime. Different designs of multiplex sample introduction were developed and utilized to analyze lithium-ion battery degradation products under normal or abuse conditions to achieve fast and efficient sample introduction. After comprehensive optimization, measurements were performed on two different GC systems, with either barrier discharge ionization detection (BID) or mass spectrometric detection (MS). Three different injector designs were examined, and modifications in the pertinent hardware components and operational conditions used. The shortest achievable sample introduction time was 50 ms with an interval of 6 s. Relative standard deviations were lower than 4% and 10% for the intra- and inter-day repeatability, respectively. The sample introduction system and column head pressure had to be carefully controlled, as this parameter most critically affects the amount of sample introduced and, thus, detector response. The newly developed sample introduction system was successfully used to monitor volatile degradation products of lithium-ion batteries and demonstrated concentration changes over the course of time of the degradation products (e.g., fluoroethane, acetaldehyde and ethane), as well as for solvents from the battery electrolyte like ethyl carbonate.

Simulation of gas chromatographic separations and estimation of distribution-centric retention parameters using linear solvation energy relationships

For method development in gas chromatography, suitable computer simulations can be very helpful during the optimization process. For such computer simulations retention parameters are needed, that describe the interaction of the analytes with the stationary phase during the separation process. There are different approaches to describe such an interaction, e.g. thermodynamic models like Blumberg's distribution-centric 3-parameter model (K-centric model) or models using chemical properties like the Linear Solvation Energy Relationships (LSER). In this work LSER models for a Rxi-17Sil MS and a Rxi-5Sil MS GC column are developed for different temperatures. The influences of the temperature to the LSER system coefficients are shown in a range between 40 and 200 °C and can be described with Clark and Glew's ABC model as fit function. A thermodynamic interpretation of the system constants is given and its contribution to enthalpy and entropy is calculated. An estimation method for the retention parameters of the K-centric model via LSER models were presented. The predicted retention parameters for a selection of 172 various compounds, such as FAMEs, PCBs and PAHs are compared to isothermal determined values. 40 measurements of temperature programmed GC separations are compared to computer simulations using the differently determined or estimated K-centric retention parameters. The mean difference (RSME) between the measured and predicted retention time is less than 8 s for both stationary phases using the isothermal retention parameters. With the LSER predicted parameters the difference is 20 s for the Rxi-5Sil MS and 38 s for the Rxi-17Sil MS. Therefore, the presented estimation method can be recommended for first method development in gas chromatography.

Relation between characteristic temperature and elution temperature in temperature programmed gas chromatography - part I: Influence of initial temperature and heating rate

The development of new analytical methods can save resources, time and costs if there are prediction tools like computer simulation which support the optimization process. In GC the distribution-centric 3-parameter model (K-centric model) is well established for prediction of retention factors k and retention times but laborious isothermal measurements for determination of the characteristic parameters are needed. For the most important parameter, the characteristic temperature Tchar, the search for simpler determination methods or even estimates is an interesting research topic. In this work the elution temperatures for 37 fatty acid methyl esters, 6 BTEXs and 40 other volatile substances are determined by measurements under variable heating rates, initial temperatures, constant pressure mode and constant flow mode. The relationship between the measured elution temperature and the characteristic temperature was investigated. The novel multivariate curve fit model presented in this study describes accurately the relation between the characteristic temperature Tchar and elution temperatures Telu under variable heating rates RT, respectively, and initial temperature Tinit conditions. The novel model shows good accordance to earlier estimation models and expands the prediction range, especially for high volatile compounds. The model is suitable for determination of Tchar by estimated Telu and vice versa. Predictions of retention times of simple temperature programs were also possible by using the model with relative deviations < 5% compared to measurements.

Retention Database for Prediction, Simulation, and Optimization of GC Separations

This work presents an open source database with suitable retention parameters for prediction and simulation of GC separations and gives a short introduction to three common retention models. Useful computer simulations play an important role to save resources and time in method development in GC. Thermodynamic retention parameters for the ABC model and the K-centric model are determined by isothermal measurements. This standardized procedure of measurements and calculations, presented in this work, have a useful benefit for all chromatographers, analytical chemists, and method developers because it can be used in their own laboratories to simplify the method development. The main benefits as simulations of temperature-programed GC separations are demonstrated and compared to measurements. The observed deviations of predicted retention times are in most cases less than 1%. The database includes more than 900 entries with a large range of compounds such as VOCs, PAHs, FAMEs, PCBs, or allergenic fragrances over 20 different GC columns.

Estimation of retention parameters from temperature programmed gas chromatography

A fast and reliable method is presented to evaluate retention parameters of the distribution-centric 3-parameter model from temperature programed gas chromatographic measurements. Based on a fully differentiable model of the migration of solutes in a gas chromatographic (GC) system, Newton's method with a trust region is used to determine the three parameters, respectively the three parameters and the column diameter, of several solutes as the minima of the difference between measured and calculated retention times. The determined retention parameters can then be used in method development, using the simulation of GC separation. The results of the retention parameters are compared to the parameters determined using isothermal GC measurements and show good agreement, with deviations of less than 0.5% (1.8 K) for the most important parameter of characteristic temperature T_char. Using the estimated retention parameters, additional GC separations are simulated and compared with measurements. Retention times in additional temperature programmed measurements could be predicted with less than 0.7% deviation. Four to five different temperature programs are enough to determine reliable retention parameters. Unless the column diameter and the column length are exactly known, it is preferable to also estimate the diameter (more precisely the L/d-ratio) together with the retention parameters.

Theory of linear focusing in chromatographic columns with exponential retention. Part 1: Basic solutions

This report is the first of 2-part study of the effect of gradients in column parameters on the column performance. If t, x and p are, respectively, time since sample introduction, distance from column inlet and some parameter of solute migration along the column then ∂p/∂t and ∂p/∂x are, respectively, the rate of changing p and the gradient of p. Unified approach to study of gradients and rates in different chromatographic techniques (LC, GC, etc.) has been developed. To facilitate a unified approach, the umbrella term mobilization (y) representing column temperature (T) in GC, solvent composition (ϕ) in LC, etc. is introduced. Differential equations for migration of a solute band (collection of solute molecules) under the following conditions are formulated and solved:The key solutions describe the time of migration of a solute band and the band width - both as functions of the distance traveled by the band. The solutions are used in Part 2 for the study of the effects of the negative gradients in y on column performance in several practically important cases. A reduction of the key general solutions to much simpler equations for gradient LC has been demonstrated herein as an example.

Optimizing column-to-column retention time alignment in high-speed gas chromatography by combining retention time locking and correlation optimized warping

We examine and then optimize alignment of chromatograms collected on nominally identical columns using retention time locking (RTL), an instrumental alignment tool, and software-based alignment using correlation optimized warping (COW). For this purpose, three samples are constructed by spiking two sets of analytes into a base test mixture. The three samples are analyzed by high-speed gas chromatography with four nominally identical columns and identical separation conditions. The data is first analyzed without alignment, then using COW alone, then RTL alone, and finally with RTL followed by COW to correct the severe column-to-column misalignment. Principal component analysis (PCA) is used to investigate how well each alignment method clustered the chromatograms into the three sample classes via a scores plot without being compromised by the specific column(s) used. The degree-of-class separation (DCS) is used as a classification metric, measured as the Euclidian distance between the centroids of two clusters in PC space in the scores plot, normalized by their pooled variance. With no alignment, the average DCS between sample classes (DCS_sam) was 3.0, while the average DCS between the four nominally identical columns, i.e., column classes (DCS_col) was 76.1 (ideally the DCS_col should be 0), indicating the chromatograms were initially classified by the columns used. Using either COW or RTL alone also produced unsatisfactory results, with COW alone incorrectly aligning many peaks, leading to a DCS_sam of only 1.9 and DCS_col of 1.7, while RTL alone provided a DCS_sam of 4.7 and DCS_col of 4.2. Finally, using RTL followed by COW alignment, DCS_sam increased to 32.5, indicating successful classification by chemical differences between sample classes, while the DCS_col decreased to 0.4, indicating virtually no classification due to column-to-column differences, as desired. Thus, RTL provided a "first-order" correction of the initial retention mismatch observed for the nominally identical columns, while additional alignment via COW was required to optimize sample classification by PCA.

A fast temperature-programmed second-dimension column for comprehensive two-dimensional gas chromatography

The short analysis time and constant temperature environment in the second dimension of two-dimensional comprehensive chromatography frequently causes wraparound problems, especially for complex high boilers. This problem can be solved by temperature programming on the second column, but since this requires heating and cooling the column in a matter of seconds, it is difficult to implement. In this study, we describe a method of accomplishing rapid heating and cooling with a resistively heated column cooled by compressed air. Critical to this method is minimizing the lag time between the actual temperature and the reported temperature by using the column heating element as the temperature sensor, virtually eliminating the danger of overshooting the temperature setpoint. This technique facilitates a ramp rate of up to 100 °C/s with minimal overshooting-well beyond the requirements of gas chromatography. A single-layer column bundle design allows a compressed-air cooling device to cool the column from 200 to 50 °C at an average rate of -21 °C/s. The secondary dimension temperature programming is facilitated by the longer secondary dimension time made possible by the direct flow modulation method. We evaluated the performance of the single-layer column bundle and demonstrated this method by applying it to a gasoline sample. We also compared this method with the traditional isothermal approach and found that use of the secondary temperature program reduced the naphthalene retention time from 12.1 to 6.3 s and its peak width at half height from 846 to 126 ms.

Comparison of the Dynamic Thermal Gradient to Temperature-Programmed Conditions in Gas Chromatography Using a Stochastic Transport Model

This paper compares dynamic (i.e., temporally changing) thermal gradient gas chromatography (GC) to temperature-programmed GC using a previously published stochastic transport model to simulate peak characteristics for the separation of C12-C40 hydrocarbons. All comparisons are made using chromatographic conditions that give approximately equal analyte retention times (t_R). As shown previously, a static thermal gradient does not improve resolution (R_s) equally for all analytes, which highlights the need for a dynamic thermal gradient. An optimal dynamic thermal gradient should result in constant analyte velocities at any instant in time for those analytes that are actively being separated (i.e., analytes that have low retention factors). The average separation temperature for each analyte is used to determine the thermal gradient profile at different times in the temperature ramp. Because many of the analytes require a similar thermal gradient profile when actively being separated, the thermal gradient profile in this study was held fixed; however, the temperature of the entire thermal gradient was raised over time. From the simulations performed in this study, optimized dynamic thermal gradient conditions are shown to improve R_s by up to 13% over comparative temperature-programmed conditions, even with a perfect injection (i.e., zero injection bandwidth). In the dynamic thermal gradient simulations, all analytes showed improvements in R_s along with slightly shorter t_R values compared to simulations for traditional temperature-programmed conditions.

Comparison of Static Thermal Gradient to Isothermal Conditions in Gas Chromatography Using a Stochastic Transport Model

This paper compares static (i.e., temporally unchanging) thermal gradient gas chromatography (GC) to isothermal GC using a stochastic transport model to simulate peak characteristics for the separation of C12-C14 hydrocarbons resulting from variations in injection bandwidth. All comparisons are made using chromatographic conditions that give approximately equal analyte retention times so that the resolution and number of theoretical plates can be clearly compared between simulations. Simulations show that resolution can be significantly improved using a linear thermal gradient along the entire column length. This is mainly achieved by partially compensating for loss in resolution from the increase in mobile phase velocity, which approximates an ideal, basic separation. The slope of the linear thermal gradient required to maximize resolution is a function of the retention parameters, which are specific to each analyte pair; a single static, thermal gradient will not affect all analytes equally. A static, non-linear thermal gradient that creates constant analyte velocities at all column locations provides the largest observed gains in resolution. From the simulations performed in this study, optimized linear thermal gradient conditions are shown to improve the resolution by as much as 8.8% over comparative isothermal conditions, even with a perfect injection (i.e., zero initial bandwidth).

Residual solvent analysis with hyper-fast gas chromatography-mass spectrometry and a liquid carbon dioxide cryofocusing in less than 90 s

A new hyper-fast gas chromatography method with less than 90 s runtime including the column cool down was developed for the analysis of four gases and 16 residual solvents, combining a CO₂ cryofocusing with a flow-field thermal gradient gas chromatograph (FF-TG-GC) and ToF-MS. The extremely low analysis time can be achieved by combining the new FF-TG-GC and a very short Rxi-624 Sil MS separation column with a small inner diameter and small film thickness (2.05 m × 0.1 mm × 1.0 µm). The column is inserted into a low thermal mass, resistively heated stainless steel capillary. This enables fast temperature programs with heating rates up to 3000 °C/min and a column cool down within a few seconds. In addition to temporal temperature gradients, the FF-TG-GC can generate a spatial temperature gradient that leads to an improved peak shape. Further, an external liquid CO₂ cryo-trap was designed in order to reduce the injection bandwidths of analytes and to take full advantage of the resolving power of the separation column. No modifications are required to the FF-TG-GC for the use of the cryogenic trap, as the cooled spot is heated by the resistively heated stainless steel capillary during the temperature program. With cryofocusing, analyzed residual solvents are baseline separated. R² values over 0.99 for calibration curves and low relative standard deviations (mainly < 3%) for repeatability tests were obtained.

Simulation of the effects of negative thermal gradients on separation performance of gas chromatography

The effect of a gradient of solute velocity on the chromatographic separation of closely spaced solutes is investigated by usage of a simulation. The concept of the ideal basic separation (IBS), introduced by Blumberg, is used to determine the theoretical limit of a separation without any natural or artificial gradients of features of the chromatographic medium. The IBS is the best achievable separation and can therefore be used as a baseline to which other separations can be compared to. An addition of a negative velocity gradient cannot improve the separation of closely spaced solutes. The velocity gradient is realized by adding a temperature gradient to a GC separation. The simulation confirms this theoretical limit for a range of differently strong retained solutes. In a second part controlled deviations from IBS are used to show, that a velocity gradient can be beneficial in realistic, non-IBS. The addition of a negative velocity gradient can improve e.g. the separation of broad injected solute zones or counteract a positive gradient of the mobile phase velocity caused by gas decompression along the GC column. However, the improved separation cannot exceed that of a corresponding ideal basic separation. The resolution of broadly injected solutes can be increased by up to 45% of the corresponding IBS resolution by adding a negative velocity gradient. A positive velocity gradient due to gas decompression reduces the separation by up to 6%. The added negative velocity gradient, realized by a linear temperature gradient, can compensate this resolution loss by up to 2%.

High-throughput platforms for metabolomics

Mass spectrometry has become a choice method for broad-spectrum metabolite analysis in both fundamental and applied research. This can range from comprehensive analysis achieved through time-consuming chromatography to the rapid analysis of a few target metabolites without chromatography. In this review article, we highlight current high-throughput MS-based platforms and their potential application in metabolomics. Although current MS platforms can reach throughputs up to 0.5 seconds per sample, the metabolite coverage of these platforms are low compared to low-throughput, separation-based MS methods. High-throughput comes at a cost, as it's a trade-off between sample throughput and metabolite coverage. As we will discuss, promising emerging technologies, including microfluidics and miniaturization of separation techniques, have the potential to achieve both rapid and more comprehensive metabolite analysis.