Peak deconvolution to correctly assess the band broadening of chromatographic columns

Vanderheyden, Yoachim; Broeckhoven, Ken; Desmet, Gert

doi:10.1016/j.chroma.2016.08.058

Cited by 27 publications

(38 citation statements)

References 70 publications

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“…After significant corrections for noise phenomena, was obtained by means of peak-width methods and moment methods excellent correspondence between theory and experiment, also in strong support to plate theory [35]. Deconvolution by means of Fourier transforms results in drawbacks with reduction of noise that need be dealt with according to additional empirical theories [35,36]. The lag time of the detector has a smoothing effect on the observed signal [38], and the degree of influence on the signal of chromatographic elution is investigated herein for the simple case of pulse flow.…”

Section: Introductionsupporting

confidence: 66%

Section: Introductionmentioning

confidence: 53%

“…Most chromatographic theories predict a Gaussian-shaped distribution of concentrations along the length of the pipe [13,14], and the corresponding full width at half maximum (FWHM) increases as a function of time when the segment moves downstream. The optimum conditions of peak shape with respect to chromatographic separation are described by the Van Deemter equation [23], which is widely used for purposes of optimization [35]. Very large injection volumes produce long segments when injected into narrow pipes, and the resulting 'square distribution' of the concentration of solute molecules is pulse-like [11,25,36] rather than Gaussian shaped [11,37].…”

Section: Introductionmentioning

confidence: 99%

“…That correction provided peaks with no tail and slightly reduced retention times, and it added to the understanding of plate theory [36]. Vanderheyden et al [35] introduced peak deconvolution by using the Pap-Pápai equation [41] and two exponentially-modified Gaussian curves to describe the peak.…”

Section: Introductionmentioning

confidence: 99%

“…The principle of peak deconvolution by Gaussian functions is a widely accepted method of extracting additional information about the constituents of the observed peak [35,36,42]. In chromatography, deconvolution has two different meanings comprising: (1) To prepare a linear combination of Gaussian functions to describe the observed peak [42], (2) Perform signal reconstitution by mathematical deconvolution of the observed peak with an extra-column band broadening function [35,36].…”

Section: Introductionmentioning

confidence: 99%

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Signal convolution indicates chromatographic pulse flow and open-end flow

2019

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Only slices are measured of very long segments of solute molecules that are injected into columns in chromatographic systems. Since the concentration of solute molecules changes during elution as a function of time, the observed signal should be reconstructed for a comparison of experimental results with theory. The influence of response time on the observed signal in high-performance liquid chromatography experiments was investigated in detail using a C-18 column for the measurement of caffeine in pure methanol as eluent. The response function influenced the observed signal by converting the square signal of pulse flow into a chromatographic peak. At faster linear flow rates (LFRs), the response function influenced the observed shape of the chromatographic peak, whereas diffusion dominated at slow LFRs. By convolution of the square signal with the response function, it was possible to predict the shape of the observed signal and chromatographic parameters and to provide an alternative explanation to the van Deemter equation. By using the shape of a known response function and modelling the new theory to data, it was proposed that the injected solute molecules were eluted over long distances through the chromatographic column, distances that are much longer than the physical length of the system.

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Section: Introductionsupporting

confidence: 66%

Section: Introductionmentioning

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Signal convolution indicates chromatographic pulse flow and open-end flow

2019

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Evaluation of the van Deemter equation in terms of open‐ended flow to chromatography

Andersen

Mukami

Maina

2020

J of Separation Science

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Plate theory and adsorption theory are the main tools available for understanding chromatographic experiments. Both theories predict a Gaussian distribution of solute molecules within the tubular system. However, Gaussian concentration distributions are observed predominantly at slow linear flow rates, while asymmetric concentration distributions are observed at the linear flow rates most used in chromatography. Allegedly, this asymmetry originates from an inhomogeneous distribution of grain sizes in the column and column overload. However, it is an experimental fact that the distribution of chemicals within an injected volume of solute changes as a function of time, while the response is measured simultaneously. Accordingly, the obtained signal cannot be compared to the theory before some type of time‐based deconvolution of the data has been performed. Adjustments to high‐performance liquid chromatography data were thus proposed through empirical equations that describe the relevant time values, peak height, peak area, and parameters of the van Deemter equation. It was proposed that the transfer of solute from the front to the rear part of the pulse during laminar open‐ended flow occurs at rate that depends on the linear flow rate, and to a lesser extent, on properties of the response function.

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