Peak shape analysis and plate theory for plasma chromatography

Spangler, Glenn E.; Collins, Charles I.

doi:10.1021/ac60353a013

Cited by 94 publications

(71 citation statements)

References 12 publications

(21 reference statements)

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“…Otherwise, the spreading due to diffusion in the peak model will not scale properly with the position of the peak in the plasmagram. This result is consistent with the work of Spangler and Collins in 1975 [15] although the derivation presented here is more simplified from the frequency domain signal processing approach. Equation 12 offers a useful design guide on the optimal gate time for a given plasmagram peak mobility.…”

Section: The Ideal Gate Shuttersupporting

confidence: 91%

Decomposition of overlapping plasmagram peaks by spectral subtraction

Swanson

2011

Int. J. Ion Mobil. Spec.

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Low field atmospheric pressure Ion Mobility Spectroscopy (IMS) involves the careful analysis of plasmagrams with multiple peaks which can mask one another when they are closely spaced in drift time or corresponding reduced mobility. A typical signal processing approach to decomposing overlapped peaks would be to use an orthogonal decomposition technique, but unfortunately Gaussian-like functions are not orthogonal, so no unique decomposition can be guaranteed. However, each ion species in the drift tube will arrive at the Faraday plate with a known statistical distribution determined by the IMS instrument's drift tube design, electric field strength, reagent gas flow and other instrument-specific factors such as the ion gate function. This paper presents a straightforward algorithm for decomposing plasmagrams into distinct peaks using a subtractive technique that independently estimates the statistical parameters of each peak, rejecting spurious peaks and electrical noise. The results show that for relatively short gate times, the plasmagram peaks are nearly Gaussian-shaped, but slightly fatter and asymmetric. We show that including of the gate rise and fall times is also significant in matching the plasmagram peak shape. We also show that the diffusion effects on resolution can be attributed to combinations of non-uniform ion distributions in the reaction chamber as well as detritus effects in the drift tube. Given the known peaks statistical parameters, one can then separate overlapping peaks using a straightforward spectral subtractive technique.

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Section: The Ideal Gate Shuttersupporting

confidence: 91%

Decomposition of overlapping plasmagram peaks by spectral subtraction

Swanson

2011

Int. J. Ion Mobil. Spec.

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“…Recall that the IRM mode (in V s cm −2 ) is simply m = C t|d · d * , where C t|d is the conversion constant between drift time and IRM (see Section 'Data from MCC/IMS measurements'). Spangler et al [14] empirically derived that ω1 / On the retention time axis, the peak width ω1 /2 grows approximately linearly with retention time, i.e., there are constants r_width_offset > 0 and r_width_factor > 0 such that width of a peak with maximum at retention time r is approximately ξ(r) := r · r_width_factor + r_width_offset .…”

Section: Assumptionsmentioning

confidence: 99%

An Online Peak Extraction Algorithm for Ion Mobility Spectrometry Data

Kopczynski

Rahmann

2014

Lecture Notes in Computer Science

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Ion mobility (IM) spectrometry (IMS), coupled with multi-capillary columns (MCCs), has been gaining importance for biotechnological and medical applications because of its ability to detect and quantify volatile organic compounds (VOC) at low concentrations in the air or in exhaled breath at ambient pressure and temperature. Ongoing miniaturization of spectrometers creates the need for reliable data analysis on-the-fly in small embedded low-power devices. We present the first fully automated online peak extraction method for MCC/IMS measurements consisting of several thousand individual spectra. Each individual spectrum is processed as it arrives, removing the need to store the measurement before starting the analysis, as is currently the state of the art. Thus the analysis device can be an inexpensive low-power system such as the Raspberry Pi. The key idea is to extract one-dimensional peak models (with four parameters) from each spectrum and then merge these into peak chains and finally two-dimensional peak models. We describe the different algorithmic steps in detail and evaluate the online method against state-of-the-art peak extraction methods.

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“…The background with respect to IMS is described in [2,15]. The motion of electrons and ions in gases is described using different mathematical functions [16][17][18]: A detailed peak shape analysis for IMS spectra was reported by Glasser [19], Eiceman [20] considers electrical parameter, Goubran [21] investigated experimental signal analysis, Spangler [22] included theoretical aspects, Guevremont [23] compared experimental and calculated peak shapes in FAIMS.…”

Section: Introductionmentioning

confidence: 99%

Breit-Wigner-Function and IMS-signals

Vogtland

Baumbach

2009

Int. J. Ion Mobil. Spec.

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Theoretical considerations to describe the motion of ion swarms in weak electrical fields in gases at ambient pressure normally start with pulses of Gaussian form to inject ions in the drift region of the ion mobility spectrometer. The influence of the drift gas flowing contrary to the ion drift direction is mostly neglected with respect to the form of the pulse. At the Faraday-plate a superposition of the balance between energy gain between the collisions and loss by collisions with neutral molecules during the drift towards the electrode and influence of the motion of the drift gas molecules flowing contrary becomes visible in peak shape. An analytical description on the basis of Gaussian-and Breit-Wigner-Functions is presented for the single spectrum as well as for 3D-dependences within MCC/IMS with regard to the additional influence of retention time dependencies.

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Peak shape analysis and plate theory for plasma chromatography

Cited by 94 publications

References 12 publications

Decomposition of overlapping plasmagram peaks by spectral subtraction

Decomposition of overlapping plasmagram peaks by spectral subtraction

An Online Peak Extraction Algorithm for Ion Mobility Spectrometry Data

Breit-Wigner-Function and IMS-signals

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