Abundance correction for mass discrimination effects in polymer mass spectra

Engler, Martin S.; Crotty, Sarah; Barthel, Markus J.; Pietsch, Christian; Schubert, Ulrich S.; Böcker, Sebastian

doi:10.1002/rcm.7553

Cited by 6 publications

(6 citation statements)

References 35 publications

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“…Using mixtures of peptides, synthetic polymers and lipids, the authors showed the detection of analyte ions that had been suppressed with the traditional dry-drop method. Mass discrimination has always been a serious problem in MALDI-TOF MS. Engler et al devised a free module for COCONUT software to overcome mass discrimination when analyzing polymers . The authors illustrate the improvements of applying the software to spectra of three different styrene/isoprene copolymers, as well as their corresponding homopolymers.…”

Section: Traditional Ionization Methods For Msmentioning

confidence: 55%

“…Mass discrimination has always been a serious problem in MALDI-TOF MS. Engler et al devised a free module for COCONUT software to overcome mass discrimination when analyzing polymers. 149 The authors illustrate the improvements of applying the software to spectra of three different styrene/isoprene copolymers, as well as their corresponding homopolymers. Lu et al measured the ion-toneutral ratios of four common MALDI matrixes at 355 nm using a TOF-MS. 150 These authors noted that the ion-toneutral ratios are similar to those predicted by the thermal proton transfer model.…”

Section: ■ Traditional Ionization Methods For Msmentioning

confidence: 99%

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Advances in Ionization for Mass Spectrometry

Peacock¹,

Zhang

Trimpin

2016

Anal. Chem.

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Section: Traditional Ionization Methods For Msmentioning

confidence: 55%

Section: ■ Traditional Ionization Methods For Msmentioning

confidence: 99%

Advances in Ionization for Mass Spectrometry

Peacock¹,

Zhang

Trimpin

2016

Anal. Chem.

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“…Our model allows for computing the likelihood of a single polymer chain [24]. Let S be a sequence (polymer chain) and H a hypothesis, i.e., the geometric model.…”

Section: Methodsmentioning

confidence: 99%

Exploring the Limits of the Geometric Copolymerization Model

et al. 2017

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The geometric copolymerization model is a recently introduced statistical Markov chain model. Here, we investigate its practicality. First, several approaches to identify the optimal model parameters from observed copolymer fingerprints are evaluated using Monte Carlo simulated data. Directly optimizing the parameters is robust against noise but has impractically long running times. A compromise between robustness and running time is found by exploiting the relationship between monomer concentrations calculated by ordinary differential equations and the geometric model. Second, we investigate the applicability of the model to copolymerizations beyond living polymerization and show that the model is useful for copolymerizations involving termination and depropagation reactions.

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“…This mass discrimination in MALDI MS has been found to underestimate the polymer molecules of higher mass. [22][23][24] Thermal analysis…”

Section: Click Polymerizationmentioning

confidence: 99%