Fingerprint Multiplicity in MALDI-TOF Mass Spectrometry of Copolymers

Evaluation of the degradation of the graphene-polypropylene composites of masks in harsh working conditions

The recent COVID-19 outbreak has led health authorities to recommend at least the use of surgical masks, most preferably respirators (FFP2 or KN95), to prevent the spread of the virus. Non-woven fabrics have been chosen as the best option to manufacture the face masks, due to their filtration efficiency, low cost, and versatility. Modifying the mask filters with graphene has been of great interest due to its potential use as antibacterial and virucidal properties. Indeed, some companies have commercialized face masks in which graphene is coated and/or embedded. However, the Canadian sanitary authorities advised against using the Shandong Shengquan New Materials Co. graphene masks because of the possibility of pulmonary damage produced by graphene inhalation. Thus, we have analyzed the stability of the graphene filter of these masks and compared it with two other commercially available graphene mask filters, evaluating the morphological and spectroscopical change of the fibers, as well as the particles released during the endurance tests. Our work introduces the necessary tools and methodology to evaluate the potential degradation of face masks under extreme working conditions. These methods complement the present standard tests ensuring the security of the new filters based on composites or nanomaterials.

Encoding Information into Polyethylene Glycol Using an Alcohol-Isocyanate "Click" Reaction

In this article, the capability of encoding information using a homologous series of monodisperse monomethoxypolyethylene glycols (mPEG), with a number of ethylene oxide units ranging from n_EO = 5 to 8, and monodisperse linear aliphatic isocyanates containing a number of CH₂ units from 3 to 7, is demonstrated. The “click” reaction of the two corresponding homologous series yielded 20 different isocyanate end-capped polyethylene glycol derivatives (mPEG-OCONHR) whose sodiated adduct ion’s nominal m/z values spanned from 360 to 548, providing an average ca. 8 m/z unit for the storage of one-bit information. These mPEG-OCONHR oligomers were then used to encode information in binary sequences using a 384-well MALDI sample plate and employing the common dried-droplet sample preparation method capable of encoding 20 bit, i.e., 2.5 byte information in one spot, was employed. The information stored in the spots was read by MALDI-TOF MS using the m/z value of the corresponding mPEG-OCONHR oligomers. The capability of the method to store data was demonstrated by writing and reading a text file, visualizing a small picture and capturing a short audio file written in Musical Instrument Digital Interface (MIDI) sequence. Due to the very large similarities in the chemical structures of the encoding oligomers and their “easy to be ionized” property, as well as their very similar ionization efficiencies, the MALDI-TOF MS signal intensities from each compound was so strong and unambiguous that complete decoding could be performed in each case. In addition, the set of the proposed encoding oligomers can be further extended to attain higher bit “densities”.

MALDI-ToF mass spectrometry detection of intramolecular composition gradient in copolymers

Since their addition to the polymer-architecture portfolio, gradient copolymers have attracted significant attention. Up to now, however, the existence of the intramolecular composition gradient must have been ascertained by sampling during living copolymerization because a reliable method for the detection of the composition gradient in the finalized copolymer had not been established yet. Here we show that MALDI-ToF mass spectrometry not only identifies imperfect, i.e. prematurely terminated copolymers but these copolymers can be used as "time capsules" which provide information on composition evolution and the intramolecular composition gradient.

Exploring the Limits of the Geometric Copolymerization Model

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.

New Statistical Models for Copolymerization

For many years, copolymerization has been studied using mathematical and statistical models. Here, we present new Markov chain models for copolymerization kinetics: the Bernoulli and Geometric models. They model copolymer synthesis as a random process and are based on a basic reaction scheme. In contrast to previous Markov chain approaches to copolymerization, both models take variable chain lengths and time-dependent monomer probabilities into account and allow for computing sequence likelihoods and copolymer fingerprints. Fingerprints can be computed from copolymer mass spectra, potentially allowing us to estimate the model parameters from measured fingerprints. We compare both models against Monte Carlo simulations. We find that computing the models is fast and memory efficient.

Abundance correction for mass discrimination effects in polymer mass spectra

RATIONALE

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) is frequently used to analyze homo- and copolymers, i.e. for computing copolymer fingerprints. However, the oligomer abundances are influenced by mass discrimination, i.e. mass- and composition-dependent ionization. We have developed a computational method to correct the abundance bias caused by the mass discrimination.

METHODS

MALDI-TOFMS in combination with computational methods was used to investigate three random copolymers with different ratios of styrene and isoprene. Furthermore, equimolar high- and low-mass styrene and isoprene homopolymers (2500 and 4200 Da) were mixed and also analyzed by MALDI-TOFMS. The abundances of both copolymers and homopolymers were corrected for mass discrimination effects with our new method.

RESULTS

The novel computational method was integrated into the existing COCONUT software. The method was demonstrated using the measured styrene and isoprene co- and homopolymers. First, the method was applied to homopolymer spectra. Subsequently, the copolymer fingerprint was computed from the copolymer MALDI mass spectra and the correcting function applied. The changes in the composition are plausible, indicating that correction of copolymer abundances was reasonable.

CONCLUSIONS

Our computational method may help to avoid erroneous conclusions when analyzing copolymer MS spectra. The software is freely available and represents a step towards comprehensive computational support in polymer science. Copyright © 2016 John Wiley & Sons, Ltd.