Prediction of Retention Time and Collision Cross Section (CCSH+, CCSH- and CCSNa+) of emerging contaminants using Multiple Adaptive Regression Splines

Ultra-high performance liquid chromatography coupled to ion mobility separation and high-resolution mass spectrometry instruments have proven very valuable for screening of emerging contaminants in the aquatic environment. However, when applying suspect or non-target approaches (i.e. when no reference standards are available) there is no information on retention time (RT) and collision cross section (CCS) values to facilitate identification. In-silico prediction tools of RT and CCS can therefore be of great utility to decrease the number of candidates to investigate. In this work, Multiple Adaptive Regression Splines (MARS) was evaluated for the prediction of both RT and CCS. MARS prediction models were developed and validated using a database of 477 protonated molecules, 169 deprotonated molecules and 249 sodium adducts. Multivariate and univariate models were evaluated showing a better fit for univariate models to the empirical data. The RT model (R2=0.855) showed a deviation between predicted and empirical data of ± 2.32 min (95% confidence intervals). The deviation observed for CCS data of protonated molecules using CCSH model (R2=0.966) was ± 4.05% with 95% confidence intervals. The CCSH model was also tested for the prediction of deprotonated molecules resulting in deviations below ± 5.86% for the 95% of the cases. Finally, a third model was developed for sodium adducts (CCSNa, R2=0.954) with deviation below ± 5.25% for the 95% of the cases. The developed models have been incorporated in an open access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data.

Dynamics of formation of during inhibition of steel by sulfanilamide in solutions of hydrochloric acid with different pH

Experimentally proved by the method of polarization resistance formation of protective layers during inhibition steel corrosion by Sulfanilamide in aqueous solutions of hydrochloric acid with different pH. It is shown the difference due to the predominance of the protonated or unprotonated form of the molecule. It was found that at predominance of protonated forms of molecules (pH £2,4) formed dense protective films and predominance of unprotonated forms of molecules (pH ³2,4) are formed layers that do not inhibit diffusion processes. Sulfanilamide provides high and stable inhibition efficiency (<90%) in acid chloride solutions in case of formation protective layers consisting of protonated molecules what to consider when use it.

A New Library-Search Algorithm for Mixture Analysis Using DART-MS

This manuscript introduces a new library-search algorithm for identifying components of a mixture using in-source collision-induced dissociation (is-CID) mass spectra. The two-stage search, titled the Inverted Library-Search Algorithm (ILSA), identifies potential components in a mixture by first searching its low fragmentation mass spectrum for target peaks, assuming these peaks are protonated molecules, and then scoring each target peak with possible library matches using one of two schemes. Utility of the ILSA is demonstrated through several example searches of model mixtures of acetyl fentanyl, benzyl fentanyl, amphetamine and methamphetamine searched against a small library of select compounds and the NIST DART-MS Forensics library. Discussion of the search results and several open areas of research to further extend the method are provided. A prototype implementation of the ILSA is available at <a href="https://github.com/asm3-nist/DART-MS-DST">https://github.com/asm3-nist/DART-MS-DST</a>.

A New Library-Search Algorithm for Mixture Analysis Using DART-MS

This manuscript introduces a new library-search algorithm for identifying components of a mixture using in-source collision-induced dissociation (is-CID) mass spectra. The two-stage search, titled the Inverted Library-Search Algorithm (ILSA), identifies potential components in a mixture by first searching its low fragmentation mass spectrum for target peaks, assuming these peaks are protonated molecules, and then scoring each target peak with possible library matches using one of two schemes. Utility of the ILSA is demonstrated through several example searches of model mixtures of acetyl fentanyl, benzyl fentanyl, amphetamine and methamphetamine searched against a small library of select compounds and the NIST DART-MS Forensics library. Discussion of the search results and several open areas of research to further extend the method are provided. A prototype implementation of the ILSA is available at <a href="https://github.com/asm3-nist/DART-MS-DST">https://github.com/asm3-nist/DART-MS-DST</a>.

Gas phase protonated nicotine is a mixture of pyridine- and pyrrolidine-protonated conformers: implications for its native structure in the nicotinic acetyl-choline receptor

The infrared (IR) spectra of gas phase protonated nicotine has been measured in the never-before probed N-H “fingerprint region” (3,200–3,500 cm−1). The protonated molecules generated by an electrospray source are...

Tentative detection of HC5NH+ in TMC-1

Using the Yebes 40m radio telescope, we report the detection of a series of seven lines harmonically related with a rotational constant B0 = 1295.81581 ± 0.00026MHz and a distortion constant D0 = 27.3 ± 0.5Hz towards the cold dense cloud TMC-1. Ab initio calculations indicate that the best possible candidates are the cations HC5NH+ and NC4NH+. From a comparison between calculated and observed rotational constants and other arguments based on proton affinities and dipole moments, we conclude that the best candidate for a carrier of the observed lines is the protonated cyanodiacetylene cation, HC5NH+. The HC5N/HC5NH+ ratio derived in TMC-1 is 240, which is very similar to the HC3N/HC3NH+ ratio. Results are discussed in the framework of a chemical model for protonated molecules in cold dense clouds.