Direct Dielectric Barrier Discharge Ionization Promotes Rapid and Simple Lubricant Oil Fingerprinting

Plasma-based ambient mass spectrometry: Recent progress and applications

Ambient mass spectrometry (AMS) has grown as a group of advanced analytical techniques that allow for the direct sampling and ionization of the analytes in different statuses from their native environment without or with minimum sample pretreatments. As a significant category of AMS, plasma-based AMS has gained a lot of attention due to its features that allow rapid, real-time, high-throughput, in vivo, and in situ analysis in various fields, including bioanalysis, pharmaceuticals, forensics, food safety, and mass spectrometry imaging. Tens of new methods have been developed since the introduction of the first plasma-based AMS technique direct analysis in real-time. This review first provides a comprehensive overview of the established plasma-based AMS techniques from their ion source configurations, mechanisms, and developments. Then, the progress of the representative applications in various scientific fields in the past 4 years (January 2017 to January 2021) has been summarized. Finally, we discuss the current challenges and propose the future directions of plasma-based AMS from our perspective.

Thermogravimetry combined with electrospray and atmospheric pressure chemical ionization mass spectrometry for characterization of synthetic polymers

RATIONALE

Thermogravimetry (TG) combined with electrospray and atmospheric chemical ionization (ESI+APCI) mass spectrometry (MS) was developed to rapidly characterize thermal decomposition products of synthetic polymers and plastic products. The ESI-based TG-MS method is useful for characterizing thermally labile, nonvolatile, and polar compounds over an extensive mass range; and the APCI-based TG-MS counterpart is useful for characterizing volatile and nonpolar compounds. Both polar and nonpolar compounds can be simultaneously detected by ESI+APCI-based TG-MS.

METHODS

Analytes with different volatility were produced from TG operated at different temperatures, which were delivered through a heated stainless-steel tube to the ESI+APCI source where they reacted with the primary charged species generated from electrospray and atmospheric pressure chemical ionization (ESI+APCI) of solvent and nitrogen. The analyte ions were then detected by an ion trap mass spectrometer.

RESULTS

A semi-volatile PEG 600 standard was used as the sample and protonated and sodiated molecular ions together with adduct ions including [(PEG)n + 15]⁺ , [(PEG)n + 18]⁺ , and [(PEG)n + 29]⁺ were detected by TG-ESI+APCI-MS. The technique was further utilized to characterize thermal decomposition products of nonvolatile polypropylene glycol (PPG) and polystyrene (PS) standards, as well as a PS-made water cup and coffee cup lid. The characteristic fragments of PPG and PS with mass differences of 58 and 104 between respective ion peaks were detected at the maximum decomposition temperature (T_max ).

CONCLUSIONS

The information obtained from the TG-ESI+APCI-MS analysis is useful in rapidly distinguishing different types of polymers and their products. In addition, the signals of the additives in the polymer products, including antioxidants and plasticizers, were also detected before the TG temperature reached T_max .

Detailed chemical analysis of a fully formulated oil using dielectric barrier discharge ionisation-mass spectrometry

RATIONALE

Fully formulated oils (FFOs) are integral to automotive lubrication; however, detailed compositional analysis is challenging due to high levels of chemical complexity. In particular, existing mass spectrometric approaches often target particular FFO components, leading to poor analytical coverage of the overall formulation, with increased overheads and analytical timescales.

METHODS

Herein we report the application of a commercially available SICRIT SC-20 dielectric barrier discharge ionisation (DBDI) source and Thermo Fisher Scientific LTQ Orbitrap XL to the analysis of an FFO. Nitrogen was used as a discharge gas for the DBDI source, and was modified using a range of commonplace solvents to tailor the experimental conditions for the analysis of various components.

RESULTS

The reported method allowed analysis of a range of FFO components of interest, encompassing a wide range of chemistries, in under 1 min. By modifying the discharge gas used for ionisation, experiments could be optimised for the analysis of particular FFO components across positive and negative ion modes. In particular, use of water vapour as a discharge gas modifier with positive ion mode mass spectrometry permitted concomitant analysis of antioxidants and base oil hydrocarbons. Furthermore, case studies of selected linear alkanes and alkenes profile the differences in the range of ions formed across these saturated and unsaturated aliphatic compounds, giving insight into the fate of base oil hydrocarbons in FFO analyses.

CONCLUSIONS

A rapid method for analysis of FFO compositions has been developed and provides coverage of a range of components of interest. The results indicate that the method presented may be of utility in analysis of other FFOs or similarly challenging complex mixtures.

The Often-Overlooked Power of Summary Statistics in Exploratory Data Analysis: Comparison of Pattern Recognition Entropy (PRE) to Other Summary Statistics and Introduction of Divided Spectrum-PRE (DS-PRE)

Unsupervised exploratory data analysis (EDA) is often the first step in understanding complex data sets. While summary statistics are among the most efficient and convenient tools for exploring and describing sets of data, they are often overlooked in EDA. In this paper, we show multiple case studies that compare the performance, including clustering, of a series of summary statistics in EDA. The summary statistics considered here are pattern recognition entropy (PRE), the mean, standard deviation (STD), 1-norm, range, sum of squares (SSQ), and X⁴, which are compared with principal component analysis (PCA), multivariate curve resolution (MCR), and/or cluster analysis. PRE and the other summary statistics are direct methods for analyzing data-they are not factor-based approaches. To quantify the performance of summary statistics, we use the concept of the "critical pair," which is employed in chromatography. The data analyzed here come from different analytical methods. Hyperspectral images, including one of a biological material, are also analyzed. In general, PRE outperforms the other summary statistics, especially in image analysis, although a suite of summary statistics is useful in exploring complex data sets. While PRE results were generally comparable to those from PCA and MCR, PRE is easier to apply. For example, there is no need to determine the number of factors that describe a data set. Finally, we introduce the concept of divided spectrum-PRE (DS-PRE) as a new EDA method. DS-PRE increases the discrimination power of PRE. We also show that DS-PRE can be used to provide the inputs for the k-nearest neighbor (kNN) algorithm. We recommend PRE and DS-PRE as rapid new tools for unsupervised EDA.

Applications of ambient ionization mass spectrometry in 2020: An annual review

Recent developments in mass spectrometry (MS) analyses have seen a concerted effort to reduce the complexity of analytical workflows through the simplification (or removal) of sample preparation and the shortening of run-to-run analysis times. Ambient ionization mass spectrometry (AIMS) is an exemplar MS-based technology that has swiftly developed into a popular and powerful tool in analytical science. This increase in interest and demonstrable applications is down to its capacity to enable the rapid analysis of a diverse range of samples, typically in their native state or following a minimalistic sample preparation approach. The field of AIMS is constantly improving and expanding, with developments of powerful and novel techniques, improvements to existing instrumentation, and exciting new applications added with each year that passes. This annual review provides an overview of applications of AIMS techniques over the past year (2020), with a particular focus on the application of AIMS in a number of key fields of research including biomedical sciences, forensics and security, food sciences, the environment, and chemical synthesis. Novel ambient ionization techniques are introduced, including picolitre pressure-probe electrospray ionization and fiber spray ionization, in addition to modifications and improvements to existing techniques such as hand-held devices for ease of use, and USB-powered ion sources for on-site analysis. In all, the information provided in this review supports the view that AIMS has become a leading approach in MS-based analyses and that improvements to existing methods, alongside the development of novel approaches, will continue across the foreseeable future.