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

Neto, Tatiana de Oliveira Zuppa; Avval, Tahereh G.; Morais, Pedro Augusto de Oliveira; Ellis, Wade C.; Chapman, Sean C.; Oliveira, Anselmo E. de; Linford, Matthew R.; Farnsworth, Paul B.; Filho, Nelson Roberto Antoniosi

doi:10.1021/jasms.0c00071

Cited by 12 publications

(7 citation statements)

References 44 publications

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“…Due to the broad range of compounds present in petroleum, extensive sample preparation is typically required when using traditional MS techniques to avoid instrument contamination. DBD‐MS was recently applied to the rapid analysis of automotive lubricant, a type of lubricant made from crude oil 136 . A total of 35 commercially‐available oil samples were acquired, consisting of a combination of synthetic, semi‐synthetic, and mineral oils.…”

Section: Applications Of Ambient Ionization Mass Spectrometrymentioning

confidence: 99%

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

Rankin‐Turner

Heaney

2021

Analytical Science Advances

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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.

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Section: Applications Of Ambient Ionization Mass Spectrometrymentioning

confidence: 99%

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

Rankin‐Turner

Heaney

2021

Analytical Science Advances

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“…DBDI sources are often set up to allow ambient sampling via the direction of the plasma at samples deposited on surfaces. In such a manner, the analysis of various engine oils available on the market has been reported, whereby the authors used a simple experimental set‐up to allow chemometric fingerprinting of samples 12 …”

Section: Introductionmentioning

confidence: 99%

“…In such a manner, the analysis of various engine oils available on the market has been reported, whereby the authors used a simple experimental set‐up to allow chemometric fingerprinting of samples. 12 …”

Section: Introductionmentioning

confidence: 99%

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

Vincent

Hancock²,

Mckendrick

et al. 2022

Rapid Comm Mass Spectrometry

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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.

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“…It has been used in an algorithm for selecting information-rich mass chromatograms from liquid chromatography-mass spectrometry data. , It has helped identify autologous blood doping in athletes from high-speed capillary electrophoresis results . It has also been used in a chemometrics study of automotive lubricant oils analyzed by dielectric barrier discharge ionization time-of-flight mass spectrometry (DBDI-TOFMS) . The reordered spectrum is a convenient way of visualizing and comparing the relationships between PRE values and their corresponding spectra …”

Section: Introductionmentioning

confidence: 99%

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)

Avval

Moeini

Carver

et al. 2021

J. Chem. Inf. Model.

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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 X 4 , 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.

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

Cited by 12 publications

References 44 publications

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

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

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

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)

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