Efficient synthesis of dodecylbenzene sulfonic acid in microreaction systems

Geng, Yuhao; Huang, Jinpei; Tan, Bin; Xu, Yiming; Li, Ping; Xu, Jianhong

doi:10.1016/j.cep.2020.107858

Cited by 22 publications

(5 citation statements)

References 22 publications

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“…In all samples, we easily identified benzyl sulfonates (DBE = 4), depicted in Figure 3 a, including the cited parent ion (C 18 H 29 SO 3 – ). 19 , 20 An intense SIMS-induced fragment ion (C 8 H 7 SO 3 – , DBE = 5) was also in all filtered spectra and DBE plots ( Figure 3 a–c), which has been confirmed previously using 3D OrbiSIMS and MS/MS. 15 Benzyl sulfonates with masses higher than the cited parent ion were present in both injector tip deposits, termed “high mass benzyl sulfonates” ( Figure 3 a,b), which extended up to much higher masses in injector tip 1 (C 78 ) but were not present in the injector needle deposit ( Figure 3 c).…”

Section: Resultssupporting

confidence: 86%

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets

et al. 2022

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Modern mass spectrometry techniques produce a wealth of spectral data, and although this is an advantage in terms of the richness of the information available, the volume and complexity of data can prevent a thorough interpretation to reach useful conclusions. Application of molecular formula prediction (MFP) to produce annotated lists of ions that have been filtered by their elemental composition and considering structural double bond equivalence are widely used on high resolving power mass spectrometry datasets. However, this has not been applied to secondary ion mass spectrometry data. Here, we apply this data interpretation approach to 3D OrbiSIMS datasets, testing it for a series of increasingly complex samples. In an organic on inorganic sample, we successfully annotated the organic contaminant overlayer separately from the substrate. In a more challenging purely organic human serum sample we filtered out both proteins and lipids based on elemental compositions, 226 different lipids were identified and validated using existing databases, and we assigned amino acid sequences of abundant serum proteins including albumin, fibronectin, and transferrin. Finally, we tested the approach on depth profile data from layered carbonaceous engine deposits and annotated previously unidentified lubricating oil species. Application of an unsupervised machine learning method on filtered ions after performing MFP from this sample uniquely separated depth profiles of species, which were not observed when performing the method on the entire dataset. Overall, the chemical filtering approach using MFP has great potential in enabling full interpretation of complex 3D OrbiSIMS datasets from a plethora of material types.

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Section: Resultssupporting

confidence: 86%

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets

et al. 2022

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“…In all deposits the dodecylbenzenesulfonate ion, C 18 H 29 SO 3 − [C 6 H 4 (SO 3 )(C 12 H 25 )] − , was present and is assumed to be representative of the intact species on the surface because it is cited as the specific molecule added to lubricant oil packages and is known to have a linear saturated hydrocarbon tail. 29,30 This was highest in normalized intensity in the diesel filter and is discussed later. One exception to the generic formula was the C 8 H 7 SO 3 − (0 ppm) ion, containing a short unsaturated chain (Figure 1a).…”

Section: Resultsmentioning

confidence: 83%

“…Several alkylbenzyl sulfonate ions were present in all engine component deposits and were assigned with the generic formula of [C 6 H 4 (SO 3 )(C n H 2 n +1 )] − , with a saturated hydrocarbon chain extending from the benzyl group (Figure a–c). In all deposits the dodecylbenzenesulfonate ion, C 18 H 29 SO 3 – [C 6 H 4 (SO 3 )(C 12 H 25 )] − , was present and is assumed to be representative of the intact species on the surface because it is cited as the specific molecule added to lubricant oil packages and is known to have a linear saturated hydrocarbon tail. , This was highest in normalized intensity in the diesel filter and is discussed later. One exception to the generic formula was the C 8 H 7 SO 3 – (0 ppm) ion, containing a short unsaturated chain (Figure a).…”

Section: Resultsmentioning

confidence: 99%

Spatially Resolved Molecular Compositions of Insoluble Multilayer Deposits Responsible for Increased Pollution from Internal Combustion Engines

Edney

Lamb

Spanu

et al. 2020

ACS Appl. Mater. Interfaces

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Internal combustion engines are used heavily in diverse applications worldwide. Achieving the most efficient operation is key to improving air quality as society moves to a decarbonized energy system. Insoluble deposits that form within internal combustion engine components including fuel injectors and filters negatively impact CO2 and pollutant emissions. Understanding the composition, origins, and formation mechanisms of these complex materials will be key to their mitigation however, previous attempts only afforded nondiagnostic chemical assignments and limited knowledge toward this. Here, we uncover the identity and spatial distribution of molecular species from a gasoline direct injector, diesel injector, and filter deposit in situ using a new hyphenation of secondary ion mass spectrometry and the state-of-the-art Orbitrap mass analyzer (3D OrbiSIMS) and elemental analysis. Through a high mass resolving power and tandem MS we unambiguously uncovered the identity, distribution, and origin of species including alkylbenzyl sulfonates and provide evidence of deposit formation mechanisms including formation of longer chain sulfonates at the gasoline deposit’s surface as well as aromatization to form polycyclic aromatic hydrocarbons up to C66H20, which were prevalent in the lower depth of this deposit. Inorganic salts contributed significantly to the diesel injector deposit throughout its depth, suggesting contamination over multiple fueling cycles. Findings will enable several strategies to mitigate these insoluble materials such as implementing stricter worldwide fuel specifications, modifying additives with adverse reactivity, and synthesizing new fuel additives to solubilize deposits in the engine, thereby leading to less polluting vehicles.

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“…1, A to C). In all deposits the dodecylbenzene sulfonate ion, C18H29SO3 -[C6H4(SO3)(C12H25)] -, was present and is assumed to be representative of the intact species on the surface because it is cited as the specific molecule added to lubricant oil packages (30,31). This was highest in normalized intensity in the diesel filter and is discussed later.…”

Section: Identification Of Key Molecular Speciesmentioning

confidence: 99%

Unambiguous Identification of Key Molecular Species in Deposits Responsible for Increased Pollution from Internal Combustion Engines

Edney

Lamb²,

Spanu³

et al. 2020

Preprint

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<div>Clean and efficient internal combustion engine performance will play a significant role in</div><div>the move to a decarbonized energy system. Currently, fuel deposit formation on engine</div><div>components negatively impacts CO2 and pollutant emissions, where previous attempts at</div><div>deposit characterization afforded non-diagnostic chemical assignments. Here, we uncover</div><div>the identity and 3D spatial distribution of molecular species from gasoline, diesel injector</div><div>and filter deposits with the 3D OrbiSIMS technique. Alkylbenzyl sulfonates, derived from </div><div>lubricant oil contamination in the engine fuel cycle, were common to samples, we</div><div>evidence transformation of the native sulfonate to longer chain species by reaction with</div><div>fuel fragments in the gasoline deposit. Inorganic salts, identified in both diesel deposits,</div><div>were prevalent throughout the injector deposits depth. We identified common polycyclic</div><div>aromatic hydrocarbons up to C66H20, these were prevalent in the gasoline deposits lower</div><div>depths. This work will enable deposit mitigation by unravelling their chemical</div><div>composition, spatial distribution, and origins.</div>

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Efficient synthesis of dodecylbenzene sulfonic acid in microreaction systems

Cited by 22 publications

References 22 publications

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets

Spatially Resolved Molecular Compositions of Insoluble Multilayer Deposits Responsible for Increased Pollution from Internal Combustion Engines

Unambiguous Identification of Key Molecular Species in Deposits Responsible for Increased Pollution from Internal Combustion Engines

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