Towards a Comprehensive Characterization of the Low-Temperature Autoxidation of Di-n-Butyl Ether.
Nesrine BelhadjMaxence LailliauRoland BenoitPhilippe DagautPublished in: Molecules (Basel, Switzerland) (2021)
In the present study, we investigated the oxidation of 2500 ppm of di-n-butyl ether under fuel-rich conditions (φ = 2) at low temperatures (460-780 K), a residence time of 1 s, and 10 atm. The experiments were carried out in a fused silica jet-stirred reactor. Oxidation products were identified and quantified in gas samples by gas chromatography and Fourier transform infrared spectrometry. Samples were also trapped through bubbling in cool acetonitrile for high-pressure liquid chromatography (HPLC) analyses. 2,4-dinitro-phenylhydrazine was used to derivatize carbonyl products and distinguish them from other isomers. HPLC coupled to high resolution mass spectrometry (Orbitrap Q-Exactive®) allowed for the detection of oxygenated species never observed before, i.e., low-temperature oxidation products (C8H12O4,6, C8H16O3,5,7, and C8H18O2,5) and species that are more specific products of atmospheric oxidation, i.e., C16H34O4, C11H24O3, C11H22O3, and C10H22O3. Flow injection analyses indicated the presence of high molecular weight oxygenated products (m/z > 550). These results highlight the strong similitude in terms of classes of oxidation products of combustion and atmospheric oxidation, and through autoxidation processes. A kinetic modeling of the present experiments indicated some discrepancies with the present data.
Keyphrases
- high resolution mass spectrometry
- liquid chromatography
- gas chromatography
- tandem mass spectrometry
- mass spectrometry
- ultra high performance liquid chromatography
- hydrogen peroxide
- simultaneous determination
- high performance liquid chromatography
- solid phase extraction
- ms ms
- particulate matter
- high resolution
- electron transfer
- nitric oxide
- machine learning
- escherichia coli
- risk assessment
- gas chromatography mass spectrometry
- electronic health record
- artificial intelligence
- deep learning
- label free