Fuel sorption into polymers: Experimental and machine learning studies

Creton, Benoît; Veyrat, Benjamin; Klopffer, Marie-Hélène

doi:10.1016/j.fluid.2022.113403

Cited by 6 publications

(3 citation statements)

References 60 publications

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“…To apply the predictive approaches mentioned above, it is necessary to characterize and simplify the fuels to surrogates. In previous works, ,, fuels were analyzed with gas chromatography techniques such as the two-dimensional gas chromatography (GC×GC) which is able to provide a detailed characterization of a fuel chemical composition, with only few milliliters of the fluid . The 27 fuels were analyzed by means of GC×GC, and compositions were expressed as distributions of mass fractions as a function of the number of carbon atoms for hydrocarbon families such as n -paraffins, i -paraffins, naphthenes, and aromatics.…”

Section: Resultsmentioning

confidence: 99%

“…From comparisons performed in previous studies, − each molecule in the pure compound database was encoded using descriptorslabeled as functional group count descriptors (FGCD)calculated on the basis of the chemical and structural formulas. In the FGCD family of molecular descriptors are included counts of atoms and groups of atoms identified as relevant from chemical aspects.…”

Section: Methodsmentioning

confidence: 99%

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Numerical Approaches to Determine Cetane Number of Hydrocarbons and Oxygenated Compounds, Mixtures, and their Blends

Creton,

Brassart,

Herbaut

et al. 2024

Energy Fuels

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In the present work, we report the development and use of models to predict the cetane number of hydrocarbons and oxygenated compounds, mixtures, and their blends. The study is divided in three steps: (i) the prediction of pure compounds' CN using ML-based approaches, (ii) the development and application of mixing rules, and (iii) the external validation of models on a set of real fuels. Experimental CN values for 658 pure compounds are collected from the literature and merged to obtain a consistent and comprehensive database. ML-based models are then trained on the database. A second database is built from the collection of 572 experimental CN values for mixtures. Existing and proposed mixing rules powered by either experimental CN or CN predicted using the ML-based models are then assessed on the basis of the second database. The new mixing rule involving the activity coefficients of mixtures' components shows the best performance. Finally, the application of our predictive numerical approach to 27 real fuels demonstrates its accuracy and relevance, and that it could be further used for testing large numbers of samples.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Numerical Approaches to Determine Cetane Number of Hydrocarbons and Oxygenated Compounds, Mixtures, and their Blends

Creton,

Brassart,

Herbaut

et al. 2024

Energy Fuels

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“…This market growth will be driven by factors such as increasing demand for fuel injectors and quick connectors in various end-use industries in emerging economies. 2 Examples of recent research on FKM rubber include its resistance to microwave-excited surface-wave plasma (CF 4 /O 2 ) sources, 3 its compatibility with neat compounds and alternative jet fuel-based fluids, 4 and its compatibility with maleic anhydride-grafted silicone rubber. 5 Nanocomposites produced by microwave graphene oxide/FKM reduction have been produced, bearing enhanced dielectric performance and ferroelectric characteristics.…”

Section: Introductionmentioning

confidence: 99%

Solvent‐free synthesized zeolites as compatibility agents in FKM rubber

Petkowicz

Silva

Mignoni

et al. 2023

J of Applied Polymer Sci

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Dry hybrid synthesized zeolite was added to a fluoroelastomer (FKM). Carbon black filler was also evaluated. The resulting systems were evaluated in terms of rheological, physicochemical and morphological characteristics. Replacing carbon black with zeolites decreased the torque maximum (125–144 nM) for all samples. The type of filler has a significant influence on the thermal stability of FKM compounds. The use of x‐ray microtomography (IMX for) on the investigated samples (fluorinated polymers) was shown to be a potential and powerful tool for fractioning the components of the resulting composite material. According to microtomography images, increasing the filler content increases the number of pores, probably due to the greater difficulty in dispersing larger volumes of fillers, which are shown as interconnected conglomerates. The SodC8.5 filler showed a considerable increase in stress at rupture (11 MPa) with only 1 phr, maintaining stability up to 10 phr, while elongation at break increased. The use of Sod and SodC8.5 loads showed an improvement of 15% and 30% in relation to the base compound. Finally, in a thermal stability test at the temperature of liquid N2, the SodC8.5 sample showed the best dimensional stability (approx. 7%), verifying the good compatibility between the filler and the fluorinated polymeric matrix.

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Building Up QSPR for Polymers Endpoints by Using SMILES-Based Optimal Descriptors

Kudyshkin

Toropova

2023

Challenges and Advances in Computational Chemistry and Physics

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Fuel sorption into polymers: Experimental and machine learning studies

Cited by 6 publications

References 60 publications

Numerical Approaches to Determine Cetane Number of Hydrocarbons and Oxygenated Compounds, Mixtures, and their Blends

Numerical Approaches to Determine Cetane Number of Hydrocarbons and Oxygenated Compounds, Mixtures, and their Blends

Solvent‐free synthesized zeolites as compatibility agents in FKM rubber

Building Up QSPR for Polymers Endpoints by Using SMILES-Based Optimal Descriptors

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