Evidence map›Paper›PMID 39257465›Full record

ArticleEnergy & fuels : an American Chemical Society journal2024

Assessment of Accelerated Aging Effect of Bio-Oil Fractions Utilizing Ultrahigh-Resolution Mass Spectrometry and k-Means Clustering of van Krevelen Compositional Space.

Diana Catalina Palacio Lozano, Daniel W Lester, J S Town, Amy M McKenna, Martin Wills

Abstract read
In one paragraph

Article in Energy & fuels : an American Chemical Society journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Diana Catalina Palacio LozanoDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, U.K.ORCID https://orcid.org/0000-0001-5315-5792
Daniel W LesterPolymer Characterisation Research Technology Platform, University of Warwick, Coventry CV4 7AL, U.K.
J S TownPolymer Characterisation Research Technology Platform, University of Warwick, Coventry CV4 7AL, U.K.
Amy M McKennaNational High Magnetic Field Laboratory, Florida State University, 1800 East Paul Dirac Drive, Tallahassee, Florida 32310-4005, United States.ORCID https://orcid.org/0000-0001-7213-521X
Martin WillsDepartment of Chemistry, University of Warwick, Coventry CV4 7AL, U.K.ORCID https://orcid.org/0000-0002-1646-2379

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bio-oils contain a substantial number of highly oxygenated hydrocarbons, which often exhibit low thermal stability during storage, handling, and refining. The primary objectives of this study are to characterize the hydroxyl group in bio-oil fractions and to investigate the relationship between the type of hydroxyl group and accelerated aging behavior. A bio-oil was fractionated into five solubility-based fractions, classified in two main groups: water-soluble and water-insoluble fractions. These fractions were then subjected to chemoselective reactions to tag molecules containing hydroxyl groups and analyzed by negative-ion electrospray ionization 21 T Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The fractions were also subjected to accelerated aging experiments and characterized by FT-ICR MS and bulk viscosity measurements. Extracting insightful information from ultrahigh-resolution data to aid in predicting upgrading methodologies and instability behaviors of bio-oils is challenging due to the complexity of the data. To address this, an unsupervised learning technique, k-means clustering analysis, was used to semiquantify molecular compositions with a close Euclidean distance within the (

Identifiers

PMID39257465
PMCPMC11382156

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