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In-situ dehydrogenation of lignin-based jet fuel: A novel and sustainable liquid organic hydrogen carrier

2024· article· en· W4405391209 on OpenAlexfundno aff
Andrew Lipton, William Schwartz, Rafał Gieleciak, Dequan Xiao, Bin Yang

Bibliographic record

VenueInternational Journal of Hydrogen Energy · 2024
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsnot available
FundersBiological and Environmental ResearchNatural Resources CanadaU.S. Department of EnergyOffice of Energy Efficiency and Renewable EnergyWashington State UniversityOffice of ScienceGovernment of Canada
KeywordsDehydrogenationJet fuelLigninIn situHydrogenMaterials scienceHydrogen storageHydrogen fuelChemical engineeringChemistryCatalysisOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

A new and sustainable liquid organic hydrogen carrier, Lignin Jet Fuel-based Liquid Organic Hydrogen Carrier (LJF-HyC), has been discovered. This innovative LOHC is created from Lignin Jet Fuel (LJF) through dehydrogenation reactions. The process was carried out in situ using platinum nanoparticles supported on zeolite, resulting in a significant increase in aromatic carbon content. This increase indicates the successful formation of aromatic rings via C–H dissociation. In-situ Nuclear Magnetic Resonance (NMR) and gas chromatographic analyses revealed the formation of unsaturated and partially unsaturated compounds, including alkylbenzenes, tetralins, naphthalenes with double bond equivalence of 4–8, from six apparent reaction pathways, four of which can be major. The original LJF, consisting primarily of mono-, di-, and tricyclohexylalkanes (96 wt%), was converted to dehydrogenated products, constituting approximately 18.5 wt% of the LJF composition. These findings pave the way for developing sustainable hydrogen carriers derived from sustainable aviation fuels.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.250
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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