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Record W4402298833 · doi:10.1016/j.mtchem.2024.102264

Polycycloalkanes at the Helm: Exploring high energy density eFuel with norbornyl derivatives

2024· article· en· W4402298833 on OpenAlexaff
Feng Wang, Delano P. Chong

Bibliographic record

VenueMaterials Today Chemistry · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
Keywords2-Norbornyl cationHigh energyMaterials scienceChemistryEngineering physicsPhysicsMedicinal chemistry

Abstract

fetched live from OpenAlex

Sustainable aviation fuel (SAF, eFuel), predominantly composed of polycyclo-hydrocarbons, is a promising alternative to conventional fossil jet fuels . It offers cleaner options for achieving immediate carbon neutrality . This study focuses on norbornyl derivatives containing seven carbon atoms (C 7 H x ), including norbornadiene (NBD), quadricyclane (QC), norbornene (NBN), [2.2.1]propellane (PPL), and norbornane (NBA). These compounds are components of high energy density (HED) fuels or precursor molecules . Understanding their chemical electronic structures reveals how energy is stored in HED compounds. The carbon nuclear magnetic resonance ( 13 C NMR) chemical shifts and C1s core electron binding energy (CEBE) properties were calculated using density functional theory (DFT). The results suggest that saturated C–C single σ-bonds and strained polycycloalkane structures are the primary energy storage mechanisms for these hydrocarbons. This study provides valuable theoretical insights for the development of sustainable HED aviation fuel (eFuel).

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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