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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.030
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

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)0.0010.000

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