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Record W2950515706 · doi:10.1021/jp044970a

Predicted High-Energy Molecules:  Helical All-Nitrogen and Helical Nitrogen-Rich Ring Clusters

2005· article· en· W2950515706 on OpenAlexaff
Lijie Wang, Paul G. Mezey

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2005
Typearticle
Languageen
FieldChemistry
TopicSynthesis and Properties of Aromatic Compounds
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNitrogenRing (chemistry)MoleculeChemistryCrystallographyDissociation (chemistry)Hydrogen bondChemical physicsAtomic physicsPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

Helical all-nitrogen and nitrogen-rich ring clusters, new types of potential high-energy molecules, were investigated in the computational study reported here. Stable helical all-nitrogen clusters N26 and N46 and nitrogen-rich helical structure N26H16 formed by fused six-membered rings were found and characterized as proper energy minima by having real frequencies for all eigenvectors of the Hessian matrix. Furthermore, the stability of [6] N-ring helix was studied by calculating the barrier of dissociation reaction. The potential of these type molecules as high-energy density materials was studied. For a better intuitive understanding of the unusual bonding patterns, the molecular isodensity contour (MIDCO) surfaces for [6] N-ring helix and [6] N-helicene were compared at some characteristic density threshold values of 0.20, 0.32, and 0.35 au. As indicated at these threshold values of the isodensity surfaces, the bonds of all-nitrogen clusters appear stronger than those of nitrogen-rich clusters. Apparently, the nitrogen-rich clusters are of higher energy than the all-nitrogen structures, especially if one takes into account the energy balance of bonds involving hydrogen.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.217
Teacher spread0.207 · 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 designTheoretical or conceptual
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

Citations26
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry ASame topicSynthesis and Properties of Aromatic CompoundsFrench-language works237,207