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Record W2049976780 · doi:10.1021/jo061658j

1,3 Geminal Interactions as the Possible Trend Setting Factors for C−H and C−C Bond Energies in Alkanes. Support from a Density Functional Theory Based Bond Energy Decomposition Study

2006· article· en· W2049976780 on OpenAlexafffund
Mariusz P. Mitoraj, Hungjuan Zhu, Artur Michalak, Tom Ziegler

Bibliographic record

VenueThe Journal of Organic Chemistry · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Calgary
FundersCanada Research Chairs
KeywordsGeminalDensity functional theoryComputational chemistryChemistryDecompositionBondStereochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A bond energy decomposition analysis has been carried out to rationalize the well-established experimental fact that C-C and C-H bond energies decrease with increasing substitution on the carbon. It is shown that this trend is set by steric 1,3 repulsive interactions (geminal repulsion) that increase in the order 1,3 hydrogen-hydrogen < 1,3 hydrogen-carbon < 1,3 carbon-carbon. On the other hand, the radical stabilization energy has little influence on the observed trend for the C-H bond energy in H-CR(1)R(2)R(3) or the C-C bond energy in H(3)C-CR(1)R(2)R(3). Thus, it varies in H-CR(1)R(2)R(3) from -7.2 kcal/mol (H-CH3) to -6.5 kcal/mol (H-C(CH3)3) and in H(3)C-CR(1)R(2)R(3) from -19.0 kcal/mol (H(3)C-CH(3)) to -16.9 kcal/mol (H(3)C-C(CH(3))(3)). It was further found that the average intrinsic C-H bond energy in H-CR(1)R(2)R(3) of 129.2 kcal/mol is smaller than the average intrinsic C-C bond energy in H(3)C-CR(1)R(2)R(3) of 143.4 kcal/mol. However, after the inclusion of steric effects, the overall C-H bond becomes stronger than the C-C bond. The role of steric 1,3 repulsive interactions as the trend setting factor has most recently been suggested by Gronert (J. Org. Chem. 2006, 71, 1209) based on an empirical fit of alkane atomization energies.

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 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 score0.070
Threshold uncertainty score0.410

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)0.0000.000

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 head0.006
GPT teacher head0.241
Teacher spread0.235 · 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 teacher head, 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

Citations43
Published2006
Admission routes2
Has abstractyes

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