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Record W4415618128 · doi:10.1139/cjc-2025-0089

Synthesis, characterization of phenyl (2,4-dinitro-1-naphthyl) thioethers, kinetic and mechanistic study of their hydrazinolysis in methanol

2025· article· en· W4415618128 on OpenAlexvenueno aff
Alaa Z. Omar, Sherine N. Khattab, Mahmoud F. Ibrahim, Samir K. El‐Sadany, Magda F. Fathalla, Ezzat A. Hamed

Bibliographic record

VenueCanadian Journal of Chemistry · 2025
Typearticle
Languageen
FieldChemistry
TopicChemical Reaction Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsReaction rate constantEnthalpyNucleophileMethanolKinetic energyCatalysisNucleophilic substitutionReaction mechanismReaction rate

Abstract

fetched live from OpenAlex

The rate of reactions of aryl-2,4-dinitro-1-naphthyl sulfides with hydrazine in large excess in methanol were followed spectrophotometrically at λ max = 515 nm corresponding to the formation of 1-hydrazino-2,4-dinitronaphthalene anion. The rate of reaction is measured at different temperatures under pseudo first-order condition. The reaction rate is not subject to catalysis by the hydrazine. The second-order rate constant (k N ) at 25 °C depended marginally on the nature of the 4′-substituent. Low enthalpy and negative entropy of activation values suggested a second-order nucleophilic substitution mechanism for the reaction, further supported by a linear plot ( r = 0.927) with the isokinetic temperature of the reaction “β” predicted to be 1382 K. The isokinetic temperature significantly exceeds the experimental range (298–318 K), indicating enthalpy-controlled reaction kinetics. The correlations of σ-Hammett constants with k N values gave good correlation coefficients ( r = 0.9939–0.9571) with ρ values ranged between 0.35 and 0.25 depending on temperatures. The plot of the logarithmic of the rate and the p K a of the nucleophile gave value of β LG value (−0.14, r = 0.97) suggested that the transition state involving in the fast step is consistent with substrates having good leaving groups.

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)0.001
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 score0.002
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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