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Record W2124810691 · doi:10.1063/1.2006089

Hydrogen-bonding interactions in acetic acid monohydrates and dihydrates by density-functional theory calculations

2005· article· en· W2124810691 on OpenAlexafffund
Qiqi Gao, K. T. Leung

Bibliographic record

VenueThe Journal of Chemical Physics · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConformational isomerismHydrogen bondAcetic acidChemistryMoleculeDensity functional theoryCrystallographyComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Equilibrium structures and the respective binding energies of acetic acid monohydrates and dihydrates have been determined by density-functional theory calculations with different basis sets, including 6-31+G(3d,p), 6-311++G(d,p), and 6-311++G(3df,3pd). Given that the C=O and OH groups in acetic acid provide the predominant hydrogen-bonding interactions with water, six stable conformer structures have been found each for the monohydrate and syn-dihydrate. Of the three syn- and three anti-conformers of acetic acid with water, the most stable monohydrate structure is found to be that of the syn-conformer bonding with water in a cyclic double H-bonded geometry. Similarly, the syn-conformer bonding with two water molecules in a cyclic double H-bonded geometry has also been determined to be the most stable among the six plausible structures for the syn-dihydrate. Frequency analysis of the stable conformers has been performed and the vibrational spectra of the most stable monohydrate and dihydrate structures are compared with the experimental gas-phase and matrix data. Furthermore, the calculated binding energies between an acetic acid and a water molecule for both monohydrate and dihydrate are larger than that between two water molecules, which supports our recent experimental observation of coevaporation of acetic acid with water upon annealing acetic acid on ice.

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 score0.244
Threshold uncertainty score0.493

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 head0.011
GPT teacher head0.254
Teacher spread0.243 · 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

Citations38
Published2005
Admission routes2
Has abstractyes

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