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Record W2043437881 · doi:10.1021/jp8055653

Binding Energies of the Silver Ion to Alcohols and Amides: A Theoretical and Experimental Study

2008· article· en· W2043437881 on OpenAlexafffund
В. И. Романов, Chi‐Kit Siu, Udo H. Verkerk, Houssain El Aribi, Alan C. Hopkinson, K. W. Michael Siu

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFormamideChemistryBinding energyDenticityDensity functional theoryMethanolDimethylformamidePhysical chemistryComputational chemistryCrystallographyInorganic chemistryOrganic chemistrySolvent

Abstract

fetched live from OpenAlex

The silver ion binding energies to alcohols (methanol, ethanol, n-propanol, i-propanol, and n-butanol) and to amides (acetamide, N-methylacetamide, N, N-dimethylacetamide, formamide, N-methylformamide, and N, N-dimethylformamide) have been calculated using density functional theory (DFT) and measured using the threshold collision-induced dissociation (TCID) method. For DFT, the combined basis sets of ECP28MWB for silver and 6-311++G(2df,2pd) for the other atoms were found to be optimal using a series of test calculations on Ag (+) binding to methanol and to formamide. In addition, the Ag (+) binding energies of all ligands were evaluated with nine functionals after full geometric optimizations. TCID binding energies were measured using a triple quadrupole mass spectrometer. Reasonable to good agreements were obtained between the calculated and experimental silver(I) binding energies. Ligation of Ag (+) to the alcohols was primarily via the oxygen, although n-propanol and n-butanol exhibited additional, bidentate coordination via the CH hydrogens. By contrast, silver(I) binding to the amides was all monodentate via the carbonyl oxygen. There appears to be strong correlations between the binding energies and the polarizabilities of the ligands.

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 score0.007
Threshold uncertainty score0.275

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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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

Citations34
Published2008
Admission routes2
Has abstractyes

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