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Record W2312302028 · doi:10.1063/1.480719

The interaction of gold clusters with methanol molecules: <i>Ab initio</i> molecular dynamics of Aun+CH3OH and AunCH3OH

2000· article· en· W2312302028 on OpenAlexaff
Roger Rousseau, Dominik Marx

Bibliographic record

VenueThe Journal of Chemical Physics · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsCluster (spacecraft)ChemistryMoleculeAb initioAtom (system on chip)Molecular dynamicsBond lengthAb initio quantum chemistry methodsGold clusterChemical physicsComputational chemistryCrystallographyElectronic structure

Abstract

fetched live from OpenAlex

Structural, dynamical, and electronic properties of adducts obtained by adsorbing one methanol molecule onto charged and neutral gold clusters, Aun+–CH3OH and Aun–CH3OH, are investigated using Car–Parrinello ab initio molecular dynamics as a function of the cluster size n. The absorption process occurs by the formation of a Au⋆–O coordination bond to one particular gold atom Au⋆ without altering the structure of the underlying cluster. This chemical bond is much stronger for the charged metal clusters Aun+ than for the neutral analogs Aun. In the charged case, the C–O stretching vibration of the interacting methanol molecule is found to increase discontinuously as the underlying cluster structure changes from two-dimensional to three-dimensional. The weaker C–O bond in the neutral species however has “insufficient strength” to be sensitive to changes in coordination number and cluster structure. This leads to a constant C–O stretching frequency as the size of the cluster increases, including the regime where the Aun cluster changes from planar to three-dimensional.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.233
Teacher spread0.227 · 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 designSimulation or modeling
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

Citations53
Published2000
Admission routes1
Has abstractyes

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