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Record W1530183300 · doi:10.1063/1.4923255

Charge-induced dipole vs. relativistically enhanced covalent interactions in Ar-tagged Au-Ag tetramers and pentamers

2015· article· en· W1530183300 on OpenAlexaff
Armin Shayeghi, Rolf Schäfer, D. M. Rayner, Roy L. Johnston, André Fielicke

Bibliographic record

VenueThe Journal of Chemical Physics · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsNational Research Council Canada
FundersOffice of ScienceStichting voor Fundamenteel Onderzoek der MaterieEngineering and Physical Sciences Research CouncilDeutsche ForschungsgemeinschaftUniversity of Birmingham
KeywordsCovalent bondChemistryBinding energyCluster (spacecraft)DipoleDissociation (chemistry)Spectral lineInfrared spectroscopyBond-dissociation energyCrystallographyAtomic physicsPhysical chemistryPhysics

Abstract

fetched live from OpenAlex

Vibrational spectra of Au(n)Ag(m)(+)⋅Ar(k) (n + m = 4, 5; k = 1-4) clusters are determined by far-infrared resonant multiple photon dissociation spectroscopy in the range ν̃=100-250 cm(-1). The experimental spectra are assigned using density functional theory for geometries obtained by the Birmingham cluster genetic algorithm. Putative global minimum candidates of the Ar complexes are generated by adding Ar atoms to the Au(n)Ag(m)(+) low energy isomers and subsequent local optimization. Differential Ar binding energies indicate exceptionally strong Au-Ar bonds in Au-rich clusters, leading to fundamental changes to the IR spectra. The stronger Ar binding is attributed to a relativistically enhanced covalent character of the Au-Ar bond, while in Au-rich species charge-induced dipole interactions overcompensate the relativistic affinity to Au. Moreover, not only the absolute composition but also the topologies are essential in the description of Ar binding to a certain cluster.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.293
Teacher spread0.255 · 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 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

Citations37
Published2015
Admission routes1
Has abstractyes

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