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Record W4319836407 · doi:10.1080/00268976.2023.2168468

Structural evolution of dicarbon-silver cluster anions: from flat to 3-dimensional and from attached to core–shell

2023· article· en· W4319836407 on OpenAlexafffund
Fedor Y. Naumkin

Bibliographic record

VenueMolecular Physics · 2023
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsOntario Tech University
FundersUniversity of Ontario Institute of Technology
KeywordsMetastabilityCluster (spacecraft)Carbon fibersPlanarDiatomic moleculeShell (structure)Spectral lineChemical physicsCore (optical fiber)ChemistryMetalCarbon chainElectronComponent (thermodynamics)Molecular physicsAtomic physicsNanotechnologyMaterials scienceMoleculePhysicsComposite numberComposite materialOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

Coinage-metal based nanocomposites and interfaces attract much attention due to a variety of technological applications in the areas of materials, catalysis, molecular electronics, etc. In particular, carbon-silver systems exhibit significant prospects for multiple practical uses. The reported study at a DFT level concentrates on such cluster anions with a diatomic carbon component and presents a variety of isomers evolving with size from planar to nonplanar geometries. Structures, stabilities, charge distributions, vertical electron-detachment energies and simulated IR spectra for C2Agn– (n = 4–17) are discussed, with dicarbon attached outside or inserted inside the silver entity. In particular, the spectra show two main bands associated with the relative motions of the carbon and silver parts as a whole and stretching vibration in C2. Their relative intensities are correlated with the structural features of the systems. A sequential mechanism is proposed for formation of the metastable core–shell C2Ag17– species (found to release the carbon core upon electron detachment). The results are believed to be accessible for experimental verification.

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 score0.058
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 head0.017
GPT teacher head0.257
Teacher spread0.239 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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