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Record W2097041861 · doi:10.1139/cjc-2012-0533

Theoretical study of the stability of Be<sub><i>p</i></sub>@Rb<sub><i>q</i></sub> core-shell clusters

2013· article· en· W2097041861 on OpenAlexaffvenue
Yan Sun, René Fournier

Bibliographic record

VenueCanadian Journal of Chemistry · 2013
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsYork University
Fundersnot available
KeywordsChemistryJelliumCluster (spacecraft)Shell (structure)Atomic physicsOpen shellElectronegativityElectronCharge densityBimetallic stripCore electronCharge (physics)Kinetic energyMolecular physicsCoalescence (physics)PhysicsMetalQuantum mechanics

Abstract

fetched live from OpenAlex

Core-shell structures Ap@Bq can be energetically favored in bimetallic clusters when B has a lower surface energy than A, and p and q are chosen such that a single and complete outer shell of q atoms of B can form around the Ap core. If the difference in the electronegativities of A and B is large, one expects significant charge separation between the A core and the B shell. The combination of a closed atomic shell of B atoms and surface charges (core-shell charge separation) should impart stability on this type of Ap@Bq clusters. We report results of density functional theory calculations, including global optimization of cluster geometries, to characterize the prototype system BepRbq. Our calculations show that BepRbq clusters indeed adopt core-shell structures. However, they do not have particularly large surface charges and are unstable against coalescence. Surprisingly, the Rbq outer shell carries a net negative charge. This can be interpreted as the analog, for clusters, of electron spill-out at semi-infinite jellium surfaces, and it probably results from the electrons’ kinetic pressure.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.201
Teacher spread0.183 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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