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Record W2071333466 · doi:10.1002/pssb.200743537

<i>Ab initio</i> study of indium clusters on the Ge(5 × 5) wetting layer of Si(111)‐7 × 7

2008· article· en· W2071333466 on OpenAlexaff
D. Psiachos, M. J. Stott

Bibliographic record

Venuephysica status solidi (b) · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSurface and Thin Film Phenomena
Canadian institutionsQueen's University
Fundersnot available
KeywordsWettingAb initioWetting layerAdsorptionIndiumAtom (system on chip)Substrate (aquarium)Layer (electronics)ChemistryMaterials scienceCrystallographyChemical physicsComputational chemistryNanotechnologyPhysical chemistryMetallurgyComposite material

Abstract

fetched live from OpenAlex

Abstract An ab initio study of In adsorbed on the Ge(111)‐5 × 5 wetting layer, which forms on top of a Si(111)‐7 × 7 substrate, is reported. A recent experiment showed that small In clusters form on this surface with some regularity but their exact size and structure are still unknown. Results are presented of a detailed investigation of the structural and electronic properties of a single adsorbed In atom and small candidate In clusters, carried out using density‐functional calculations. Using density difference plots and population analysis, the mechanisms of bonding for different In structures are explained. Comparison of total energies shows that for a single In atom the faulted half cell is marginally preferred to the unfaulted half, and little tendency for clustering of In is found for low coverages. Both of these conclusions seem to be at odds with the experimental results and possible explanations are discussed. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.258
Teacher spread0.220 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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