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Record W2126760342 · doi:10.1142/s0217984902004408

ARTIFICIAL METAL NANOCLUSTER CRYSTALS

2002· article· en· W2126760342 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueModern Physics Letters B · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsSteacie Institute for Molecular Sciences
Fundersnot available
KeywordsNanoclustersMaterials scienceScanning tunneling microscopeCluster (spacecraft)FabricationMetalNanotechnologyChemical physicsCrystal (programming language)Magic number (chemistry)Condensed matter physicsElectronic structurePhysicsMetallurgy

Abstract

fetched live from OpenAlex

Artificial metal nanocluster crystals, (i.e. periodic lattices consisting of identical metal nanoclusters) were fabricated using a novel technique in which surface mediated magic clustering was used to achieve identical cluster size, while the Si(111)-7 × 7 surface was used as a template for ordering the clusters. The universality of this strategy was demonstrated by fabricating more than 10 different nanocluster arrays with different metals and alloys. The atomic structures, formation mechanism and stability of the nanoclusters were studied with in situ scanning tunneling microscopy combined with first-principles total energy calculations. Our study shows that delicate control of growth kinetics is extremely important for cluster crystal fabrication.

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.

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: none
Teacher disagreement score0.664
Threshold uncertainty score0.722

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 head0.019
GPT teacher head0.202
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