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Record W2126760342 · doi:10.1142/s0217984902004408

ARTIFICIAL METAL NANOCLUSTER CRYSTALS

2002· article· en· W2126760342 on OpenAlexaff
Jinfeng Jia, Xiuwei Liu, Shao‐Chun Li, Jiang-Yan Wang, Jin-Zhong LI, Hang Liu, Minghu Pan, Ruifen Dou, Qi‐Kun Xue, Zhiqiang Li, Shengbai Zhang

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.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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

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

Citations4
Published2002
Admission routes1
Has abstractyes

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Same venueModern Physics Letters BSame topicAdvanced Materials Characterization TechniquesFrench-language works237,207