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Record W2035443041 · doi:10.2320/matertrans.m2010177

Core-Shell Formation and Juxtaposition in Fe and Si Hybrid Clusters Prepared by Controlling the Collision Stages

2010· article· en· W2035443041 on OpenAlexfundno aff
Naokage Tanaka, K. Sumiyama, Ryoji Katoh, Takehiko Hihara, Kazuhisa Sato, Toyohiko J. Konno, Ko Mibu

Bibliographic record

VenueMATERIALS TRANSACTIONS · 2010
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsnot available
FundersAichi Science and Technology FoundationConnaught FundMinistry of Education, Culture, Sports, Science and Technology
KeywordsMaterials scienceCluster (spacecraft)Transmission electron microscopyAmorphous solidShell (structure)Substrate (aquarium)DiffractionSpectroscopyCrystallographyChemical physicsMolecular physicsNanotechnologyComposite materialOpticsChemistryPhysics

Abstract

fetched live from OpenAlex

Fe and Si hybrid clusters are co-deposited on substrates in a double-glow-discharge-source-type plasma-gas-condensation system, and observed by transmission electron microscopy, scanning transmission electron microscopy, X-ray diffraction and Mössbauer spectroscopy. Core-shell Fe/Si clusters, in which chemically heterogeneous bcc Fe-Si cores are covered by amorphous-like Si shells, are obtained on the substrate when Fe and Si cluster nuclei collide with each other at an early stage (without setting the partition plate between the two sources). On the other hand, Fe and Si clusters are juxtaposed on the substrate when their nuclei collide with each other at a late stage (with setting of the partition plate). These results demonstrate that we can obtain various hybridized states of Fe and Si clusters by controlling the collision stages.

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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Same venueMATERIALS TRANSACTIONSSame topicSilicon Nanostructures and PhotoluminescenceFrench-language works237,207