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Record W2065826948 · doi:10.1063/1.2717013

Diamond growth on Fe-Cr-Al alloy by H2-plasma enhanced graphite etching

2007· article· en· W2065826948 on OpenAlexaff
Y. S. Li, Akira Hirose

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNucleationDiamondGraphiteMaterials scienceEtching (microfabrication)AlloySubstrate (aquarium)Plasma etchingHydrogenMetallurgyLayer (electronics)Chemical engineeringPlasmaNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Without intermediate layer and surface pretreatment, adherent diamond films with high initial nucleation density have been deposited on Fe–15Cr–5Al (wt. %) alloy substrate. The deposition was performed using microwave hydrogen plasma enhanced graphite etching in a wide temperature range from 370to740°C. The high nucleation density and growth rate of diamond are primarily attributed to the unique precursors used (hydrogen plasma etched graphite) and the chemical nature of the substrate. The improvement in diamond adhesion to steel alloys is ascribed to the important role played by Al, mitigation of the catalytic function of iron by suppressing the preferential formation of loose graphite intermediate phase on steel surface.

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 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)0.001
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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 teacher head, 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

Citations10
Published2007
Admission routes1
Has abstractyes

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