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The Formation of Carbon Microcoils Having the Coil-Type Overall Geometry

2016· article· en· W2230795965 on OpenAlexvenueno aff
Gi-Hwan Kang, Sung‐Hoon Kim

Bibliographic record

VenueJournal of Coating Science and Technology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsnot available
FundersNational Research Foundation of KoreaNational Research Foundation
KeywordsCarbon fibersMaterials scienceChemistryNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Carbon microcoils could be synthesized using a thermal chemical vapor deposition process in which C2H2/H2 is used as the source gas and SF6 as an additive gas. We investigated the formation of carbon microcoils as a function of reaction time to study the growth mechanism of coil-type carbon microcoils, particularly under long reaction time. After the first 5 min of the reaction, wave-like carbon nanocoils were formed along with carbon microcoils at certain positions on the sample. An increase in reaction time (60 min) led to the formation of double helix-type carbon microcoils. Further increase in the reaction time (120 min) led to the formation of twist-type carbon microcoils with occasional growth of the coil-type carbon microcoils on the sample. However, at the longest reaction time (180 min) investigated in this work, we observed a decrease in the density of the carbon microcoils. Based on these results, we determine the optimal reaction time for the growth of double helix-type carbon microcoils and suggest the growth mechanism of the coil-type carbon microcoils with a focus on long reaction time.

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)0.001
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
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.247
Teacher spread0.238 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Coating Science and Technology→Same topicCarbon Nanotubes in Composites→French-language works237,207→