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Record W3168843313 · doi:10.1139/tcsme-2020-0148

Optimization of deposition parameters for MPCVD diamond coatings grown on WC-Co substrates using the Taguchi and analytical hierarchy process methods

2021· article· en· W3168843313 on OpenAlexvenueno aff
Xiaogang Jian, Jibo Hu, Jinyao Tang, Qianli Ma

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2021
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsnot available
Fundersnot available
KeywordsTaguchi methodsTungsten carbideMaterials scienceDiamondSubstrate (aquarium)TungstenDeposition (geology)Analytical Chemistry (journal)Mechanical engineeringComposite materialMetallurgyEngineeringChemistryChromatography

Abstract

fetched live from OpenAlex

In this study, substrate temperature (t), total pressure (p), methane flow (M), and carbon dioxide flow (C) were examined for depositing diamond coatings on cemented tungsten carbide substrates (WC-Co; 6 wt.%) under an atmosphere of CH4–H2–CO2. The Taguchi method and analytical hierarchy process method were used to plan the parameters and the sequencing of the parameters, respectively. The results show that three schemes with improved parameters could be identified using the Taguchi method, and the best sequence for these parameters (t = 750 °C; p = 6 kPa; M = 7 mL/min; C = 4 mL/min) was obtained using the analytical hierarchy process method; these results were verified experimentally.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.306
Teacher spread0.278 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicDiamond and Carbon-based Materials ResearchFrench-language works237,207