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Record W3044387106 · doi:10.3390/mi11080719

Diamond Deposition on Iron and Steel Substrates: A Review

2020· review· en· W3044387106 on OpenAlexafffund
Xiaoju Li, Lianlong He, Yuanshi Li, Q. Yang

Bibliographic record

VenueMicromachines · 2020
Typereview
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversity of Saskatchewan
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDiamondMaterials scienceChemical vapor depositionGraphiteMetallurgyDeposition (geology)CoatingSubstrate (aquarium)Carbon fibersAmorphous carbonCarbon filmNanotechnologyThin filmAmorphous solidComposite materialComposite numberChemistry

Abstract

fetched live from OpenAlex

This article presents an overview of the research in chemical vapor deposition (CVD) diamond films on steel substrates. Since the steels are the most commonly used and cost-effective structural materials in modern industry, CVD coating diamond films on steel substrates are extremely important, combining the unique surface properties of diamond with the superior toughness and strength of the core steel substrates, and will open up many new applications in the industry. However, CVD diamond deposition on steel substrates continues to be a persistent problem. We go through the most relevant results of the last two and a half decades, including recent advances in our group. This review discusses the essential reason of the thick catalytic graphite interlayer formed on steel substrates before diamond deposition. The high carbon diffusion in iron would induce severe internal carburization, and then voluminous graphite precipitated from the substrate. In order to hinder the catalytic graphite formation, various methods have been applied for the adherent diamond film deposition, such as pre-imposed various interlayers or multi-interlayers, special controls of the deposition process, the approaches of substrate alloying and so on. We found that adherent diamond films can be directly deposited on Al alloying steel substrates, and then the role of Al alloying element was examined. That is a thin dense amorphous alumina sublayer in situ formed on the alloying substrate, which played a critical role in preventing the formation of graphite phase and consequently enhancing diamond growth and adhesion. The mechanism of Al alloying suggests that the way used to improve hot corrosion resistance is also applicable. Then, some of the hot corrosion resistance methods, such as aluminizing, siliconizing, and so on, which have been used by some researchers examining CVD diamond films on steel substrates, are reviewed. Another way is to prepare diamond-like carbon (DLC) films on steel substrates at low temperature, and then the precipitated graphite from the internal carburization can be effectively avoided. In addition, based on some new findings, the understanding of the diamond nucleation and metastable growth is discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.001

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 head0.030
GPT teacher head0.326
Teacher spread0.296 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2020
Admission routes2
Has abstractyes

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