MétaCan
Menu
Back to cohort

Recent Development in Clay Based Functional Coating for Corrosion Protection

2013· article· en· W1989283128 on OpenAlexaff
Trilochan Mishra, Ashok Mohanty, Shashi Kant Tiwari

Bibliographic record

VenueKey engineering materials · 2013
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Oxide Properties and Applications
Canadian institutionsCanadian Society of Intestinal Research
Fundersnot available
KeywordsChromate conversion coatingCoatingMontmorilloniteLayered double hydroxidesMaterials scienceCorrosionIon exchangeIntercalation (chemistry)Clay mineralsMetalChlorideChemical engineeringIonNanotechnologyMetallurgyChemistryInorganic chemistryComposite materialMineralogyOrganic chemistry

Abstract

fetched live from OpenAlex

There is a large variety of techniques available to protect metals from various types of corrosion. Till date chromate containing metal coatings is one of the most commonly used methods. Layered clays are basically of two types depending on the type of ion exchange capacity. In the recent years different researchers demonstrated the use of such cation/ anionic clays as potential nanocontainers for the inhibitors. These nanocontainers can be used in the coating to induce self-repairing capacity when the coating surface is damaged. Due to the disturbance in the pH and availability of chloride ions clay based nanocontainers can release the inhibitor to protect the surface. In the recent year use of anionic clay like hydrotalcites or layered double hydroxides are much studied in comparison to cationic clay like montmorillonite. This review critically analysed the potential of these clay in the future development of self-healing coating.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.204
Teacher spread0.177 · 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

Citations24
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueKey engineering materialsSame topicMagnesium Oxide Properties and ApplicationsFrench-language works237,207