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Surface Modification of Magnesium Base Alloys by Gas/Plasma Nitridation

2000· article· en· W2029794083 on OpenAlexaff
Tatsuhiko Aizawa, Hideyuki Kuwahara, Tachai Luangvaranunt

Bibliographic record

VenueMaterials science forum · 2000
Typearticle
Languageen
FieldChemistry
TopicInorganic Chemistry and Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNitridingMaterials scienceMagnesiumMetallurgySurface modificationEutectic systemTitaniumTinTitanium nitrideNitrideMagnesium alloyAlloyChemical engineeringLayer (electronics)Composite material

Abstract

fetched live from OpenAlex

Gas and plasma nitriding processes were executed in the magnesium with modification by titanium in search for an effective surface treatment method for magnesium alloys, Magnesium - nitrogen system has completely no solid solution or solubility, so that nitride should be only formed by eutectic reaction in the liquid phase, Hence, magnesium is difficult or nearly impossible to have its surface modified by nitriding, Addition of nitride forming element into magnesium enables us to lower the onset temperature of nitriding. Magnesium - titanium alloys with 1 to 5 wt% are yielded by the bulk mechanical alloying, and, subjected to gas nitriding for vanous process conditions. Successful co-formation of Mg 3 N 2 as well as TiN becomes a proof to demonstrate the possibility of gas/plasma nitriding in the solid-state magnesium with aid of nitride former.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations5
Published2000
Admission routes1
Has abstractyes

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