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Record W4237352543 · doi:10.2320/jinstmet.j2018062

Effect of C and Al Elements on High Resistivity and High Rigidity of Ultra-High Strength TiC<sub>(1−</sub><i><sub>X</sub></i><sub>)</sub>/Ti-Metal Matrix Composites Fabricated by Blended Elemental Reactive Sintering

2019· article· en· W4237352543 on OpenAlexaff
Tadahiko Furuta, Katsuomi Shiina, Yoshihisa Ueda, Shinobu Shimazaki, Kiyoji Nakamura

Bibliographic record

VenueJournal of the Japan Institute of Metals and Materials · 2019
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsASTER
Fundersnot available
KeywordsMaterials scienceElectrical resistivity and conductivityUltimate tensile strengthSinteringComposite materialTitaniumBrittlenessElongationMetallurgy

Abstract

fetched live from OpenAlex

The effects of the C and Al content on the resistivity and rigidity of newly developed ultra-high strength titanium-based metal matrix composites (Ti-MMCs) fabricated using a technique that we refer to as blended elemental reactive sintering (BERS), were investigated. The composition of the MMCs was TiC(1−X)/Ti-6Al-4V and Ti-8.6Al-5.7V, which were compared with those for TiB/, SiC/and AlN/Ti-MMCs. The blended TiC reacted with Ti powder and transformed to TiC(0.50~0.62) during sintering. The resulting TiC(0.50~0.62)/Ti-8.6Al-5.7V exhibited a specific resistance of 2.3 μΩm, a Young's modulus of 135 GPa, and a tensile strength of 1.25 GPa, with a substantial elongation of approximately 2.5%. On the other hand, TiB/Ti-6Al-4V had excellent mechanical properties, but an extremely low electrical resistance because the conducting TiB particles have a resistivity of only 0.07 μΩm. Blended SiC and AlN also reacted with Ti powder during sintering and formed a brittle phase at the interface between the particles and the Ti matrix. As a result, Ti-6Al-4V MMCs that are suitable for use as structural materials could not be fabricated using BERS with SiC or AlN.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.016
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Japan Institute of Metals and MaterialsSame topicAluminum Alloys Composites PropertiesFrench-language works237,207