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Record W2064544527 · doi:10.2109/jcersj.111.372

Simultaneous Synthesis of Titanium Carbide-Alumina from Woody Materials by Self-Propagating High Temperature Synthesis

2003· article· en· W2064544527 on OpenAlexaff
Tatsuya Ashitani, Ryuichi Tomoshige, Tomoko Ueno, Kokki Sakai

Bibliographic record

VenueJournal of the Ceramic Society of Japan · 2003
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsImpact
Fundersnot available
KeywordsMaterials scienceCelluloseTitaniumLigninCarbideCarbon fibersOxygenTitanium carbideChemical engineeringAluminiumYield (engineering)Nuclear chemistryMetallurgyComposite materialOrganic chemistryChemistryComposite number

Abstract

fetched live from OpenAlex

In order to prepare simultaneously TiC-Al2O3, and to suppress formation of carbon defects in TiC prepared from self-propagating high temperature synthesis (SHS) of woody materials with Ti, the reaction of each woody material with Ti and Al was investigated and compared with their reaction with Ti only. The reaction of Japanese cedar (Cryptomeria joponica D. Don) bark, cellulose or lignin as the woody materials, with Ti alone or Al-containing Ti powder was examined under the conditions favorable for the SHS reaction. It was found that TiC-Al2O3 could be successfully prepared from the woody materials by means of the SHS reaction. The effectiveness of Al in reducing the amount of carbon defects in the TiC was confirmed by performing the SHS reaction with and without Al. The carbon and oxygen in the woody materials reacted with Ti and Al to yield TiC and α-Al2O3, respectively. The amount of carbon defects in cellulose-derived TiC decreased with increasing aluminum, whereas lignin-derived TiC hardly changed in that regard. Because added aluminum reacts preferentially with oxygen in the woody material, it is guessed that oxygen which it takes to remove carbon atom from the TiC lattice is used up.

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 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 score0.004
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.004
GPT teacher head0.175
Teacher spread0.172 · 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.

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

Citations2
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Ceramic Society of JapanSame topicIntermetallics and Advanced Alloy PropertiesFrench-language works237,207