Synthesis of Titanium Carbide from Woody Materials by Self-Propagating High Temperature Synthesis.
Bibliographic record
Abstract
Woody waste materials were used for the preparation of titanium carbide ceramics (TiC) by utilizing combustion synthesis or self-propagating high temperature synthesis (SHS). The outer and inner barks and wood of the sugi (Cryptomeria japonica) were used to react with titanium powder as raw materials, as well as commercially available reagents of cellulose and lignin. It was detected by X-ray diffractometry that the TiC phase was obtained directly arose from the mixture of the woody waste materials and titanium powder, without formation of any major oxide phase. Broadening of half width and shift in diffraction peaks of the obtained TiC phase suggest that the TiC phase included lattice deformation and had a non-stoichiometric composition. This latter observation may imply the release of carbon, i.e., formation of carbon mono- or dioxide. The carbide phase had a mean particle size of 1-5μm, and showed a shape similar to a TiC synthesized from a mixture of graphite and titanium powders. The combustion velocity of the mixtures tended to increase with the relative amount of carbon included in the woody materials. On the other hand, the velocity indicated a tendency to decrease with hydrogen and oxygen contents in the materials, which resulted from an endothermic reaction, accompanied with pyrolysis of the woody waste materials during SHS reaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".