Fabrication of Porous Fe/TiB2 Composites by Reactive Precursor Method
Bibliographic record
Abstract
Porous Fe/TiB2 composites were fabricated by a reactive precursor method. Fundamentally, iron, titanium and boron powders were blended to synthesize 20 to 70vol%TiB2 particles in Fe/TiB2 composites after the combustion reaction. Additionally, various foaming agent powders (CaCO3, MgCO3, SrCO3, TiH2, ZrH2 and C) were added to the blended powder. The blended powder compact was heated to induce the combustion reaction. The specimen prepared with carbon had large pores and high porosity (the maximum porosity was 60% and the pore size was about 800 µm). The reasons why the porosity increases are twofold; (i) the melting point of iron is decreased by carburizing and (ii) carbon is oxidized during the combustion process and the formation of gaseous CO results in generating the pores.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".