Microstructure and First Hydrogenation Properties of Ti30V60Mn(10−x)Crx (x = 0, 3.3, 6.6, 10) + 4 wt.% Zr
Bibliographic record
Abstract
In this paper, we studied the effect of the Cr/Mn ratio on the microstructure, crystal structure and hydrogen absorption properties of the quaternary alloys of compositions Ti30V60Mn(10−x)Crx (x = 0, 3.3, 6.6 and 10) + 4 wt.% Zr. The addition of Hf instead of Zr was also investigated. We found that all alloys are single-phase BCC (Body Centred Cubic) but with regions of high concentration of Zr (or Hf). The first hydrogenation at room temperature under 2 MPa of hydrogen happens quickly without any incubation time. The Ti30V60Mn3.3Cr6.6 + 4 wt.% Zr alloy showed the fastest kinetics and highest hydrogen absorption (3.8 wt.%). For this composition, replacing Zr with Hf made the first hydrogenation slower and reduced the capacity to 3.4 wt.%. No activation was observed for the same alloy without additives. As the alloy without additives did not absorb hydrogen at all, it means that the presence of these high concentrations of Zr (or Hf) is essential for quick first hydrogenation.
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 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) | 0.001 | 0.000 |
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.
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".