Bibliographic record
Abstract
In the past, hardness measurements on nanocrystalline metals were limited to Vickers micro-hardness and nano-indentation tests, mainly due to sample size/thickness limitations. On the other hand, most industries require hardness values on the Rockwell scale and make extensive use of hardness conversion relationships for various hardness scales. However, hardness conversions currently do not exist for nanocrystalline metals. With recent advances in electrodeposition technology, thicker specimens with a wide range of grain sizes can now be produced. In this study, the relationships between Vickers and Rockwell hardness scales have been developed for such materials. In addition, hardness indentations were used to gain further insight into the work hardening of nanocrystalline and polycrystalline nickel. Vickers microhardness and nano-indentation profiles below large Rockwell indentations showed that polycrystalline nickel exhibited considerable strain hardening, as expected. On the other hand, for nanocrystalline nickel the micro-Vickers and nano-indentations hardness profile showed low strain hardening capacity.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".