Boron-induced microstructure evolution and related wear behavior in NbMoTaWBx high-entropy alloys and composites at room and elevated temperatures
Bibliographic record
Abstract
Refractory high entropy alloys (RHEAs) such as NbMoTaW exhibit potential for wear-resistant applications due to their high hardness and thermal stability at elevated temperatures. The addition of boron (B) may lead to a transformation from RHEAs into refractory high entropy composites (RHECs) due to the formation of hard boride phases. This transition is anticipated to significantly increase the hardness and wear resistance over a large temperature range. In this study, we investigate the impact of boride reinforcements on the microstructure and wear performance of the NbMoTaWB x (x = 0–2) at room and elevated temperatures up to 600 °C. The results show the following: (i) The microstructure evolves from a dendritic microstructure to a complex microstructure with eutectic phase, dispersed body-centered cubic (BCC) particles and boride phases, showing the transition from RHEAs to RHECs; (ii) At room temperature, the wear rate decreases with increasing boron content, with abrasive wear as the primary mode and oxidation wear as minor contribution; (iii) At 600 °C, the wear rate increases with increasing boron content, and the dominant wear mode is oxidation-abrasion.
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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) | 0.001 | 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".