(W <sub>1‐x</sub> ,M <sub>x</sub> )C carbides with desired combinations of compatible density and properties – A first‐principles study
Bibliographic record
Abstract
Abstract Tungsten monocarbide (WC) is one of the highly valuable hard materials for industry, widely used as reinforcement in hardfacing overlays, thermal spray coatings, composites, and various alloys. However, its large density leads to the inhomogeneous distribution of WC particles in the metal‐matrix hardfacing overlays. It is highly wished to have appropriate reinforcing phases with an optimal combination of high strength, compatible density, and physical properties. In this study, we tailored WC by partially substituting W with 3d and 4d transition metals through first‐principles calculations. It is demonstrated that WC can be tailored by element‐substitution with desired properties. Identified stable carbides possess lowered density and mechanical properties that are comparable to those of WC. Physical properties, for example, the Debye temperature, Grüneisen parameter, and thermal conductivity, of the tailored carbides are also studied for widened applications. Efforts are made to generate comprehensive information on metal‐substituted with elucidated underlying mechanisms through analyzing the corresponding electronic characteristics.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".