Mechanosynthesis of TaC-WC powders under environmental conditions and their consolidation via electric arc furnace
Bibliographic record
Abstract
Abstract In this study, tantalum carbide (TaC) was synthesized using an innovative approach that synergistically integrates mechanosynthesis and electric arc furnace processes. By employing high-energy ball-milling (HEBM) for 50 min under environmental conditions, TaC-WC powders were successfully synthesized, using a powder mixture of tantalum and carbon in a 1:1 stoichiometric ratio. This method yielded a composition of 72.5 wt% TaC and 27.5 wt% WC, with an average particle size of 0.7 ± 0.3 μm. The use of an electric arc furnace led to the fabrication of a highly dense material with a relative density above 98%. Notably, WC derived from the mechanical milling material served as an effective sintering aid. x-ray photoelectron Spectroscopy (XPS) results indicated the formation of metal oxides on the surface of the sample, and despite the presence of these oxides, the density of the material remained uncompromised. Furthermore, x-ray diffraction (XRD) analysis after the electric arc furnace treatment demonstrated the preservation of the TaC and WC phases. Mechanical properties, including Vickers hardness, Young’s modulus and fracture toughness were 22.8 ± 0.5 GPa under an applied load of 9.8 N, 539 GPa and 6.6 MPa m1/2, respectively. The results underscore a novel and efficient synthesis route for TaC-WC with enhanced mechanical properties and high density, which are crucial aspects for applications in ultra-high temperature ceramics.
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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".