Thermal control managing for in-situ synthesis of Ti-C-Fe system by laser cladding on carbon steel
Bibliographic record
Abstract
In-situ laser cladding enables the formation of a uniform clad by melting the powder and substrate to form a composition from pure powder components. Since TiC has desirable properties such as hardness, wear and corrosion resistance, titanium (Ti) and graphite (C) are used as a composite material (i.e., TiC) to increase hardness and wear resistance of AISI 1030 carbon steel. To increase the corrosion, erosion, and wear resistance of a low grade material substrate the entire substrate surface must be coated by the multi-track cladding. Preliminary experiments indicate that deposition of multi-track of TiC-Fe base composite results in different TiC morphologies which might affect the clad properties. In this paper, effect of different heat input on TiC morphology has been studied.Results show that different heat input which are designed by laser parameters affect the TiC morphology. SEM and EDS data show that TiC particles are built up uniformly during the laser cladding process in the iron matrix with dissimilar morphologies.
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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".