Effect of Alloying and Microalloying Elements on Carbides of High-Speed Steel: An Overview
Bibliographic record
Abstract
In high-speed steel, carbides are essential phase constituents, which have a direct impact on engineering performance and qualities of high-speed steel. The formation, morphology, and distribution of carbides are dictated by alloying elements. In this paper, various types of carbides in high-speed steel are presented. The effects of different alloying elements such as C, W, Mo, Cr, and V on the formation of carbides in high-speed steel are discussed. Research progresses on carbide improvement by microalloying elements such as N, B, Mg, and rare earth (RE) elements are reviewed. It is reported that Cr promotes the precipitation of M2C, N enhances the formation of fibrous M2C, Mg effectively shatters the large-size carbide grid, Nb refines granular carbide MC, and rare earth elements encourage the formation of M6C, resulting in irregular M2C lamellae. The incorporation of microalloying elements improves the distribution and size of carbides and also refines the solidification structure of high-speed steel.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".