Research of Properties and Structure of Boron-modified Roll-foundry Iron
Bibliographic record
Abstract
The aim of the research is to determine the properties and the structure of boron-alloyed iron used for rolls production. It was found that boron can form different carbides in iron, which significantly improve both hardenability and microhardness. Iron borides Fe3(B,C) are also formed in cast iron as only 40% of carbon atoms in cementite matrix can be replaced by boron. Besides, boron influences the temperatures of structural constituents decomposition (increases the rate of cementite decomposition), it also decreases the temperatures of developing phase transformations. The research group determined the kinetics of martensite decomposition, which is formed when chilled cast iron is poured into a metal mold and then undergoes thermal treatment to the temperature of 400 °C. In the temperature range of 210 – 400 °C the main process is decomposition of the retained austenite into bainite, while in the temperature range of 400 – 500 °C, the main process is decomposition of martensite and forming a ferrite-cementite mixture. In order to get the necessary properties of the roll face, it is necessary to provide its thermal treatment (tempering), when it is heated to the temperature of 400 °C to avoid martensite decomposition, because otherwise in the process of roll operation it can result in crack formation.
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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".