On the Issue of Alloying and Modification of Alloys: Using the Waste Products for Creation of Novel Materials
Bibliographic record
Abstract
At the large and powerful industrial (private or state) enterprises of the world, particularly, Kazakhstan, RF, and some other post-Soviet (and not only) countries, the products are manufactured using obsolete technologies with high wastes’ generation. At that, the storage and warehousing are unorganized and technically unreasonable (wastes of different chemical compositions and hazard class are mixed) that does not allow their further efficient recycling. Increased processing of many industrial and household wastes is not only economical, but also considerably improves the environmental situation, significantly reduces the consumption of natural raw materials, and reduces the use of scarce lands for waste storage [1]. The authors of this article carried out a literary review on this topic and attempted to use microsilica, as a waste of silicon production, to create new materials with special properties. This refers to the field of experimental study of structures, phases, structural components for understanding the processes of alloying, modification, diffusion, etc. Understanding physical thinking from the metal physics point of view in the study of the nature and kinetics of the phase transformations, alloying, and modification processes enables using the physical research methods to solve research and technological problems in metallurgy and materials science in order to predict and change the required set of properties. The method of research in this article is electron microscopy as the simplest and fastest method of obtaining information about the microstructure, elemental composition, and distribution of components in the bulk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".