The Suitability of Seashell, Animal Bone and Sodium Carbonate as Energizers in Case Carburization of Mild Steel
Bibliographic record
Abstract
This work examines the suitability of using seashell (Oyster shell), animal bone and Na2CO3 materials as energizers for case hardening of mild steel. A carburizer consisting of charcoal was used for research with sea shell, animal bone and Na2CO3 as energizers. Samples were carburized in fabricated rectangular stainless steel boxes using different percentages of energizers (10, 20, 30, 40, and 50%) respectively. The samples were covered completely in each of the boxes with the mixture of carburizer and energizer placed in the chamber of the furnace. The process was carried out at carburizing temperature of 9500C, soaked for 4, 6, and 8hours and quenched in oil. Twenty samples were further tempered at 2000C for 1hour to relieve the stress built up during quenching. Hardness test, chemical analysis and impact test were carried out on the samples. The hardness values of the carburized mild steel were measured with a micro hardness tester. The results of the study showed that hardness values of the untempered mild steel samples were slightly improved than the tempered samples at carburizing temperature of 9500C and carburizing time of 4, 6 and 8hours. The Impact results revealed that samples carburized at 9500C in seashell energizer for 8hours have the highest impact values of 184 Joules for the tempered samples which are higher than the untempered samples due to increase in toughness resulting from tempering. The results also showed that seashell and animal bones are potential energizers in case carburization of mild steel.
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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 | 0.001 |
| 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".