On the synthesis and sintering behavior of a novel Mg-Ca alloy, Part II: Spark plasma sintering
Bibliographic record
Abstract
With the growing interest in lightweight materials, magnesium and its alloys have received substantial attention for replacing existing alloys. After investigating the mechanical alloying process of Mg-Ca alloys and determining the optimum parameters for milling in part I of this study, the current research aims to examine the second step: the sintering process. This study proposes the powder metallurgy method to process Mg-Ca alloy through the spark plasma sintering technique at 420 °C under an applied pressure of 38 MPa. Samples with different additives (starch or paraffin) were sintered for various dwell times (7 and 10 min) to determine the optimal mechanical and physical properties. To study the microstructure and phase composition of the sintered alloys, X-ray diffractometer (XRD), field scanning electron microscopy (FESEM), and X-ray energy dispersive spectroscopy (EDS) were utilized. Density measurement, compression test, and micro-hardness evaluation were also conducted for the physical and mechanical feathers analysis. The results indicated that samples with a dwell time of 10 min exhibited superior mechanical properties. Additionally, the starch-containing sample outperformed the paraffin-containing sample in both physical and mechanical properties.
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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) | 0.000 | 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".