A Statistical Analysis of Epoxy Polymer Reinforced with Micro Ceramic Particles
Bibliographic record
Abstract
A significant amount of research has been focused on the use of ceramic nano/micro particles to enhance the strength and stiffness of polymeric matrices. This work evaluates the effect of Portland cement or crystalline silica (quartz) particle inclusions into epoxy polymer. Two experiments were conducted based on a full factorial design analysis. Experiment I investigated the effect of Portland cement amount (ASTM III), two types of hardeners (HY 951 and 956) and two curing times (7 and 28 days) on the compressive behaviour and density of particulate composites. Experiment II evaluated the incorporation of quartz or cement particles by mixing different mass fraction levels, considering 28 days of curing time and HY 951 hardener. The samples were prepared in a randomized manufacturing process and tested in compression. The mechanical properties were significantly affected by the type of hardener used. Both particles can enhance the compressive strength and stiffness of the composites.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".