Influence of Alkaline Solution Aging on Mechanical Properties of Natural Particle Reinforced Polymer Blend
Bibliographic record
Abstract
This paper aims at studying the degradation mechanism of the epoxy/unsaturated polyester (EP/UP) hybrid composites in alkaline aging.The secondary parameters are natural waste fillers that are employed to measure the resistance to alkaline attack.The weight percentages of date seed, olive seed and pistachio shell powder were added to the polymer blend in 0, 6, 8, 10 and 12 percentages to observe the influence of the additives on the initial mechanical performance and durability under alkaline conditions.Impact strength, hardness, compressive strength and flexural strength of the composites were also tested with an accelerated aging period in a solution of 10 weight percent of NaOH under different periods.Before aging, the filler addition to all mechanical properties; impact, compressive, and flexural strengths were at the highest point of 8 weight percent filler content whereas hardness rose to 12 weight percent.The degradation of all composites was gradual after being subjected to alkaline conditions, which was regulated by filler-matrix interfacial debonding, matrix softness and diffusion of solution into the polymer.Although flexural strength and hardness degraded at a slower rate, impact strength was the most sensitive to alkaline attack, with compressive strength being the next.The systems of interest exhibited greatest resistance to degradation by alkalis through pistachio shell-reinforced composites.The findings indicate the possibility of waste-based fillers in the preparation of cost-effective and durable polymer fillers in alkaline environments and verify that alkaline aging is the key factor that affects the longterm behavior.
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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".