Synthesis and Characterization of Zeolite-Geopolymer Composites for Water Treatment
Bibliographic record
Abstract
This research has studied the synthesis of zeolite-based geopolymer materials with different Si/Al ratios using kaolin and zeolite A with simple, scalable, ambient condition and low-cost method.Along with that, the mechanical strength, density, and pellet formability of the materials were also investigated.Consequently, research introduced zeolite-based geopolymer material with high zeolite content but still kept acceptable strength in water.The metal adsorption capacity was conducted at various initial concentrations and between samples with different Si/Al ratios to provide a suitable kinetic and thermodynamic model for the adsorption process.This study demonstrated that optimized 1.15 Si/Al ratio zeolite-geopolymer composites, which contain 62.4% zeolite, can be a promising adsorbent for removing heavy metal ions from water with 23.15 mg/g for Cu 2+ and 12.38 mg/g for Fe 3+ maximum adsorption capacities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".