Characterization of nano-hydroxyapatite synthesized from eggshells for absorption of heavy metals
Bibliographic record
Abstract
This paper presents the synthesis of nano hydroxyapatite using deposition process and eggshell as a cost-effective starting material. This study investigates its potential as an effective adsorbent for heavy metals. Various analytical techniques, including X-ray diffraction (XRD), X-ray fluorescence spectroscopy (XRF), Fourier transform infrared (FTIR), surface area measurement (BET), and scanning electron microscopy (SEM), were used to characterize the composition. The main objective was to evaluate the suitability of the synthesized hydroxyapatite as a heavy metal adsorbent in aqueous solutions. The results of this research showed that hydroxyapatite, which has a particle size in the range of nanometers and a specific area of 150 square meters per gram, and has the necessary properties for absorption, was successfully processed. The results showed that the prepared samples had a uniform mesopore distribution between 2 and 3 nm and 6 and 20 nm.
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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".