Adsorption kinetics of cadmium ions onto powdered corn cobs
Bibliographic record
Abstract
Abstract Environmental pollution caused by the presence of toxic materials such as cadmium is becoming global problem and concern. This paper presents a report on kinetics of Cd2+ removal from aqueous solutions through adsorption using powdered corn cobs (PCC). Corn cobs were collected from a selected location, washed to remove sand, air dried, ground and sieved into different particle sizes. The selected properties of PCC were determined using acid digestion method. Adsorption capacities through kinetics of Cd2+ removal from synthetic solutions, typical raw water and domestic‐institutional wastewater were studied. Effects of pH, PCC particle size, initial concentration of Cd2+ and temperature on adsorption capacities were monitored through pseudo first‐ and second‐order models, Elovich and intraparticle diffusion models to present adsorption rate parameters. The study revealed that PCC contained 86.89% volatile solids, had 4.56% acid solubility, 0.52 water solubility and 2.33% ash content. PCC removed Cd2+ from aqueous solutions (synthetic, raw water, and wastewater). The relationship between time and concentration of Cd2+ remaining in the solution followed exponential functions with squared correlation coefficient ranging from 0.9928 to 0.9993, 0.8701 to 0.9284, and 0.8514 to 0.9290 for synthetic solution, raw water, and typical domestic‐institutional wastewater, respectively. Mechanism of cadmium adsorption onto PCC was in two separate stages linear portions in the first parts, while the final parts are curves indicating intraparticle diffusion. It was concluded that PCC is an effective adsorbent for Cd2+ removal. The estimated production cost was 0.068 USD as against 0.50, 2.12, and 3.12 USD for producing adsorbents from empty fruit bunches; pencom shell and sugar cane based activated carbons, respectively.
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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".