Adsorption equilibrium, thermodynamics, kinetics, mechanism and process design of zinc(II) ions onto cashew nut shell
Bibliographic record
Abstract
Abstract Cashew nut shell (CNS) is an agricultural waste was investigated as a new adsorbent for the removal of zinc(II) from aqueous environment. Effects of solution pH, CNS dose, contact time, initial zinc(II) concentration and temperature on removal efficiency were tested and optimum conditions were evaluated. The equilibrium data were fitted well with Langmuir isotherm model and pseudo‐second‐order kinetic model. Langmuir monolayer adsorption capacity of CNS was examined as 24.98 mg/g. Changes in standard Gibbs free energy (▵G°), standard enthalpy (▵H°) and standard entropy (▵S°) showed that the sorption of zinc(II) ions onto CNS are spontaneous and exothermic at 303–333 K. Sorption process was found to be controlled by both surface and pore diffusion. A batch adsorber was designed for different CNS dose to effluent volume ratios using Langmuir equation. Effective diffusivity values were found to be 1.927 × 10−11 (10 mg/L), 2.135 × 10−11 (20 mg/L), 2.267 × 10−11 (30 mg/L), 2.305 × 10−11 (40 mg/L) and 2.362 × 10−11 (50 mg/L) m2/s. © 2011 Canadian Society for Chemical Engineering
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".