Thermodynamic, kinetic, and equilibrium studies on phenol removal by use of cashew nut shell
Bibliographic record
Abstract
Abstract Adsorption of phenol from aqueous solution onto cashew nut shell (CNS) was investigated to assess the possible use of this adsorbent. The influence of various parameters such as contact time, phenol concentration, adsorbent dose, pH, and temperature has been studied. Studies showed that the pH of aqueous solutions affected phenol removal as a result of decrease in removal efficiency with increasing solution pH. The experimental data were analysed by the Langmuir equation. Equilibrium data fitted well with the Langmuir model with maximum monolayer adsorption capacity of 5.405 mg/g. Thermodynamic parameters such as ΔG°, ΔH°, and ΔS° have also been evaluated and it has been found that the sorption process was feasible, spontaneous, and exothermic in nature. The pseudo‐first‐order and pseudo‐second‐order kinetic models were selected to follow the adsorption process. Kinetic parameters, rate constants, equilibrium sorption capacities and related correlation coefficients, for each kinetic model were calculated and discussed. It was shown that the adsorption of phenol could be described by the pseudo‐second‐order equation, suggesting that the adsorption process is presumable a chemisorption. The CNS investigated in this study showed good application potential for the removal of phenol from aqueous solution.
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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".