Evaluation of Kinetics of Leaching of Lignins and Tannins in Batch Adsorption of Cr (VI) by Emblica officinalis Leaf Powder (EOLP)
Bibliographic record
Abstract
The present paper is aimed to assess the contents of lignin and tannin leached in the batch adsorption test filtrate and to evaluate the kinetics of leaching of lignin and tannins. For the purpose, raw Emblica officinalis leaf powder (EOLP) has been used as adsorbent for removal of Cr (VI) from aqueous solution in batch mode of operation. Test results indicate that EOLP imparts lignin and tannin in batch test filtrate. Both lignin and tannin contents are related to pH, chemical oxygen demand (COD), initial Cr(VI) concentration (C0) residual Cr(VI) concentration in batch test filtrate (C),amount of adsorbent (Wad) and the time of contact (t). Dimensionless parameters are developed and the lignin and tannin contents are well correlated with dimensionless parameters. From the studies conducted on rate of leaching of both soluble lignin and tannins, the kinetics of leaching of soluble lignin and tannin follow a pseudo second order type rate kinetics. Linear regression models are developed based on pseudo second order kinetics for determination of lignin and tannin contents in batch test filtrate. However, these findings need further verification in future investigations.
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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".