Lignocellulosic: Non-Conventional Low Cost Biosorbent for the Elution of Coomassie Brilliant Blue (R-250)
Bibliographic record
Abstract
The objective of present research work focuses on the utilization of lignocellulosic material like coir pith for the removal of dye. Coir pith is an inexpensive and ecofriendly biosorbent that is utilized for the removal of Coomassie Brilliant Blue (R-250) dye from waste streams by adsorption method. The adsorption experiments were preceded considering the dose of adsorbent, stay time, concentration of dye, pH(pzc) point zero charge activity by pH drift method. Adsorption isotherms for monolayer and multilayered adsorption were applied and the values of constants like Langmuir (KL), Freundlich (Kf), and Dubinin-Radushkevich (Es) were estimated by applying standard graphical method to assess the adsorption capacity of coir pith raw (CPR) and its modified carbonized form (CPC). The most appropriate model for the equilibrium process of CPR-CBB(R-250) and CPC-CBB(R-250) were the Freundlich and D-R isotherm model. A complete thermodynamic evaluation was conducted by estimating the values of enthalpy (?H°), free energy (?G°), and entropy (?S°) of the system. The surface morphology of CPR and CPC was evaluated by Scanning Electron Microscopy (SEM) and Fourier transforms infrared (FTIR) techniques. The results showed that with the rise in temperature of the system the dye adsorption rate was also increased. Thermodynamic analysis revealed that the adsorption process was endothermic and spontaneous in nature. Kinetics of dye removal was also investigated and results revealed that CPR and CPC follows second order rate constant. The maximum removal capacity of CBB(R-250) with CPR was found to be 70% and of CPC is 99%.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".