Fixed bed column adsorption of ACID Yellow 17 dye onto Tamarind Seed Powder
Bibliographic record
Abstract
Abstract The intention of this study was to explore the efficacy and feasibility for Acid Yellow 17 adsorption onto fixed bed column of Tamarind Seed Powder. The effect of various parameters like flow rate, initial concentration of dye, bed height, and pH were exploited in this study. The Thomas, Yoon–Nelson, Bed Depth Service Time (BDST), and Adams and Bohart model were analysed to evaluate the column adsorption performance. The adsorption capacity, rate constant and correlation coefficient associated to each model for column adsorption was calculated and mentioned. The adsorption capacity increases with increasing initial dye concentration and bed height and decreasing flow rate. The maximum adsorption capacity related to Adams and Bohart model was found to be 978.5 mg/g at initial concentration of 50 ppm at constant flow rate of 15 mL/min, bed height of 15 cm, and pH 7. Le but de cette étude était d'explorer l'efficacité et la faisabilité de l'Acid Yellow 17 adsorption sur colonne à lit fixe de Tamarind Seed Powder. L'effet de différents paramètres comme le débit, la concentration initiale de colorant, la hauteur du lit et le pH ont été exploitées dans cette étude. Le Thomas, Yoon‐Nelson, BDST et Adams et le modèle Bohart ont été analysées pour évaluer les performances d'adsorption colonne. La capacité d'adsorption, constante de vitesse et coefficient de corrélation associé à chaque modèle de la colonne d'adsorption a été calculé et mentionné. Les augmentations de capacité d'adsorption avec une concentration croissante de colorant initial et un lit en hauteur et le débit diminue. La capacité maximale d'adsorption liées au modèle Adams et Bohart a été trouvé à 978,5 mg/g à la concentration initiale de 50 ppm à débit constant de 15 ml/min, la hauteur du lit de 15 cm et un pH de 7.
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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".