Studies on Removal of Cr (VI) from Aqueous Solutions Using Powder of Mosambi Fruit Peelings (PMFP) As a Low Cost Sorbent
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The powder of mosambi fruit peelings (PMFP) was used as an adsorbent for the removal of heavy metal like Cr (VI) from aqueous solutions was studied using batch tests. The influence of physico‐chemical key parameters such as the initial metal ion concentration, pH, agitation time, adsorbent dosage, and the particle size of adsorbent has been considered in batch tests. Sorbent ability to adsorb Cr (VI) ions was examined and the mechanism involved in the process investigated. The optimum results were determined at an initial metal ion concentration was 10 mg/lit, pH=2, agitation time – 60 min, an adsorbent dose (150 mg/50 ml) and the particle size (0.6 mm). The % adsorption, Langmuir constants [Q 0 =7.51(mg/g) and b=1.69(mg/lit)] Freundlich constant(K f =2.94), Lagergren rate constants (K ad (min -1 )=5.75 x 10 -2 ) for [Cr(VI)] 10 mg/lit were determined for the adsorption system as a function of sorbate concentration. The equilibrium data obtained were tested using Langmuir, Freundlich adsorption isotherm models, and the kinetic data obtained were fitted to pseudo first order model.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 it