Multiwalled <scp>CNTs</scp> for <scp>Cr(VI)</scp> removal from industrial wastewater: An advanced study on adsorption, kinetics, thermodynamics for the comparison between the embedded and non‐embedded carboxyl group
Bibliographic record
Abstract
Abstract The adsorption capabilities of multiwalled carbon nanotubes (MWCNTs) with and without the embedded carboxyl group for the removal of parts per million levels of hexavalent chromium were examined as a function of several parameters, namely contact time, pH of initial solution, initial concentration of Cr(VI), adsorbent dosage as well as temperature of solution. Adsorption isotherms have been utilized to explain the adsorption mechanism. Ion exchange, intra‐particle diffusion, and electrostatic interactions are found to be the fundamental mechanisms describing the adsorption of Cr(VI). The maximum adsorption capacities of Cr(VI) ion by raw MWCNTs and functionalized MWCNTs were found to be 84.75 and 78.13 mg · g−1, respectively, as calculated by the Langmuir adsorption isotherm model. This is with regard to the electron‐rich atoms inside the functional group which repels the negatively charged dichromate ions. Kinetic studies were performed, and the data was found in good agreement with the pseudo‐second‐order.
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.
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".