Removal of Cd(II) and Pb(II) complexes with glycolic acid from aqueous solutions on different ion exchangers
Bibliographic record
Abstract
The sorption of Cd(II) and Pb(II) ions from aqueous solutions on different ion exchangers was investigated by using glycolic acid (GA) as a complexing agent. Glycolic acid is useful for organic synthesis in oxidation–reduction, esterification, and long-chain polymerization. The experiments were carried out by using the following chelating ion exchangers: Purolite S-930, Purolite S-940, Purolite S-950, Diaion CR-20, and Wofatit MC-50 and the cationic ion exchangers: Purolite C-104, Lewatit CNP-80, and Lewatit SP-112. The influence of the initial concentration of Cd(II) and Pb(II) and glycolic acid, pH of the solution, and phase contact time on the sorption percentage was determined in the batch experiments. Pseudo-first-order and pseudo-second-order kinetic models were used to describe the kinetic data, and the rate constants were evaluated. The experimental data, fitted using the Langmuir and Freundlich adsorption models, were applied to describe the equilibrium isotherms and determined the isotherm constants. The Cd(II) and Pb(II) concentrations in the raffinate were determined by the AAS method.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".