A study on the adequacy of some actinides adsorption on a modified guanidine Schiff base from laboratory effluents
Bibliographic record
Abstract
Abstract Besides the distinctive features and medicinal benefits of guanidine Schiff bases, the possibility of their use as a sorbent for radioactive contents of effluents was developed in the current study. A series of adsorption experiments were performed with 2,2‐benzene‐1,4‐dildiguanidine di‐salicylate synthesized sorbent from sulphate feed solutions containing UO 2 2+ and ThSO 4 2+ species each separately. Infrared studies demonstrated that the sorbent links to both actinides via the azomethine nitrogen atom and the hydroxyl groups on the sorbent. Thermal analyses were also performed. Using the greatest adsorption results, UO 2 2+ and ThSO 4 2+ were able to bind to modified guanidine Schiff base (MGSB) sorbent with uptake capacities of 98 and 54 mg/g respectively. The maximal uptake was achieved at pH 5.5 and 3.5 and 90 min contact time for UO 2 2+ and ThSO 4 2+ , respectively. The equilibrium adsorption results for UO 2 2+ and ThSO 4 2+ were in good agreement with Langmuir isotherm and the pseudo‐second‐order reaction model and demonstrated the endothermic nature and kinetic improvement by increasing temperatures. All kinetic and isotherm results demonstrated the chemical adsorption of both UO 2 2+ and ThSO 4 2+ at the MGSB active sites. Positive ∆ H (40.54 and 40.16 kJ/mol for UO 2 2+ and ThSO 4 2+ , respectively) proved the endothermic nature of the adsorption process.
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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".