Enhancing U(VI) removal from water using nano-Kaolin and nano-Kaolin/MnFe<sub>2</sub>O<sub>4</sub> composite adsorbents
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Bibliographic record
Abstract
Abstract The binding behavior of U(VI) ions onto nano-Kaolin (NK) and nano-Kaolin/MnFe 2 O 4 composite (NK-MF) adsorbents was systematically investigated, focusing on the influence of pH, adsorbent mass, temperature, and contact time. Kinetic analysis, utilizing the pseudo-second-order model, revealed that both NK and NK-MF composites reach their maximum capacity of adsorption (q m ) at pH 3. The maximum adsorption capacities were found to be (8.6) mg g −1 for NK and (14.79) mg g −1 for NK-MF at 25C°, indicating a significant enhancement due to the incorporation of MnFe 2 O 4 . The adsorption isotherms were examined using Langmuir, Freundlich, and Dubinin-Radushkevich models to characterize the adsorption mechanisms. The Langmuir and Freundlich models provided the best fit (R 2 > 0.9), indicating monolayer and multilayer adsorption. Thermodynamics parameters, including enthalpy change (ΔH°), Gibbs free energy change (ΔG°), and entropy change (ΔS°), were derived from adsorption data across different temperatures. The values at 25 °C of ΔH° were (49.67) for NK and (70.97) for NK-MF; ΔG° values were (−5.06) kJ mol −1 for NK and (−7.39) kJ mol −1 for NK-MF; and ΔS° values were 187.36 J (mol·K) −1 for NK and (263.70) J (mol·K) −1 for NK-MF. The results indicate that the adsorption process is endothermic, with conditions that favor adsorption and a positive entropy change. These findings demonstrate the effectiveness and potential of NK and NK-MF composites as viable adsorbents for the uptake of U(VI) ions from water-based solutions. The incorporation of MnFe 2 O 4 into NK improves adsorption capacity, making NK-MF a novel and practical material for uranium removal in environmental applications.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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