Synthesis, characterization, and adsorption properties of a Ce(III)-imprinted polymer supported by mesoporous SBA-15 matrix by a surface molecular imprinting technique
Bibliographic record
Abstract
A new Ce(III) ion imprinted polymer (Ce(III)-IIP), which can be used for selective removal of Ce(III) from aqueous solutions, was successfully prepared based on the matrix material of ordered mesoporous silica SBA-15 by surface molecular imprinting technology. The prepared polymer was characterized by X-ray diffraction, transmission electron microscopy, Fourier transmission infrared spectrometry, and nitrogen adsorption−desorption isotherm. The results showed that Ce(III)-IIP kept a uniform framework mesoporosity of SBA-15 but a decrease in Brunauer−Emmett−Teller surface area, pore volume, and average pore diameter. Batch adsorption tests were researched on the effects of solution pH value, mass of sorbent, and contact time at different initial Ce(III) concentrations and temperatures. The kinetic data well fitted the pseudo-second-order kinetic model compared with the pseudo-first-order model. The adsorption isotherm fitted Langmuir model and the dimensionless separation factor RL indicated favorable adsorption. In addition, the Gibbs free energy (ΔG0), entropy (ΔS0), and enthalpy (ΔH0) were calculated from the adsorption data. These values suggested that the adsorption of Ce(III) onto Ce(III)-IIP was a spontaneous and endothermic nature of the process. The relative selectivity coefficients for different metal ion were larger than that of the nonimprinted polymer, indicating that Ce(III)-IIP synthesized for Ce(III) had a higher selectivity specialism for this ion.
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) | 0.000 | 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 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".