Catalytic Ozonation of Pharmaceuticals Using CeO2-CeTiOx-Doped Crossflow Ultrafiltration Ceramic Membranes
Bibliographic record
Abstract
The removal of persistent organic micropollutants (OMPs) from secondary effluent in wastewater treatment plants is critical for meeting water reuse standards. Traditional treatment methods often fail to adequately degrade these contaminants. This study explored the efficacy of a hybrid ozonation membrane filtration (HOMF) process using CeO2 and CeTiOx-doped ceramic crossflow ultrafiltration ceramic membranes for the degradation of OMPs. Hollow ceramic membranes (CM) with a 300 kDa molecular weight cut-off (MWCO) were modified to serve as substrates for catalytic nanosized metal oxides in a crossflow and inside-out operational configuration. Three types of depositions were tested: a single layer of CeO2, a single layer of CeTiOx, and a combined layer of CeO2 + CeTiOx. These catalytic nanoparticles were distributed uniformly using a solution-based method supported by vacuum infiltration to ensure high-throughput deposition. The results demonstrated successful infiltration of the metal oxides, although the yield permeability and transmembrane flow varied, following this order: pristine > CeTiOx > CeO2 > CeO2 + CeTiOx. Four OMPs were examined: two easily degraded by ozone (carbamazepine and diclofenac) and two recalcitrant (ibuprofen and pCBA). The highest OMP degradation was observed in demineralized water, particularly with the CeO2 + CeTiOx modification, suggesting O3 decomposition to hydroxyl radicals. The increased resistance in the modified membranes contributed to the adsorption phenomena. The degradation efficiency decreased in secondary effluent due to competition with the organic and inorganic load, highlighting the challenges in complex water matrices.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".