Fabricating Highly Efficient Ternary Mn–CeO <sub> <i>x</i> </sub> /Co <sub>3</sub> O <sub>4</sub> Catalysts for Low Temperature Thermal Desorption of Persistent Perfluorooctanoic Acid in Soil
Bibliographic record
Abstract
ABSTRACT Developing efficient catalytic thermal desorption systems is of great significance in the field of sustainable soil remediation. Herein, novel Mn–Ce solid solution modified Co 3 O 4 nanocrystals were successfully prepared for the removal of perfluorooctanoic acid (PFOA) in soil. The ternary Mn–CeO x /Co 3 O 4 catalyst exhibited the maximum of 99.2% for PFOA degradation at 200°C, while the N 2 flow rate was 0.5 L min −1 and the catalyst content added up to 0.5% of the soil mass. The superior performance of the optimized catalyst can be ascribed to the mutual conversion of oxidation valence states of Mn, Ce, and Co elements, respectively, which dramatically improved its oxygen mobility and the strength of surface acid sites. Furthermore, the probable reaction pathways were proposed according to the main intermediates identified by Fourier transform infrared (FT‐IR) and gas chromatography‐mass spectrometry (GC–MS). This study provides a cost‐effective strategy for practical catalytic thermal desorption towards the remediation of toxic persistent organics in soil.
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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) | 0.000 | 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".