A new microfiltration membrane with three-dimensional reticular architecture for Nano-pollutants removal from wastewater
Bibliographic record
Abstract
This research provides a new insight into designing next-generation filtration materials for Nano-pollutants removal from wastewater, and potentially for gas/solid or liquid/solid separation in corrosive environment. Considering the high corrosion and oxidation resistance, Ti–40Al–10Nb–10Cr porous alloy was prepared by powder metallurgy and used as a mechanical support with a pore size of around 10 μm. Subsequently, metallic Zn nanoparticles was coated on the Ti–40Al–10Nb–10Cr porous framework by means of chemical vapor deposition, obtaining a novel microfiltration membrane with three-dimensional reticular architecture. Furthermore, the influence of Zn coating on surface morphology, pore feature, and filtration capability of Ti–40Al–10Nb–10Cr porous alloy was investigated. It is of note that the as-prepared microfiltration membrane exhibits an excellent Nano-pollutants filtration efficiency of greater than 99.989% from wastewater. Most importantly, such a three-dimensional reticular architecture provides excellent structural stability, allowing the reutilization of the microfiltration membrane for at least 200 filtration cycles of wastewater treatment.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".