Open‐cell polyvinylidene fluoride foams as carriers to promote biofilm growth for biological wastewater treatment
Bibliographic record
Abstract
Abstract This article reports the design and fabrication of open‐cell polyvinylidene fluoride (PVDF) foams as carriers that can promote biofilm growth and organic removal efficiency for biological wastewater treatment in attached growth bioreactors. Open‐cell PVDF foams were fabricated by a manufacturing approach that integrated compression molding and particulate leaching. PVDF carriers were structured with two governing factors of leaching agent types (e.g., sodium chloride [NaCl] and sodium acetate [NaOAc]) and contents (e.g., 80 and 90 wt%). Open‐cell PVDF foams possessed high porosity and high protected surface area (i.e., more than ×10 to ×20 of the areas of commercialized carriers), which promoted biofilm growth in these carriers. As a successful advantage, PVDF carriers used in the moving bed biofilm reactors (MBBR) were entirely covered by biofilm in both interior and exterior parts without clogging. This provides strong evidence of the bacterial compatibility of the fabricated open‐cell PVDF foam carriers. Moreover, the specific morphology of the PVDF carriers in this article provided superior biofilm protection from the detachment in MBBR. Experimental results revealed that PVDF open‐cell foams fabricated by 80 wt% of NaCl demonstrated higher mechanical strength with an organic removal efficiency of 77% ± 7% in the corresponding bioreactor containing them.
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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".