Separation of Bovine Serum Albumin and Humic Acid Using Antifouling Ultrafiltration Membranes Based on the Blends of Poly(Amide Imide) and Zirconium Containing <scp>MOF</scp> ‐808
Bibliographic record
Abstract
ABSTRACT Hybrid poly(amide imide) (PAI) ultrafiltration (UF) membranes were successfully fabricated using MOF‐808 for the separation of bovine serum albumin (BSA) and humic acid (HA). The zirconium‐based MOF‐808 was synthesized by a straightforward solvothermal process, and its chemical functionality was confirmed by FTIR and XRD. The crystalline and granular structure of MOF‐808 was clearly visible in scanning electron microscope (SEM) images. The surface functionalities of the membranes were analyzed using FTIR and XRD. The PAI membrane containing 4 wt.% of MOF‐808 exhibited a contact angle (CA) of 57.8°, water uptake of 75.1%, pure water flux (PWF) of 139.2 Lm −2 h −1 , and porosity of 27.4%, indicating increased surface hydrophilicity of the hybrid membranes. The antifouling behavior was evaluated using BSA and HA foulants. The flux recovery ratio (FRR) of the hybrid membranes increased to above 90% during the rejection of BSA and HA, demonstrating their antifouling properties and excellent separation ability. Overall results clearly show that the PAI/MOF‐808 hybrid UF membranes are promising for water and 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) | 0.001 | 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 | 0.001 | 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".