Surface Properties of Biofouled Membranes from a Submerged Anaerobic Membrane Bioreactor after Cleaning
Bibliographic record
Abstract
The surface structural properties of biofouled membranes from a laboratory-scale submerged anaerobic membrane bioreactor (SAnMBR) treating kraft pulping evaporator condensate after cleaning were studied. A flat sheet polyvinylidene fluoride (PVDF) membrane was used for the study. Three different cleaning methods, physical cleaning (PC), maintenance chemical cleaning (MCC), and recovery cleaning (RC) were applied to the fouled membrane surface, and the treated membranes were subject to flux recovery and surface structural analysis by using spectroscopic methods, zeta potential measurement, attenuated total reflectance-Fourier transform infra red spectroscopy (ATR-FTIR), and advanced correlative microscopic methods, including confocal laser scanning microscopy (CLSM), atomic force microscopy (AFM), and scanning electron microscopy (SEM). Neither PC, MCC, nor RC methods restored the membrane permeability to initial conditions. Adhesion of a thin extracellular polymeric substance (EPS) layer, consisting of proteins and polysaccharides with a thicknesses of 4.0 µm, 5.3 µm, and 7.1 µm and roughness of 190 nm, 236 nm, and 273 nm was observed on RC, MCC, and PC treated membrane surfaces, respectively. Partial flux recovery was achieved with the MCC and RC methods. This was correlated to the reduction of the protein associated with the foulant. Polysaccharides were found to be the most stable and predominant EPS constituent in relation to protein on the biofouled layer of RC and MCC membrane surfaces.
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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 | 0.001 | 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".