Pressure-Driven Functional Polymeric Membrane Technology as Athermal Separation Unit Operation in Chemical Engineering : A Review
Bibliographic record
Abstract
This manuscript provides an overview of published scientific and trade literatures and a collection of useful reference information on all aspects of membrane science and technology, selected result of experiment applications, and more recent developments in pressure-driven flat sheet membrane (PDFSM) processes as new frontier and athermal separation unit operation in chemical engineering covering general description of the basic principles of membrane separation processes, benefits and drawbacks, and future trends of membrane developments. Meanwhile, experiment results of selected applications of membranes are removing and/or reducing bacteria, and recovering high protein and low fat from skim milk by microfiltration (MF) membrane (Fluoro polymer, 0.45 µm, Alfa Laval) as an alternative to replace heat sterilization, separating and/or concentrating protease enzyme by ultrafiltration (UF) membrane (Polysulphone, 20000 MWCO, DSS), separating target and valuable components in corn steeping water by using nanofiltration (NF) membrane (Thin Film Composite on Polyester, DSS), and separating and/or purifiing ions component in brackish water and sea water by reverse osmosis (RO) membrane (Thin film composite on Polypropylene, DSS).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".