Pervaporation Dehydration of Ethanol with Malic Acid Crosslinked Graphene/Poly(Vinyl Alcohol) Nanocomposite Membranes
Bibliographic record
Abstract
Graphene (GE) based poly(vinyl alcohol) (PVA) nanocomposite membranes were prepared by solution blending method. The influence of GE on morphological, structural, and thermal properties of GE/PVA membranes was studied. Then, malic acid (MA) was used as a crosslinker of the nanocomposite membranes. The effect of MA content on the degree of crosslinking, thermal, mechanical properties, and pervaporation (PV) performance of nanocomposite membranes was investigated. The characterizations of GE/PVA and MA crosslinked GE/PVA nanocomposite membranes were performed by X-ray diffraction spectrum, transmission electron microscope, Fourier-transform infrared spectroscopy, and differential scanning calorimetry, and tensile testing. The characterization results indicated that the good compatibility between GE and PVA was obtained with 0.5wt% filler content. Thermal stability and mechanical properties of MA crosslinked GE/PVA membranes were enhanced by adding 20wt% MA with respect to PVA. The best PV performance for dehydration of 50wt% ethanol solution was obtained by using the 20wt% MA crosslinked GE/PVA membrane. This membrane showed that the total permeation flux and selectivity are 0.690kg/m2h and 23.89, respectively.
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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".