Ion-retention properties of graphene oxide/zinc oxide nanocomposite membranes at various pH and temperature conditions
Bibliographic record
Abstract
Laminar graphene oxide (GO) is a promising candidate material for next-generation highly water-permeable membranes. Despite extensive research, there is little information known concerning GO's ion-sieving properties at high acidic/basic pH and temperatures. In this study, the ion-blockage properties of the pristine GO and GO/zinc oxide (ZnO) nanocomposite membranes were tested using a non-pressure-driven filtration setup over a wide range of pH and temperatures. The ZnO nanoparticles within the composite membranes were synthesized via the room-temperature oxidation of zinc acetate and zinc acrylate precursors and were uniformly distributed across the composite membrane. It is observed that partially replacing the zinc acetate precursor with zinc acrylate improves the blockage performance of the composite membranes under extreme basic conditions by 42%. Moreover, photocatalytically-reduced composite membranes blocked copper sulfate ions 28% more than as-prepared composite membranes. Further, it was discovered that the composition of the membrane plays a vital role in its ion blockage performance at higher temperatures.
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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".