Pressure‐Driven Solvent Transport and Complex Ion Permeation through Graphene Oxide Membranes
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this paper, an in‐depth investigation of three graphene oxide (GO) based membranes—pure GO, Al 3+ intercalated GO (Al‐GO), and poly(ethylene glycol) (PEG) modified GO (PEG‐GO)—is presented. Both Al‐GO and PEG‐GO membranes have wider interlayer d ‐spacing compared to pure GO, and the d‐ spacing size correlates well to the cross‐membrane water flux with J PEG‐GO > J Al‐GO > J GO . Pressure‐driven transport of water/ethanol mixtures across all three types of GO membranes is dominated by solvent viscosity—not solvent polarity showing distinctively semi‐hydrophilic membrane characteristics. Interestingly, the results suggest that both ethanol cluster size and molecular geometry contribute to preferential ethanol rejection, indicating that both GO and Al‐GO membranes possess superior size sieving capability. Further, the lower permeation of tris(1,10‐phenanthroline)ruthenium(II) (Ru(phen) 3 2+ ) compared to the charge‐equivalent smaller‐sized tris(bipyridine)ruthenium(II) (Ru(bpy) 3 2+ ) demonstrates the excellent steric selectivity of GO membranes. Compared to pure GO, the widened d ‐spacing in PEG‐GO allows ≈100% higher ion permeation while ion flux through Al‐GO is an order of magnitude lower, suggesting the significant role of electrostatic interaction in ion transport. In conclusion, these findings ought to enrich the understanding of the GO‐based membranes and enable future rational designs for a wide range of applications, including water purification and solvent separation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it