Highly Conductive and Permeable Nanocomposite Ultrafiltration Membranes Using Laser-Reduced Graphene Oxide
Bibliographic record
Abstract
Electrically conductive membranes are a promising avenue to reduce water treatment costs due to their ability to minimize the detrimental impact of fouling, to degrade contaminants, and to provide other additional benefits during filtration. Here, we demonstrate the facile and low-cost fabrication of electrically conductive membranes using laser-reduced graphene oxide (GO). In this method, GO is filtered onto a poly(ether sulfone) membrane support before being pyrolyzed via laser into a conductive film. Laser-reduced GO composite membranes are shown to be equally as permeable to water as the underlying membrane support and possess sheet resistances as low as 209 Ω/□. Application of the laser-reduced GO membranes is demonstrated through greater than 97% removal of a surrogate water contaminant, 25 μM methyl orange dye, with an 8 V applied potential. Furthermore, we show that laser-reduced GO membranes can be further tuned with the addition of p -phenylenediamine binding molecules to decrease the sheet resistance to 54 Ω/□.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".