Constructing hierarchical porous polyimide/reduced graphene oxide sponge as an oil-water separation material with a balanced performance in thermal stability, elasticity, and oil-adsorption
Bibliographic record
Abstract
To overcome the low thermal stability of conventional polymers and the low elasticity of reduced graphene oxide (rGO) as oil-water separation materials, in this study, hierarchical porous polyimide/reduced graphene oxide (PI/rGO) sponges were prepared with SiO2, polyurethane (PU), polyether amine (PEA), and liquid paraffin (LP) templates, respectively. According to experimental results, all four types of PI/rGO exhibit ideal elasticity, wherein the PI/rGO (SiO2), PI/rGO (PEA), and PI/rGO (LP) further exhibit high thermostability and excellent adsorption capability in oil and organic solvents. This study proposed a new strategy to synthesize an oil-separation material with a balanced performance of thermal stability, elasticity, and oil-adsorption.
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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) | 0.001 | 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".