Novel Forward Osmosis Membranes Engineered with Polydopamine/Graphene Oxide Interlayers: Synergistic Impact of Monomer Reactivity and Hydrophilic Interlayers
Bibliographic record
Abstract
In this study, a series of polyamide membranes with improved water permeability and thermal stability for forward osmosis applications were synthesized with the main objective of tuning the chemical structure of the polyamide layer to enhance its resistance at higher temperatures. Constructing an interlayer over the substrate of thin-film composite membranes is a promising approach to have better control over the synthesis of a thin and smooth selective layer. Polyamide thin-film composite membranes equipped with polydopamine/graphene oxide interlayers were fabricated. To enhance the thermal stability of thin-film composite membranes, the selective layer chemical composition was modified by an amine monomer: triaminopyrimidine (TAP). The presence of an interlayer made the polyamide layer smoother and thinner. The FTIR spectra showed characteristic peaks for PDA/GO and polyamide, showing the successful formation of the interlayer and selective layer. XPS results demonstrated that the TAP monomers increased cross-linking of the polyamide by forming more amide linkages during the polymerization process. TAP monomers contributed to fewer structural variations of the polyamide layer at high temperatures, leading to a smaller increase in water flux and reverse salt flux of TAP-modified membranes by increasing the temperature. A membrane made with 2 wt % TAP showed 3.2 L/m 2 h and 3.5 g/m 2 h increases in water flux and reverse salt flux, respectively, with 1 M NaCl solution as the draw solution by increasing the temperature from 25 to 65 °C. However, thin-film composite membranes with no TAP showed 8.3 L/m 2 h and 6.1 g/m 2 h increases in water flux and reverse salt flux, respectively. Our results could be leveraged to develop novel forward osmosis membranes that can potentially dewater hot wastewater streams.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".