Effect of the Functional Groups of Polymers on Their Adsorption Behavior on Graphene Oxide Nanosheets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Graphene‐based polymer nanocomposites are emerging materials for both fundamental research and industrial applications. The influence of polymer functional groups on their adsorption behavior onto graphene oxide (GO) nanosheets is investigated, with poly(methyl methacrylate) (PMMA), poly(methyl methacrylate‐co‐methacrylic acid) (PMMA‐co‐MAA), and poly(methacrylic acid) (PMAA) having the same backbone but different functional side groups selected as the model polymers. Fourier transform infrared spectroscopy and X‐ray diffraction results confirm the interfacial interaction between the polymer and GO. Thermogravimetric analysis reveals notable enhancements in the amount of the adsorbed polymer up to 30.6 wt.% for PMMA‐co‐MAA/GO and 49.7 wt.% PMAA/GO compared with 18.7 wt.% for PMMA/GO. The water contact angle decreases from 71.3 o for PMMA/GO to 69.1° for PMMA‐co‐MAA/GO and to 61.2° for PMAA/GO. The further washing process reduces the adsorption amount for the polymer/GO hybrid. Overall, the polar functional groups of the polymer directly influence the polymer adsorption behavior onto GO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it