In Situ Processing to Achieve High-Performance Epoxy Nanocomposites with Low Graphene Oxide Loading
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
Modifying the polymer matrix by nanoparticles can be a promising approach to improve the performance of fiber-reinforced polymer (FRP) composites. Organic solvents are usually used for dispersing graphene oxide (GO) well in the polymer matrix. In this study, a green, facile, and efficient approach was developed to prepare epoxy/GO nanocomposites. In situ polymerization is used for synthesizing nanocomposites, eliminating the need for organic solvents and surfactants. By loading just 0.6 wt% of GO into the epoxy resin, Young’s modulus, tensile strength, and toughness improved by 38%, 46%, and 143%, respectively. Fractography analysis indicates smooth fracture surfaces of pure resin that changed to highly toughened fracture surfaces in this nanocomposite. Plastic deformation, crack pinning, and deflection contributed to improving the toughness of the nanocomposites. FTIR investigations show that amide bonding was created by the reaction of the carboxylic acid groups in GO with some amine groups in the curing agent during the dispersion processes.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it