Influence of Curing Agents Molecular Structures on Interfacial Characteristics of Graphene/Epoxy Nanocomposites: A Molecular Dynamics Framework
Bibliographic record
Abstract
Abstract This paper presents a comprehensive molecular dynamics study on the effects of the stoichiometric ratio of epoxy:hardener, hardener's linear and cyclic structure, and number of aromatic rings on the interfacial characteristics of graphene/epoxy nanocomposite. The van der Waals gap and polymer peak density as a function of the type of the hardener is calculated by analyzing the local mass density profile. Additionally, steered molecular dynamics are used to conduct normal pull‐out of graphene to study the effect of the mentioned features of hardeners on the interfacial mechanical properties of nanocomposites, including traction force, separation distance, and distribution quality of reacted epoxide rings in the epoxy. Influence of the hardeners on the damage mechanism and its initiation point are also studied by analyzing the evolution of local mass density profile during the normal pull‐out simulation. It is seen that stoichiometric ratio and geometrical structure of the hardeners affect the interfacial strength. It is also revealed that the hardener type can change the epoxy damage initiation point. The damage occurs in the interphase region for a higher stoichiometric ratio or cyclic structure of hardener. In comparison, for hardener's lower stoichiometric ratio and non‐cyclic structure, failure begins in the epoxy near graphene layers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".