Tailoring the failure morphology of 2D bicrystalline graphene oxide
Bibliographic record
Abstract
The aim of this article is to study the effect of oxide functionalisation on the failure morphology of bicrystalline graphene. Molecular dynamics based simulations in conjunction with reactive force field were performed to study the mechanical properties as well as failure morphology of different configurations of bicrystalline graphene oxide. Separate simulations were performed with hydroxyl and epoxide functionalisation, and later on the same simulations were extended to study the graphene oxide as a whole. The authors have predicted that epoxide functionalisation helps in transforming the catastrophic brittle behaviour into ductile. Failure morphologies depict that epoxide groups tend to boost the ductility through altering the fracture path and not affecting the grain boundaries either. Also, the epoxide to ether transformations were found to be the decisive mechanism behind the plastic response shown by epoxide groups. Simulations help in concluding a ductile failure for bicrystalline graphene in conjunction with oxidation of selective atoms in the nanosheet, which further opens new avenues for the application of these graphene sheets in nanodevices and nanocomposites.
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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) | 0.002 | 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".