Stretchability of PMMA-supported CVD graphene and of its electrical contacts
Bibliographic record
Abstract
Abstract The remarkable mechanical robustness and excellent electrical/thermal properties make graphene a promising candidate for future flexible, stretchable and bio-integrated electronics. In practice, many soft electronics such as the graphene electronic tattoos (GETs) demand the chemical vapor deposited (CVD) graphene to be supported by a deformable substrate. Moreover, various conductive overlayers need to directly laminate on graphene to make electrical contacts. To investigate the mechanical reliability of CVD graphene in these situations, we fabricated CVD monolayer graphene supported by ultrathin poly(methyl methacrylate) (PMMA) substrate and also placed gold/polyethylene terephthalate (Au/PET) and graphene/PMMA (Gr/PMMA) overlayers on graphene. The stretchability of the Gr/PMMA and the overlayer-Gr/PMMA interface was characterized by electrical resistance change during uniaxial tensile tests. Combined with in situ microstructure and Raman investigation, we identified four deformation/fracture stages of Gr/PMMA—pre-cracking elastic deformation, limited micro-cracking in graphene, extensive cracking in graphene, and macro-cracking in PMMA. While micro-cracks emerged in graphene at very small strain (~0.9%), the electrical conductivity of the Gr/PMMA specimen remained up to tensile strains of ~14.5%. In contrast, 100 nm-thick Au film supported by the same PMMA substrate fully ruptured after tensile strains of ~1%. When laminating Au/PET and Gr/PMMA over Gr/PMMA, we found that the Au/PET- Gr/PMMA interface is very vulnerable but the Gr/PMMA- Gr/PMMA interface behaves very similar to intact Gr/PMMA electromechanically. The cyclic behaviour of Gr/PMMA, the effects of PMMA thickness and adhesion are also briefly discussed. The present experimental study provides fundamental insight into the failure of ultrathin polymer-supported graphene and its electrical contacts, which is critical for designing future graphene-based soft electronics.
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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 | 0.000 |
| 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 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".