Why Doesn’t It Stick? Revealing the Impact of Mobile Oligomers on Ecoflex Surface Functionality and Bonding
Bibliographic record
Abstract
Achieving stable interfacial performance in soft electronics requires a nuanced understanding of how the bulk elastomer composition affects surface functionality. This relationship is well-established in Sylgard 184, a polydimethylsiloxane (PDMS) elastomer that, upon oxidation, forms a cohesive SiO x surface supporting strong adhesion to vapor- and solution-deposited functional films. In contrast, Ecoflex, a widely used ultrasoft silicone elastomer, exhibits a long-recognized but poorly understood incompatibility with metal and solution-processed conductors. Here, we introduce layered PDMS/Ecoflex composites as a new experimental platform for systematically probing this limitation. We show that mobile low-molecular-weight siloxane oligomers in Ecoflex can migrate through a 100 μm thick PDMS membrane cross-linked directly to the Ecoflex substrate, significantly altering surface properties and undermining film deposition. By systematically removing and reintroducing these additives, we demonstrate their pivotal role in driving wetting failure, adhesion loss, and electrical degradation. While removing the additives enables the deposition of uniform, adherent, and conductive gold films, these species are also essential to Ecoflex’s extreme softness, revealing an inherent trade-off between surface functionality and mechanical compliance. Upon reintroduction, the oligomers restore softness but reverse the interfacial improvements, even compromising previously well-adhered films. These findings clarify the origin of Ecoflex’s surface instability and underscore the need to consider bulk formulation when designing elastomer interfaces for soft electronics.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".