Channel cracks in atomic-layer and molecular-layer deposited multilayer thin film coatings
Bibliographic record
Abstract
Metal oxide thin film coatings produced by atomic layer deposition have been shown to be an effective permeation barrier. The primary failure mode of such coatings under tensile loads is the propagation of channel cracks that penetrate vertically into the coating films. Recently, multi-layer structures that combine the metal oxide material with relatively soft polymeric layers produced by molecular layer deposition have been proposed to create composite thin films with desired properties, including potentially enhanced resistance to fracture. In this paper, we study the effects of layer geometry and material properties on the critical strain for channel crack propagation in the multi-layer composite films. Using finite element simulations and a thin-film fracture mechanics formalism, we show that if the fracture energy of the polymeric layer is lower than that of the metal oxide layer, the channel crack tends to penetrate through the entire composite film, and dividing the metal oxide and polymeric materials into thinner layers leads to a smaller critical strain. However, if the fracture energy of the polymeric material is high so that cracks only run through the metal oxide layers, more layers can result in a larger critical strain. For intermediate fracture energy of the polymer material, we developed a design map that identifies the optimal structure for given fracture energies and thicknesses of the metal oxide and polymeric layers. These results can facilitate the design of mechanically robust permeation barriers, an important component for the development of flexible 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 | 0.000 |
| 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 | 0.001 | 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 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".