Statistical Paradigm for Organic Optoelectronic Devices: Normal Force Testing for Adhesion of Organic Photovoltaics and Organic Light-Emitting Diodes
Bibliographic record
Abstract
In this study, we assess the utility of a normal force (pull-test) approach to measuring adhesion in organic solar cells and organic light-emitting diodes. This approach is a simple and practical method of monitoring the impact of systematic changes in materials, processing conditions, or environmental exposure on interfacial strength and electrode delamination. The ease of measurement enables a statistical description with numerous samples, variant geometry, and minimal preparation. After examining over 70 samples, using the Weibull modulus and the characteristic breaking strength as metrics, we were able to successfully differentiate the adhesion values between 8-tris(hydroxyquinoline aluminum) (Alq 3 ) and poly(3-hexyl-thiophene) and [6,6]-phenyl C61-butyric acid methyl ester (P3HT:PCBM) interfaces with Al and between two annealing times for the bulk heterojunction polymer blends. Additionally, the Weibull modulus, a relative measure of the range of flaw sizes at the fracture plane, can be correlated with the roughness of the organic surface. Finite element modeling of the delamination process suggests that the out-of-plane elastic modulus for Alq 3 is lower than the reported in-plane elastic values. We suggest a statistical treatment of a large volume of tests be part of the standard protocol for investigating adhesion to accommodate the unavoidable variability in morphology and interfacial structure found in most organic devices.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".