Effect of pre‐aging intermediate layers on the performance of multi‐layer organic photovoltaic devices
Bibliographic record
Abstract
Abstract Understanding the degradation behaviour of organic photovoltaic (OPV) devices is an essential part to improve their stability prior to massive production. Accelerated aging can help to assess their stability and study the underlying degradation mechanisms of OPVs. Most studies focus on individual layers or a full device, and little is known about the role a pre‐aged layer stack plays in the performance of a device. Herein, we report the investigation of the effects of pre‐aging of multiple layers on the performance of OPVs. Instead of aging a single layer or an entire stack (sequential layers: ITO/PEDOT:PSS/MoOx/F‐BsubPc/C 60 /BCP/Ag), our process involved aging the intermediate layer stack for 24 h after depositing a specific layer before continuing with the subsequent depositions to fully fabricate/manufacture OPVs. Aging was conducted under four controlled conditions considering parameters including moisture, gas type, and temperature in the absence of light according to the International Summit on Organic Photovoltaic Stability (ISOS) protocols. Short of PEDOT:PSS we found that multiple layers, being subjected to the parameters, resulted in a decline in OPV device performance after being fully manufactured. Device performance is evaluated based on short‐circuit current density ( J sc ), power conversion efficiency (PCE), and open‐circuit voltage ( V oc ). Our analysis provides insight into the degradation mechanisms of layered/planar OPV structures and offers strategic guidance for optimizing fabrication processes, particularly during the layer deposition transitions. We recommend that during OPV vacuum deposited fabrication, intermediate layers should be protected from moisture, O 2 , high temperature, and even inert gases, preferably in a low‐vacuum environment.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".