Highly Conducting Hybrid Silver-Nanowire-Embedded Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) for High-Efficiency Planar Silicon/Organic Heterojunction Solar Cells
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Bibliographic record
Abstract
Embedding nanowires, such as silver nanowires (AgNWs), in a transparent conductive polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) to enhance its conductivity is technologically important for improving the performances of devices comprising transparent conductive layers. Addition of nanowires in the highly conducting form of cosolvent (ethylene glycol) or mixed-cosolvent (ethylene glycol and methanol) modified PEDOT:PSS could change the nanowire structure and significantly alter the conductivity. Here, we report a simple method to embed AgNWs in PEDOT:PSS efficiently to improve its conductivity. By incorporating nanowires in the mixed cosolvent matrix prior to addition into PEDOT:PSS, this method preserves the structure of the nanowires while enabling conductivity enhancement. In contrast, the addition of AgNWs into cosolvent-premodified PEDOT:PSS leads to breaking of nanowires and conductivity impediment. The hybrid films with efficiently embedded AgNWs and mixed-cosolvent-modified PEDOT:PSS show a sheet resistance of 104 Ω/□, which is among the lowest ever reported for the as-deposited films, with conductivity enhancement of 33% relative to that of mixed-cosolvent-modified PEDOT:PSS. The resulting planar heterojunction solar cell (HSC) based on AgNW-embedded PEDOT:PSS exhibits a power conversion efficiency of greater than 15%. This demonstrates the importance of reducing sheet resistance by integrating nanowires into the PEDOT:PSS matrix as effective charge-transfer conduits interconnecting the highly conducting quinoid chains. The present approach to efficiently embed AgNWs in PEDOT:PSS could be readily extended to other nanowires or nanoparticles for improving the performance of PEDOT:PSS for applications in not just HSCs but indeed other electronic devices that require both transparent and highly conductive layers.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it