Nanostructured Photovoltaic Devices from Thermally-Reactive π-Conjugated Polymer Blends
Bibliographic record
Abstract
A facile method for preparing nano- and microstructured π-conjugated polymers (πCPs) from polymers bearing thermally cleavable solubilizing groups for the application of organic photovoltaic cells is described. Solutions of thermally reactive poly[3-(2-(2-tetrahydropyranyloxy)ethyl)thiophene)] (PTHPET), poly(methylmethacrylate) (PMMA), and camphorsulfonic acid were spin-cast to yield nano- and micro- phase segregated thin films, ∼100 nm thick. A thermally induced, acid-catalyzed, solid-phase reaction, in which the tetrahydropyran group is eliminated, renders the conjugated polymer insoluble. Subsequent removal of PMMA by dissolution affords retention of the conjugated polymer in the form of nano/microarchitectures. This strategy proved useful in the fabrication of controlled nano/microscale structures for organic photovoltaic cells devices, wherein insoluble, nanostructured De-PTHPET served as a donor layer and a spin-cast solution of PCBM accessed the recesses of the film to serve as the electron acceptor layer. The properties of nanopatterned PV devices are compared to conventional bilayer, and bulk heterojunction devices. The nanostructured, donor−acceptor films provided an advantage over molecularly blended films in that potential isolation of electron acceptor in the donor film is decreased, and vice versa, mitigating charge trapping, and providing improved device efficiency.
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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 | 0.000 | 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".