Jointly Tuned Plasmonic–Excitonic Photovoltaics Using Nanoshells
Bibliographic record
Abstract
Recent advances in spectrally tuned, solution-processed plasmonic nanoparticles have provided unprecedented control over light's propagation and absorption via engineering at the nanoscale. Simultaneous parallel progress in colloidal quantum dot photovoltaics offers the potential for low-cost, large-area solar power; however, these devices suffer from poor quantum efficiency in the more weakly absorbed infrared portion of the sun's spectrum. Here, we report a plasmonic-excitonic solar cell that combines two classes of solution-processed infrared materials that we tune jointly. We show through experiment and theory that a plasmonic-excitonic design using gold nanoshells with optimized single particle scattering-to-absorption cross-section ratios leads to a strong enhancement in near-field absorption and a resultant 35% enhancement in photocurrent in the performance-limiting near-infrared spectral region.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".