Optical Resonance Engineering for Infrared Colloidal Quantum Dot Photovoltaics
Bibliographic record
Abstract
We report optically enhanced infrared-harvesting colloidal quantum dot solar cells based on integrated Fabry–Perot cavities. By integrating the active layer of the photovoltaic device between two reflective interfaces, we tune its sensitivity in the spectral region at 1100–1350 nm. The top and bottom electrodes also serve as mirrors, converting the device into an optical resonator. The front conductive mirror consists of a dielectric stack of SiN x and SiO 2 with a terminal layer of ITO and ZnO in which current can flow, while the back mirror consists of a highly reflective gold layer. Adjusting the reflectivity and central wavelength of the front mirror as well as the thickness of the active layer allowed increases in absorption by a total of 56% in the infrared, leading to a record external quantum efficiency of 60% at 1300 nm. This work opens new avenues toward low-cost, high-efficiency rear-junction photovoltaic harvesters that add to the overall performance of silicon solar cells.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".