Solar Cells, Photodetectors, and Optical Sources from Infrared Colloidal Quantum Dots
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Optoelectronic devices made via spin‐coating of soft materials onto an arbitrary substrate enable ready integration, low cost, and physical flexibility. The use of solution‐processed colloidal quantum dots offers the added advantage of quantum‐size‐effect tuning of material bandgap. Tuning across the near‐ and short‐wavelength infrared (SWIR) spectral regions enables applications in fiber‐optic communications, night vision and biomedical imaging, and efficient solar energy collection. Here we review progress in infrared solar cells, light sensors, and optical sources based on solution‐processed materials. The latest solution‐processed photovoltaics now provide 4.2% power conversion efficiencies in the infrared, placing them a factor of three away from enabling a doubling in overall solar power conversion efficiency of visible‐wavelength solution‐processed photovoltaics. The best solution‐processed photodetectors now provide sensitivities of 10 13 Jones D * (normalized detectivity), exceeding the sensitivity of the best epitaxially grown SWIR photodetectors. Infrared optical sources, both broadband light‐emitting diodes and, more recently, lasers, have now also been reported at 1.5 µm.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 it