Multibandgap quantum dot ensembles for solar-matched infrared energy harvesting
Bibliographic record
Abstract
Abstract As crystalline silicon solar cells approach in efficiency their theoretical limit, strategies are being developed to achieve efficient infrared energy harvesting to augment silicon using solar photons from beyond its 1100 nm absorption edge. Herein we report a strategy that uses multi-bandgap lead sulfide colloidal quantum dot (CQD) ensembles to maximize short-circuit current and open-circuit voltage simultaneously. We engineer the density of states to achieve simultaneously a large quasi-Fermi level splitting and a tailored optical response that matches the infrared solar spectrum. We shape the density of states by selectively introducing larger-bandgap CQDs within a smaller-bandgap CQD population, achieving a 40 meV increase in open-circuit voltage. The near-unity internal quantum efficiency in the optimized multi-bandgap CQD ensemble yielded a maximized photocurrent of 3.7 ± 0.2 mA cm −2 . This provides a record for silicon-filtered power conversion efficiency equal to one power point, a 25% (relative) improvement compared to the best previously-reported results.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 |
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 teacher head, 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".