Colloidal Quantum Dot Bulk Heterojunction Solids with Near‐Unity Charge Extraction Efficiency
Bibliographic record
Abstract
Abstract Colloidal quantum dots (CQDs) are of interest for optoelectronic applications owing to their tunable properties and ease of processing. Large‐diameter CQDs offer optical response in the infrared (IR), beyond the bandgap of c‐Si and perovskites. The absorption coefficient of IR CQDs (≈10 4 cm −1 ) entails the need for micrometer‐thick films to maximize the absorption of IR light. This exceeds the thickness compatible with the efficient extraction of photogenerated carriers, a fact that limits device performance. Here, CQD bulk heterojunction solids are demonstrated that, with extended carrier transport length, enable efficient IR light harvesting. An in‐solution doping strategy for large‐diameter CQDs is devised that addresses the complex interplay between (100) facets and doping agents, enabling to control CQD doping, energetic configuration, and size homogeneity. The hetero‐offset between n ‐type CQDs and p ‐type CQDs is manipulated to drive the transfer of electrons and holes into distinct carrier extraction pathways. This enables to form active layers exceeding thicknesses of 700 nm without compromising open‐circuit voltage and fill factor. As a result, >90% charge extraction efficiency across the ultraviolet to IR range (350–1400 nm) is documented.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".