Smooth-morphology Ultrasensitive Solution-processed Photoconductors
Bibliographic record
Abstract
Solution-processed optoelectronic materials offer a route to low cost photodetectors, large area solar cells, and integrated optical sources. While significant progress has been reported in organic and polymer spin-cast optoelectronics, colloidal quantum dots offer a distinct further advantage -- the convenient tuning of absorption onset via the quantum size effect. Electronic transport has recently been enhanced in size effect tuned colloidal quantum dot films using ligand exchange, resulting in ultrasensitive photodetectors in both visible and infrared wavelengths. Solid-film ligand exchange, however, generally results in rough film morphologies that are incompatible with high uniformity image sensors. Here, we report a new route to visible-wavelength spin-cast lead sulfide (PbS) nanocrystal photoconductive photodetectors with a sub 1% roughness, compared to the ~10% roughness obtained using previously reported approaches. The new procedure yields devices that exhibit 10 A/W responsivities and reveals an added significant advantage: when illumination conditions change, the photodetectors respond with a single time constant of 20 ms. This compares very favorably to the multi second and multi-time-constant response of previously reported PbS-nanocrystal photoconductive photodetectors.
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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) | 0.002 | 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".