Multiple exciton generation induced enhancement of the photoresponse ofpulsed-laser-ablation synthesized single-wall-carbon-nanotube/PbS-quantum-dotsnanohybrids
Bibliographic record
Abstract
The pulsed laser deposition method was used to decorate appropriately single wall carbon nanotubes (SWCNTs) with PbS quantum dots (QDs), leading to the formation of a novel class of SWCNTs/PbS-QDs nanohybrids (NHs), without resorting to any ligand engineering and/or surface functionalization. The number of laser ablation pulses (NLp) was used to control the average size of the PbS-QDs and their coverage on the SWCNTs' surface. Photoconductive (PC) devices fabricated from these SWCNTs/PbS-QDs NHs have shown a significantly enhanced photoresponse, which is found to be PbS-QD size dependent. Wavelength-resolved photocurrent measurements revealed a strong photoconductivity of the NHs in the UV-visible region, which is shown to be due to multiple exciton generation (MEG) in the PbS-QDs. For the 6.5 nm-diameter PbS-QDs (with a bandgap (Eg) = 0.86 eV), the MEG contribution of the NHs based PC devices was shown to lead to a normalized internal quantum efficiency in excess of 300% for photon energies ≥4.5Eg. While the lowest MEG threshold in our NHs based PC devices is found to be of ~2.5Eg, the MEG efficiency reaches values as high as 0.9 ± 0.1.
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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 | 0.000 |
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 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".