(Invited) Development of Ag- and Sn-Based Colloidal Quantum Dots for Near Infrared Photodetection
Bibliographic record
Abstract
Low-cost photodetectors with sensitivity in the second near-infrared window (NIR-II, 1000–1700 nm) are highly demanded. Recently, we made the first demonstration of an Ag2Se colloidal quantum dots (QDs) photodiode with sensitivity up to 1200 nm. By employing secondary phosphine to elevate the precursor reactivity, the Ag2Se QDs with a distinct excitonic absorption peak was achieved. These nanocrystals were deposited from solution into a mesoporous TiO2 scaffold to increase the light absorption and charge separation and reduce the exciton diffusion length. By incorporating a suitable hole-transporting layer between the active layer and Ag anode, the resulting devices showed a responsivity of 4.17 mA/W at 1200 nm.1 Also, Ag2Te QDs are excellent for advancing the detection wavelength. Their synthesis with desired particle sizes, narrow size distribution and high photoluminescence quantum yield (PL QY) is challenging. We systematically investigate critical parameters affecting the synthesis in an organic phase. It shows that high Ag/Te feed ratio leads to smaller size and higher PL QY; under 4:1 Ag/Te feed molar ratio, addition of secondary phosphine leads to narrower size distribution and excellent colloidal stability; under 6:1 Ag/Te feed molar ratio, excess 1-dodecanethiol as a strong ligand slows the nucleation and results in fewer nuclei, leading to a broad size distribution and poor optical properties; additional n-trioctyl phosphine as a weak ligand provides better colloidal stability; and another weak ligand n-tributylphosphine improves Ag2Te QD colloidal stability, focuses size distribution, and enhances PL QY. After optimization relatively large Ag2Te QDs with distinct excitonic absorption peaks (~1050 – 1450 nm) and PL emission peak 1.3 – 1.7 µm (QY up to 6.2%) were obtained. NIR-II photodetection has been demonstrated with a responsivity of ~1.5 mA/W at 1400 nm.2 More recently, we have been developing Sn-based chalcogenide QDs and obtained preliminary photodetection results. These results demonstrate that Ag and Sn chalcogenide QDs offer a low-toxicity route for low-cost fabrication of NIR-II photodetection. Reference: [1] Graddage N, Ouyang J, Lu J, Chu TY, Zhang Y, Li Z, Wu X, Malenfant PRL, Tao Y. Near-Infrared-II Photodetectors Based on Silver Selenide Quantum Dots on Mesoporous TiO2 Scaffolds. ACS Applied Nano Materials 2020, 3: 12209–12217. [2] Ouyang J, Graddage N, Lu J, Zhong Y, Chu TY, Zhang Y, Wu X, Kodra O, Li Z, Tao Y, Ding J. Ag2Te Colloidal Quantum Dots for Near-Infrared-II Photodetectors. ACS Applied Nano Materials 2021, 4: 13587–13601. Keywords: Environmentally Friendly; Near Infrared; Quantum Dots; Photodetection.
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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) | 0.007 | 0.005 |
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".