Ag<sub>2</sub>Te Colloidal Quantum Dots for Near-Infrared-II Photodetectors
Bibliographic record
Abstract
Ag2Te colloidal quantum dots (QDs) are an excellent nanomaterial for applications in the second near-infrared window (NIR-II, 1000–1700 nm). However, synthesis with narrow size distribution and high photoluminescence quantum yield (PL QY) is challenging. In this study, we systematically investigate critical synthesis parameters affecting an organic phase process. We show 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 trioctylphosphine as a weak ligand provides better colloidal stability; and another weak ligand tributylphosphine improves QD colloidal stability, focuses size distribution, and enhances PL QY. A noninjection method maintains narrow size distribution in upscaling syntheses. 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.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".