Silicon Surface Passivation for Silicon-Colloidal Quantum Dot Heterojunction Photodetectors
Bibliographic record
Abstract
Sensitizing crystalline silicon (c-Si) with an infrared-sensitive material, such as lead sulfide (PbS) colloidal quantum dots (CQDs), provides a straightforward strategy for enhancing the infrared-light sensitivity of a Si-based photodetector. However, it remains challenging to construct a high-efficiency photodetector based upon a Si:CQD heterojunction. Herein, we demonstrate that Si surface passivation is crucial for building a high-performance Si:CQD heterojunction photodetector. We have studied one-step methyl iodine (CH3I) and two-step chlorination/methylation processes for Si surface passivation. Transient photocurrent (TPC) and transient photovoltage (TPV) decay measurements reveal that the two-step passivated Si:CQD interface exhibits fewer trap states and decreased recombination rates. These passivated substrates were incorporated into prototype Si:CQD infrared photodiodes, and the best performance photodiode based upon the two-step passivation shows an external quantum efficiency (EQE) of 31% at 1280 nm, which represents a near 2-fold increase over the standard device based upon the one-step CH3I passivated Si.
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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 | 0.000 | 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) | 0.000 | 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 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".