Controlled Crystal Plane Orientations in the ZnO Transport Layer Enable High‐Responsivity, Low‐Dark‐Current Infrared Photodetectors
Bibliographic record
Abstract
Colloidal quantum dots (CQD) have emerged as attractive materials for infrared (IR) photodetector (PD) applications because of their tunable bandgaps and facile processing. Presently, zinc oxide is the electron-transport layer (ETL) of choice in CQD PDs; however, ZnO relies on continuous ultraviolet (UV) illumination to remove adsorbed oxygen and maintain high external quantum efficiency (EQE), speed, and photocurrent. Here, it is shown that ZnO is dominated by electropositive crystal planes which favor excessive oxygen adsorption, and that this leads to a high density of trap states, an undesired shift in band alignment, and consequent poor performance. Over prolonged operation without UV exposure, oxygen accumulates at the electropositive planes, trapping holes and degrading performance. This problem is addressed by developing an electroneutral plane composition at the ZnO surface, aided by atomic layer deposition (ALD) as the means of materials processing. It is found that ALD ZnO has 10× lower binding energy for oxygen than does conventionally deposited ZnO. IR CQD PDs made with this ETL do not require UV activation to maintain low dark current and high EQE.
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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) | 0.000 | 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 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".