Field-emission from quantum-dot-in-perovskite solids
Bibliographic record
Abstract
Abstract Quantum dot and well architectures are attractive for infrared optoelectronics, and have led to the realization of compelling light sensors. However, they require well-defined passivated interfaces and rapid charge transport, and this has restricted their efficient implementation to costly vacuum-epitaxially grown semiconductors. Here we report solution-processed, sensitive infrared field-emission photodetectors. Using quantum-dots-in-perovskite, we demonstrate the extraction of photocarriers via field emission, followed by the recirculation of photogenerated carriers. We use in operando ultrafast transient spectroscopy to sense bias-dependent photoemission and recapture in field-emission devices. The resultant photodiodes exploit the superior electronic transport properties of organometal halide perovskites, the quantum-size-tuned absorption of the colloidal quantum dots and their matched interface. These field-emission quantum-dot-in-perovskite photodiodes extend the perovskite response into the short-wavelength infrared and achieve measured specific detectivities that exceed 10 12 Jones. The results pave the way towards novel functional photonic devices with applications in photovoltaics and light emission.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".