Rational synthesis of novel “giant” CuInTeSe/CdS core/shell quantum dots for optoelectronics
Bibliographic record
Abstract
"Giant" core/shell quantum dots (g-QDs) are promising candidates for emerging optoelectronic technologies thanks to their facile structure/composition-tunable optoelectronic properties and outstanding photo-physical/chemical stability. Here, we synthesized a new type of CuInTeSe (CITS)/CdS g-QDs and regulated their optoelectronic properties by controlling the shell thickness. Through increasing the shell thickness, as-prepared g-QDs exhibited tunable red-shifted emission (from 900 to 1200 nm) and prolonged photoluminescence (PL) lifetimes (up to ∼14.0 μs), indicating a formed band structure showing efficient charge separation and transfer, which is further testified by theoretical calculations and ultrafast time-resolved transient absorption (TA) spectroscopy. These CITS/CdS g-QDs with various shell thicknesses can be employed to fabricate photoelectrochemical (PEC) cells, exhibiting improved photoresponse and stability as compared to the bare CITS QD-based devices. The results indicate that the rational design and engineering of g-QDs is very promising for future QD-based optoelectronic technologies.
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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".