Ligand Exchange Functionalization of CIS Quantum Dots for CIS/ZnO Film Heterojunctions
Bibliographic record
Abstract
Colloidal quantum dots (QD) are rapidly making their way into several optoelectronic applications. While Cd- and Pb-based QDs are promising for high-performance devices, toxicity remains a concern. In this regard, Cu-In-S (CIS) QDs provide an alternative option for scalable, commercial production. A low-temperature, high-throughput process was used to synthesize CIS QDs with 1-dodecanethiol (DDT) ligands. While QD synthesis with a DDT ligand is facile, there are drawbacks when it comes to device implementation and interfacing with electron transport films such as ZnO. A ligand exchange process was employed to replace the DDT ligands in the as-synthesized QDs with 3-mercaptopropionic acid (MPA); owing to the short and bifunctional nature of the MPA molecules, this process improved the surface adhesion and carrier transport to ZnO. I-V measurements on planar structures showed the significance of ligand exchange in CIS QDs for heterojunction device implementation.
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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) | 0.001 | 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".