Noninjection Gram-Scale Synthesis of Monodisperse Pyramidal CuInS<sub>2</sub> Nanocrystals and Their Size-Dependent Properties
Bibliographic record
Abstract
CuInS2 nanocrystals are viewed as very good candidates for solar harvesting and light emitting applications. Here we report an optimized noninjection method for the synthesis of monodisperse pyramidal CuInS2 nanocrystals with sizes ranging from 3 to 8 nm. This synthetic route is able to yield large amounts of high quality nanoparticles, usually in the gram scale for one batch experiment. The structure and surface studies showed that the resulting nanocrystals are pyramids of CuInS2 tetragonal phase with well-defined facets, while their surface is functionalized with dodecanethiol capping ligands. Spectroscopic and electrochemical measurements revealed size-dependent optical and electrical properties of CuInS2 nanocrystals, demonstrating quantum confinement effects in these systems. The size-dependent optical bandgaps of CuInS2 nanocrystals were found to be consistent with the finite-depth well effective mass approximation (EMA) calculations, which provide a convenient method to estimate the diameter of CuInS2 pyramids. Additionally we have also determined some important physical parameters, including bandgaps and energy levels, for this system, which are crucial for the integration of CuInS2 nanocrystals in potential device applications.
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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) | 0.001 | 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 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".