Synthesis and Optical Properties of Thiol Functionalized CdSe/ZnS (Core/Shell) Quantum Dots by Ligand Exchange
Bibliographic record
Abstract
The colloidal photoluminescent quantum dots (QDs) of CdSe (core) and CdSe/ZnS (core/shell) were synthesized at different temperatures with different growth periods. Optical properties (i.e., UV/Vis spectra and photoluminescent emission spectra) of the resulting QDs were investigated. The shell‐protected CdSe/ZnS QDs exhibited higher photoluminescent (PL) efficiency and stability than their corresponding CdSe core QDs. Ligand exchange with various thiol molecules was performed to replace the initial surface passivation ligands, that is, trioctylphosphine oxide (TOPO) and trioctylphosphine (TOP), and the optical properties of the surface‐modified QDs were studied. The thiol ligand molecules in this study included 1,4‐benzenedimethanethiol, 1,16‐hexadecanedithiol, 1,11‐undecanedithiol, biphenyl‐4,4′‐dithiol, 11‐mercapto‐1‐undecanol, and 1,8‐octanedithiol. After the thiol functionalization, the CdSe/ZnS QDs exhibited significantly enhanced PL efficiency and storage stability. Besides surface passivation effect, such enhanced performance of thiol‐functionalized QDs could be due to cross‐linked assembly formation of dimer/trimer clusters, in which QDs are linked by dithiol molecules. Furthermore, effects of ligand concentration, type of ligand, and heating on the thiol stabilization of QDs were also discussed.
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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) | 0.001 | 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".