Aqueous Phase Surfactant Selective Shape Controlled Synthesis of Lead Sulfide Nanocrystals
Bibliographic record
Abstract
Aqueous phase synthesis at 80 °C was carried out to synthesize lead sulfide (PbS) nanocrystals (NC) and microcrystals (MC) by using cationic twin-tail surfactants (TTS) such as 12-0-12, 10-2-10, 12-2-12, and 14-2-14 as capping agents in the concentration range from 0.1 −to 2 mM. The effect of hydrophobicity on the shape and size of PbS NC was evaluated by choosing DTAB as a reference surfactant for all TTS. TEM micrographs of PbS MC synthesized in the presence of DTAB indicated the formation of star-shaped MC with sizes between 3 −and 5 μm. An increase in the hydrophobicity, by introducing another tail in the basic structure of DTAB to make 12-0-12, significantly controlled the shape and size and lead to the formation of well-defined nanocubes and spheres 50−100 nm in size. Similarly, the effect of the hydrocarbon tail length on the shape controlled synthesis of PbS NC was systematically evaluated. Pyrene fluorescence measurements were used to determine the variation in the degree of hydrophobicity with respect to both chemical structure as well as concentration of TTS. It was concluded that a stronger hydrophobic character and higher concentration produced well-defined geometries of PbS NC. No significant concentration effect within a range of 0.1−2 mM DTAB and 10-2-10 was observed on the morphology of PbS NC probably due to a much weaker hydrophobicity of these surfactants. An attempt was made to present all TEM results in a schematic phase diagram. This phase diagram provided the best correlation between the shape and the size of PbS NC and the surfactant parameters (i.e., hydrophobicity and concentration effects). Apart from this, shape dependence UV−vis absorbance was also noted and discussed in context with an overall preview of all shapes of PbS NC/MC obtained. The shape controlled synthesis of PbS NC was obtained due to the preferential adsorption of TTS on the {111} crystal planes that directed the overall growth predominantly at the {100} planes. FTIR measurements were used to evaluate the adsorption of TTS on the PbS surface. A large shift in the stretching vibrations of TTS head functional groups suggested their orientation toward the PbS surface. This was further supported by the high-resolution XPS spectra of C 1s and N 1s of adsorbed TTS on the PbS surface. An effective interfacial adsorption of TTS on the surface of PbS NC driven by a stronger hydrophobic character is the key to achieve controlled PbS NC growth at the nanoscale.
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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".