A CONVENTIONAL SYNTHESIS APPROACH TO PREPARE LEAD SULFIDE (PbS) NANOPARTICLES VIA SOLVOTHERMAL METHOD
Bibliographic record
Abstract
We are describing a new optimized method for the preparation of single-sized crystalline lead sulphide (PbS) nanoparticles (NPs). The optimized solvothermal method uses a mixture of octadecene and oleic acid as a reaction media and MBTS as a reducing agent. Systematic investigation was performed on various synthesis parameters, such as acid to lead (Pb) and lead to sulphur(S) feed molar ratios, feed amounts of various phosphine compounds, reducing agent, total concentrations of reaction media, growth temperature, as well as different sulphur source compounds. We optimized the amount of 2,2-dithiobis(benzothiazole) (MBTS) in the reaction mixture to produce about 100 nm size and spherical shape zinc blade type PbS NPs. A broad UV absorption spectrum was observed when the MBTS amount was increased in the reaction mixture. The excellent organic solvent dispersion properties, along with near-IR emission spectrum window make these NPs a great choice in optoelectronics applications, especially for photovoltaic devices.
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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) | 0.002 | 0.001 |
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".