Synthesis of fluorescent carbon nanoparticles by dispersion polymerization of acetylene
Bibliographic record
Abstract
Carbon nanoparticles (CNPs) are of interest due to their distinct optoelectronic properties for a diverse range of applications and their functions and properties can be changed by varying their shape, size and dimensionality. The current synthetic methods reported often result in uncontrolled shape, size and polydispersity. In this work, we focus on developing a low-temperature synthetic method for preparing fluorescent carbon nanoparticles and modulation of properties. Our method, based on the dispersion Glaser-Hay polymerization of acetylene followed by decomposition into a carbonaceous material, yields CNPs with sizes varying from 30 nm to 60 nm. The change in reaction parameters influences the shape and size of CNPs, yielding spherical CNPs. The residual alkynes were exploited further for post-functionalization/graphitization by UV irradiation to yield multifunctional CNPs, which were fluorescent in the blue region. The CNPs were characterized with microscopy and spectroscopy techniques after synthesis and after UV-irradiation to study the morphological, chemical, physical and optical properties. This allowed us to understand the influence of parameter variation on the properties and to attempt to establish the structure-property relationship.
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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".