Synthesis of Size-Tunable Spherical Carbon Nanoparticles By Polymerization of Sp-Carbon Rich Precursors and Characterization of Optical Properties for Energy Conversion and Storage Applications
Bibliographic record
Abstract
Carbon nanoparticles (CNPs) are considered as one of the most promising materials due to their unique optical and electronic properties for a wide range of applications in the field of optoelectronics, energy conversion/ storage and bio-imaging. The high photoluminescence, photostability and low toxicity of CNPs have made them suitable for various applications. The unique network of hybridized sp2 carbon atoms provides unique properties of CNPs as it allows delocalization of the electrons over the entire surface of the molecule. The studies have shown that the carbon core is responsible for the strong absorption of light while the luminescence comes from the surface sites and the functional groups present on the surface. The functions and properties of the CNPs could be modulated by changing their shape, size and dimensionality. Despite all these advantages, CNPs have been slow to transform from laboratory prototypes into real life industrial scale products because of the difficulty in synthesizing them and in controlling their size. The control over their size is important as the optical properties of CNPs have been shown to be varying with the variation in size. The synthetic methods reported until now involves high-temperature (>100 oC) processes which often results in uncontrolled shape, size, polydisperse and chemically inert nanoparticles, which makes it very difficult to modulate their optical, electronic and morphological properties. Thus, the development of low-temperature, controlled synthesis is desirable. We report the development of new synthetic methods for the preparation of carbon nanoparticles allowing precise control of their shape, size and properties by polymerization of sp-carbon rich precursors. These precursors (butadiyne and acetylene) tend to become thermodynamically unstable when polymerized to long polyyne chains and decompose inside the reaction mixture to give CNPs. Hence, these polyyne intermediates provide us the control over the size of CNPs during the reaction and in turn, over their properties for further modulation and functionalization. The size-tunable nanoparticles were synthesized in a single step from different polymerization techniques such as dispersion and micro-emulsion with Glaser-Hay polymerization. The size of the resulting carbon nanoparticle is controlled by changing different reaction parameters such as the monomer loadings and the concentration. The control over the different parameters allows us to obtain monodisperse spherical CNPs with a size in the range of 25 nm to 250 nm and use of low temperature methods (<100 oC) allows us to overcome the limitations associated with current methods. After isolation, CNPs were characterized by dynamic light scattering, microscopy to analyze the shape and size of the CNPs. To analyze the nature of carbon molecules, Raman spectroscopy and FTIR were used. The optoelectronic behavior of the CNPs was characterized in order to establish the size-property relationships.
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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) | 0.000 | 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".