Assessing the Role of Large Fullerenes as Potential Carriers of Infrared Emission Plateaus
Bibliographic record
Abstract
Abstract We investigate large fullerenes containing between 90 and 1750 carbon atoms and with radii ranging from 4.4 to 12.9 Å, and compare their computed emission spectra to Spitzer data for the fullerene-rich planetary nebulae SMP SMC 24 and SMP LMC 48 to assess their contribution to the broad infrared emission plateaus. The structures are computed without any bias using molecular dynamics simulations and contain mostly five- and six-membered rings, several seven-membered rings, and very few four- and eight-membered rings. Our largest structures consist of multishell fullerenes. The infrared spectra are calculated using the density-functional-based tight-binding theory. Their emission spectra exhibit broad plateaus from 6 to 10 μm and from 14 to 20 μm, whose 6–10/14–20 relative intensity ratios reach a maximum value for ∼200 carbons. The computed 6–10 μm plateaus exhibit distinct subfeatures in agreement with the observations. The subfeatures with the largest intensities peak at 6.6 and 7.7–7.9 μm. We assign these subfeatures to C–C stretching vibrations from the different types of rings arranged in many different ways. A comparison of the computed 6–10/14–20 μm intensity ratios as a function of fullerene size and photon energy with the observed 6–10/14–20 μm intensity ratio for SMP LMC 48 allows us to derive an upper bound of ∼150–200 carbons for the fullerene size.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".