Metallic and Semiconducting Single-Walled Carbon Nanotubes: Differentiating Individual SWCNTs by Their Carbon 1s Spectra
Bibliographic record
Abstract
The C 1s inner shell excitation spectra of individual metallic and semiconducting single-walled carbon nanotubes (SWCNTs) were measured using high-resolution electron energy loss spectroscopy in an aberration-corrected transmission electron microscope (TEM-EELS). On the basis of its diameter, the metallic SWCNT is most likely a (10,10) sample, whereas (11,12) and a number of other chiral vectors are consistent with the diameter of the semiconducting SWCNTs. The C 1s X-ray absorption spectra of the same electronically pure SWCNT materials were measured as individual bundles or agglomerations of bundles by scanning transmission X-ray microscopy. Spectral differences in the C 1s → π* transitions of metallic and semiconducting species, related to differences in the van Hove singularities in their unoccupied states, are observed by both methods. The fine structure of the C 1s → π* transitions is similar to that recently reported from nonspatially resolved X-ray absorption spectroscopy of ensemble samples of high-purity metallic and semiconducting SWCNTs. The quality of the TEM-EELS spectra of individual SWCNTs is such that the line shape can be used to identify if they are metallic or semiconducting, thereby opening up the possibility to interrogate the electronic state of single-SWCNT devices. A strong X-ray linear dichroism in the C 1s → π* band of both types of SWCNTs was observed.
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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 | 0.001 | 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".