Measuring Point Defect Density in Individual Carbon Nanotubes Using Polarization-Dependent X-ray Microscopy
Bibliographic record
Abstract
The presence of defects in carbon nanotubes strongly modifies their electrical, mechanical, and chemical properties. It was long thought undesirable, but recent experiments have shown that introduction of structural defects using ion or electron irradiation can lead to novel nanodevices. We demonstrate a method for detecting and quantifying point defect density in individual carbon nanotubes (CNTs) based on measuring the polarization dependence (linear dichroism) of the C 1s --> pi* transition at specific locations along individual CNTs with a scanning transmission X-ray microscope (STXM). We show that STXM can be used to probe defect density in individual CNTs with high spatial resolution. The quantitative relationship between ion dose, nanotube diameter, and defect density was explored by purposely irradiating selected sections of nanotubes with kiloelectronvolt (keV) Ga(+) ions. Our results establish polarization-dependent X-ray microscopy as a new and very powerful characterization technique for carbon nanotubes and other anisotropic nanostructures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 teacher head, 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".