Graft-Induced Midgap States in Functionalized Carbon Nanotubes
Bibliographic record
Abstract
Covalent addition of functional groups onto carbon nanotubes is known to generate lattice point defects that disrupt the electronic wave function, resulting namely in a reduction of their optical response and electrical conductance. Here, conductance measurements combined with numerical simulations are used to unambiguously identify the presence of graft-induced midgap states in the electronic structure of covalently functionalized semiconducting carbon nanotubes. The main experimental evidence is an increase of the conductance in the OFF-state after covalent addition of 4-bromophenyl grafts on many single- and double-walled individual nanotubes, the effect of which is fully suppressed after thermodesorption of the adducts. The graft-induced current leakage is thermally activated and can reach several orders of magnitude above its highly insulating pristine-state level. Ab initio simulations of various configurations of functionalized nanotubes corroborate the presence of these midgap states and show their localization around the addends. Moreover, the electronic density of these localized states exhibits an extended hydrogenoid profile along the nanotube axis, providing access for long-range coupling between the grafts. We argue that covalent nanotube chemistry is a powerful tool to prepare and control midgap electronic states on nanotubes for enabling further studies of the intriguing properties of interacting 1D localized states.
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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 | 0.000 | 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 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".