AC Electric Field-Induced Alignment and Long-Range Assembly of Multi-Wall Carbon Nanotubes Inside Aqueous Media
Bibliographic record
Abstract
The present work examines the behavior of multiwall carbon nanotubes (MWCNT) inside AC electric fields created by three-dimensional electrodes. The response of carbon nanotubes stably suspended in water with the aid of a nonionic surfactant is monitored by combining microscopic observations with on-line measurements of the suspension resistivity. It is found that polarization effects induced by the externally applied AC electric field on MWCNTs can cause their unidirectional orientation and end-to-end contact that result in formations of spatially distributed, long-range, three-dimensional and electrically conducting structures that span the entire gap between the electrodes. The length of the formed structures, which in the present case was approximately 30 times larger than that of an individual carbon nanotube, can be controlled by adjusting the spacing between the electrodes. The influence of main experimental parameters, namely, MWCNT concentration, applied voltage, AC field frequency, and electrode surface topography on the suspension behavior is experimentally examined. Results are demonstrated for applied voltage values, AC field frequencies, and carbon nanotube concentrations in the range 4-40 Vptp, 10 Hz-5 MHz, and 0.001-2.0 wt%, respectively. While higher electric field strengths accelerate the formation of aligned structures, higher frequency values were found to result in suspensions that exhibit smaller electrical resistivity. Carbon nanotube dispersions exposed to an AC electric field exhibit a 100-fold or more decrease in their electrical resistivity, even when carbon nanotube concentrations as low as 0.005 wt% are used.
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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".