The Mutual Interactions of Carbon Nanotubes During Dielectrophoresis
Bibliographic record
Abstract
Dielectrophoresis (DEP) has been widely used for the deposition of various types of nanomaterials including carbon nanotubes (CNTs). Here, we report the results of experiments that show that the interactions between deposited and suspended nanotubes during the deposition process can considerably affect the dynamics and the final results of the deposition. Semiperiodic stripes of nanotubes bridging two electrodes are formed from solutions containing no surfactant. The periodicity of the patterns depends on the geometry of the electrodes. Finite-element method simulations are used to explain the mechanisms underlying the observed experimental outcomes. The pattern formation is shown to be related to the mutual effects of CNTs on each other. The reason lies in the changes in the electric field as a result of deposition of CNTs. These changes directly alter the DEP force field and, therefore, the way the CNTs are guided. The extent of effectiveness of the electrothermal force, which turns out to be substantial for some solutions, is also investigated, and it is shown that although in some situations the heat generated by the current passing through the nanotubes considerably increases this force, the DEP force remains dominant when a surfactant-free solution is 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".