Investigation of multiwalled carbon nanotube interconnection geometry and electrical characteristics of an CNT-filled aluminum microgap
Bibliographic record
Abstract
In recent years a very large amount of data has been collected regarding devices formed by multiwalled carbon nanotubes (MWCNTs) in polymer matrix as well as single nanotubes. Conversely, very little investigation exists of nanotube networks composed of a small number of MWCNTs. A detailed investigation of the long time stability, adhesion to the surface, and topological structure of the interconnections between MWCNTs is reported here. Three different microscopy techniques, focused ion beam (FIB), scanning electron microscope (SEM), and atomic force microscope (AFM), were used to investigate the interconnection of MWCNTs deposited by electrophoresis on a thermally oxidized silicon wafer with aluminum microgap structures. SEM, AFM, and FIB imaging revealed an interesting interconnection morphology between the drop casted MWCNTs. In particular it was found that in some cases the MWCNTs were connected to each other in a geometry similar to a twisted structure. Furthermore a good stability of the sample in time has been found, proving a strong adhesion of the nanotubes to the oxide surface. Despite the fact that electrical contacts with aluminum to carbon nanotube - based devices are in general not very reliable, using the dielectrophoresis deposition technique with an adequate subsequent annealing procedure, long-term stable temperature sensors with carbon nanotube networks in the aluminum contact microgap were realized. Their temperature dependence can be explained by modeling the internanotube contact resistance.
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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) | 0.001 | 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".