Carbon nanotube yarns: sensors, actuators, and current carriers
Bibliographic record
Abstract
Carbon nanotubes (CNTs) have attracted extensive attention in the past few years because of their appealing mechanical and electronic properties. Yarns made through spinning multi-walled carbon nanotubes (MWNTs) have been reported. Here we report the application of these yarns as electrochemical actuators, force sensors and microwires. When extra charge is stored in the yarns, change in length. This actuation is thought to be because of electrostatic as well as quantum chemical effects in the nanotube backbones. We report strains up to 0.7 %. At the same time, the charged yarns can respond to a change in the applied tension by generating a current or a potential difference that is related to the applied tension force. As current carriers, the yarns offer a conductivity of ~300 S/cm, which increases linearly with temperature. We report a current capacity of more than 108 A/m2, which is comparable to those of macroscopic metal wires. However, these nanotube yarns have a density (0.8 g/cm3) that is an order of magnitude lower than metallic wires. The MWNT yarns are mechanically strong with tensile strengths reaching 700 MPa. These properties together make them a candidate material for use in many applications including sensors, actuators and light-weight current carriers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".