Modeling mechanical energy storage in springs based on carbon nanotubes
Bibliographic record
Abstract
A modeling study of the potential for storing energy in the elastic deformation of springs comprised of carbon nanotubes (CNTs) is presented. Analytic models were generated to estimate the ideal achievable energy density in CNTs subject to axial tension, compression, bending and torsion, taking into account limiting mechanisms such as the strength of individual CNTs, the onset of buckling, and the packing density limitations of CNT groupings. The stored energy density in CNT springs is predicted to be highest under tensile loading, with maximum values more than three orders of magnitude greater than the energy density of steel springs, and approximately eight times greater than the energy density of lithium-ion batteries. Densely packed bundles of precisely aligned, small diameter single-walled carbon nanotubes are identified as the best structure for high performance springs. The conceptual design and modeling of a portable electric power source that stores energy in a CNT spring are presented as tools for studying the potential performance of a system for generating electricity from the CNTs' stored mechanical energy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".