Instrument for evaluating the electrical resistance and wavelength-resolved transparency of stretchable electronics during strain
Bibliographic record
Abstract
A complete analysis of strain tolerance in a stretchable transparent conductor (TC) should include tracking of both electrical conductivity and transparency during strain; however, transparency is generally neglected in contemporary analyses. In this paper, we describe an apparatus that tracks both parameters while TCs of arbitrary composition are deformed under stretching-mode strain. We demonstrate the tool by recording the electrical resistance and light transmission spectra for indium tin oxide-coated plastic substrates under both linearly increasing strain and complex cyclic strain processes. The optics are sensitive across the visible spectrum and into the near-infrared region (∼400-900 nm), and without specifically optimizing for sampling speed, we achieve a time resolution of ∼200 ms. In our automated analysis routine, we include a calculation of a common TC figure of merit (FOM), and because solar cell electrodes represent a key TC application, we also weigh both our transparency and FOM results against the solar power spectrum to determine "solar transparency" and "solar FOM." Finally, we demonstrate how the apparatus may be adapted to measure the basic performance metrics for complete solar cells under uniaxial strain.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".