Single‐Step Generation of Flexible, Free‐Standing Arrays of Multimode Cylindrical Waveguides
Bibliographic record
Abstract
Polymer matrices patterned with 3‐D waveguide circuitry are critical components of flexible photonics but cannot be fabricated through conventional, linear lithographic techniques. By exploiting the spontaneous filamentation and modulation instability (MI) of a uniform optical field in a range of silicone‐acrylate‐based photopolymerizable fluids, the authors report the generation of free‐standing arrays of cylindrical, multimode waveguides with tunable flexibility in a single, room‐temperature step. A broad, incandescent beam becomes unstable and spontaneously divides into a large population (≈10 000 cm−2) of microscopic filaments; each filament becomes entrapped within a self‐induced cylindrical waveguide and propagates through the medium without diverging. By spatially modulating the beam, it is possible to generate cylindrical waveguide arrays with square symmetry. By controlling the extent of cross‐linking and the relative amount of silicone surfactant in the polymerized matrix, it is possible to tune the hardness of the arrays over an order of magnitude (Shore‐OO 9 ± 5 to 94 ± 2). The authors show that flexible waveguide arrays that possess relatively low values of hardness can be reversibly compressed to up to 70% of their original lattice parameter while retaining waveguiding capacity; the arrays exhibit 100% recovery after multiple cycles of compression and decompression.
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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".