Electrically controlled diffraction employing electrophoresis, supercapacitance, and total internal reflection
Bibliographic record
Abstract
The reflectance of a surface can be altered by controlling the concentration of dye ions in a region adjacent to an optically transparent and electrically conductive thin film. We present a method for nonmechanical light deflection achieved by altering the reflectance of a diffraction grating, an approach that creates new diffraction peaks that lie between those associated with the original grating spacing. We have demonstrated this effect by applying an electrical potential difference between interdigitated indium-tin oxide (ITO) electrodes and measuring the intensity of one of the new diffraction peaks. The measured diffraction peak intensities were found to reversibly deflect approximately 7% of the reflected light to previously nonexistent peaks. The diffraction grating was formed by patterning a thin film of planar, untreated ITO on a glass substrate using standard photolithography techniques. The size scale for this method of electrically controlled diffraction is limited only by the lithographic process; thus there is potential for the grating to deflect light to angles greater than those achievable using other methods. This approach could be used in applications such as telecommunications, where large deflection angles are required, or other applications where alternate beam-steering methods are cost prohibitive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".