Polymeric nanostructured material for high-density three-dimensional optical memory storage
Bibliographic record
Abstract
The unique properties of a polymer photonic crystal are examined with respect to applications as a medium for high-density three-dimensional optical data storage media. The nanocomposite material was produced from core-shell latex particles, in which the latex cores contained dye-labeled polymer. Nonfluorescent latex shells were attached to the core particles. Upon annealing, the close-packed core-shell particles formed a nanostructured material with the fluorescent particles periodically embedded into the optically inert matrix in a hexagonal close-packed structure. A two-photon laser scanning microscope was used to write bits of information into the material by photobleaching the optically sensitive particles and, under much lower fluence, read out the resulting image. Relative to conventional homogeneous storage media, the nanostructured periodic material is shown to increase the effective optical storage density by at least a factor of 2 by spatially localizing the optically active region and imposing an optically inactive barrier to cross-talk between bits. This polymer photonic crystal has the potential to dramatically improve performance further through the improved capabilities to optimize the photochemical processes and more fully exploiting the periodic nature of the information domains in the image processing.
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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".