Structural colour of unary and binary colloidal crystals probed by scanning transmission X-ray microscopy and optical microscopy
Bibliographic record
Abstract
Colloidal crystals composed of micro- or nano- colloids have been investigated in various fields such as photonics due to their unique optical properties. Binary colloidal crystals have an outstanding potential for fine-tuning material properties by changing the components, concentration, or size of colloids. Because of their tunable optical, electrical, magnetic, and mechanical properties, those materials attracted great attention. However, it has been hard to elucidate internal structures without fluorescent labelling or cross-sectioning. Here, we demonstrate the structural analysis of not only unary but also binary colloidal crystals using scanning transmission x-ray microscopy and compare the results with colloidal structures and optical properties observed by optical microscopy. Based on the comparison of images obtained by these two methods, the domains of colloidal crystals consisting of different structures and colours were directly identified without any additional sample preparation. Therefore, it was possible to investigate the structural colours of local domains of unary and binary colloidal crystals such as the face centred cubic (FCC) structure with different orientations, that is FCC (111) and FCC (001), and hexagonal close-packed structure, HCP (0001).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".