Progress in Domain‐Engineered Photonics Materials
Bibliographic record
Abstract
Artificially engineering ferroelectric and ferromagnetic oxide materials' domain structures provide many potential opportunities to explore such materials' extraordinary nonlinear optic, electrooptic (EO), and magnetooptic (MO) effects, to build unique photonic bandgap structures, and to generate phonon-photon-coupled polaritons.Domain engineering can be applied onto such materials, either one-dimensinally or two-dimensionally, can be patterned on the above materials periodically, quasiperiodically, or aperiodically, or can be aligned along different crystalline orientations or by using complicated cascaded structures.Those commonly involved photonic materials can be versatile including ferroelectricferromagnetic oxide crystals, semicondcutors, electrooptic polymers, and so on, in either bulk, thin film, or waveguide forms.Implementation of such domain engineering can be very versatile too, and it may follow direct crystal growth, superlattice growth, overgrowth on an already patterned structure, electrical field poling, E-beam writing, and so on.Potential applications of such domain-engineered materials for photonics are very widespread, including nonlinear frequency conversion, EO modulation, optical bistability, acoustics, ultrasonic transducers, terahertz (THz) generation, fiber optics, left-hand materials, and so on.A remarkable example of past researches in this area is the realization of the quasi-phase-matched (QPM) nonlinear frequency conversions using periodically poled crystals.Recently, development of new photonic and optoelectronic components using such advanced domain-engineered materials, covering a broad range of operation frequencies and having unique optical functions, has become very attractive.However, the effort toward this direction has been crucially relying on the availability of new optical materials, new
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".