Complex oxide thin films towards surface-phonon-polariton-based infrared optoelectronics [Invited]
Bibliographic record
Abstract
Infrared nanophotonics offers enormous potential for enhancing infrared optoelectronic technologies, due to the ability to confine light to deeply sub-wavelength dimensions. One of the limitations of traditional nanophotonics approaches is the inherent losses present in the plasmonic materials that are conventionally used. Surface phonon polaritons offer a lower-loss alternative but are more difficult to integrate with conventional III-V-based semiconductors used for infrared optoelectronics. In this work, we examine the properties of complex oxides, which can be grown directly onto III-V semiconductors for the purpose of infrared light detection. We grow films of both SrTiO 3 and BaTiO 3 on GaAs using pulsed laser deposition, and examine their properties using a combination of X-ray diffraction, atomic force microscopy, transmission electron microscopy, and infrared reflectance spectroscopy. We find that the films grown exhibit good crystallinity with smooth, uniform surfaces, and with occasional minor misoriented grains. Their optical properties indicate higher losses than perfect single crystal substrates, but by less than a factor of two, with phonon Q factors of 18-60, which is favorable when compared with plasmonic materials. We then conduct numerical simulations, which show that these films can be used to create surface phonon polariton infrared detectors that outperform similar metallic gratings by a factor of four. Our results show that the integration of oxide materials with conventional semiconductors is a viable route to improving infrared detector technology, competitive with other nanophotonics approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".