Low-loss, low-voltage, AlGaAs/GaAs high speed optical switch with doping and composition graded heterojunction interfaces
Bibliographic record
Abstract
Carrier-injection-type high-speed semiconductor optical switches have been of interest in recent years due to their nanosecond switching times, their immunity to variations in temperature, wavelength, polarization, etc, and the ease with which they can be monolithically integrated with other optoelectronic components and electronic circuitry. Their drawbacks, however, have been high insertion loss and excessive power dissipation. To overcome these limits, a novel, large cross-section, single-mode AlGaAs/GaAs optical switch has been designed and fabricated. The switch's strip-loaded waveguide uses a five-layer W-shaped heterostructure and a 1.7&mgr;m-thick core layer, which provides high fiber-coupling efficiency. Since the constituent heterojunction band discontinuities can impede the current across the junction, the addition of 20nm-40nm thick, compositionally graded interfaces significantly reduces the switching voltage. In addition, using a lightly doped core layer can reduce the series resistance of the switch, which is important in heat reduction. The core doping needs to be low otherwise it will cause increased free-carrier absorption, which contributes to high insertion loss. We have fabricated switches with different core doping levels using both abrupt and graded heterojunctions. The measured on-chip optical propagation losses are 0.3dB/cm for unintentionally doped core, 1.5dB/cm for n = 1x10<sup>16</sup>cm<sup>-3</sup> doped core, and 2.7dB/cm for n = 5x10<sup>16</sup>cm<sup>-3</sup> doped core. The measured I-V curves show that the switching voltage can be reduced by changing abrupt heterojunctions to graded ones. The calculated theoretical band structure for switches with abrupt/graded heterojunctions based on thermionic emission clearly demonstrated the advantages of applying grading in semiconductor optical switches.
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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 | 0.001 |
| 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".