Long wavelength MSM photodetectors fabricated on InGaNAs
Bibliographic record
Abstract
Recently there has been a great deal of interest in the growth of dilute nitride quaternary alloys, such as InGaNAs, on GaAs substrates for the fabrication of GaAs-based components and optoelectronic integrated circuits. The addition of indium to the binary compound GaAs produces a ternary with a lower bandgap and larger lattice constant. The incorporation of nitrogen in this ternary further decreases the bandgap while reducing the lattice constant. This makes it possible to grow material lattice-matched to a GaAs substrate but with a narrower bandgap offering the possibility of growing materials suitable for opto-electronic devices on a GaAs substrate while operating at wavelengths used in long-distance optical communications. These devices can then be integrated with mature GaAs device technologies (MESFET, HBT) in photoreceivers and receivers/transmitters for improved functionality and reliability, lower cost, reduced size, etc. We have fabricated metal-semiconductor-metal (MSM) photodetectors on 1-μm thick In <sub>.1</sub>Ga<sub>.9</sub>N<sub>.03</sub>As<sub>.97</sub> epilayers, a composition that results in a bandgap in the 1.3 μm region. We report on the DC characteristics, frequency dependence and wavelength dependence of the photoresponse. The results are compared to MSMs fabricated on GaAs. The temporal response is not as fast as that of GaAs MSMs and may be related to low carrier mobility. This shortcoming has been reported as the cause for the lower-than-expected efficiency of solar cells fabricated using this quarternary. The effect of growth conditions and thermal processing on detector characteristics such as bandwidth and dark current were investigated. The challenges associated with the use of InGaNAs in photodetectors (such as defects, response speed, requirement for thermal anneal) will be discussed.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".