Modeling of AlInAsSb waveguide avalanche photodiodes for MWIR applications
Bibliographic record
Abstract
Abstract Mid-wave infrared (MWIR) photodetectors are obtaining increased market demand in various application fields such as sensing, spectroscopy, medical diagnostics, and communication systems. The application scope is also being expanded due to the integration ability for these devices into the silicon platforms. Although the MWIR avalanche photodiodes (APDs) have been developed and reported by some laboratories, progresses are still needed on reducing the signal-to-noise ratio, enhancing the quantum efficiency and improving bandwidths etc. These goal-oriented tasks are very challenging especially due to the internal impact ionization mechanism, the structure and material complexity, and the routine design trade-off issues among all the device performances. Therefore, modeling of such MWIR APDs as well as the relevant software package are highly requested to save the development time and cost. In this work, two-dimensional modeling of MWIR AlInAsSb waveguide APD operating at 2 μm is presented. The edge-butt waveguide coupling is investigated based on the beam propagation method. The APD photon-electronic behavior are further simulated based on a drift-diffusion theory. The frequency response and bandwidth are also evaluated. Modeling results of I-V curves, multiplication gain, breakdown voltage, excess noise factor, -3 dB bandwidth and gain-bandwidth product are presented with some comparable to the experimental report from other researchers. The bandwidth results are analysed and discussed further with clues for possible improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".