GaAs/AlGaAs p-type multiple quantum wells for infrared detection at normal incidence: model and experiment
Bibliographic record
Abstract
The development of devices for mid-, long-, and very long- wavelength IR detection has benefitted greatly from advances in band-gap engineering. Recently, there has been great progress in the development of n-type GaAs/AlGaAs quantum well infrared photoconductor (QWIP) detector arrays in all three technologically important wavelength windows. P-type GaAs.AlGaAs QWIPS represent a viable alternative to n-type GaAs/AlGaAs QWIPs, offering the advantage of normal incidence absorption without the need for grating couplers. The maturity of the MBE of GaAs/AlGaAs layered materials offers the possibility of mass producing low cost, high performance, large size, high uniformity, multicolor, high frequency bandwidth, two-dimensional imaging QWIP arrays. This paper describes progress in optimizing the performance of p- type GaAs/AlGaAs QWIPs through modeling, growth, and characterization. Using the 8x8 envelope-function approximation (EFA), a number of structures were designed and their optical absorption calculated for comparison with experiment. Samples were grown by MBE based on the theoretical designs and their photoresponse measured. P-type QWIPs were optimized with respect to the well and barrier widths, alloy concentration, and dopant concentration; resonant cavity devices were also fabricated and temperature dependent photoresponse was measured. The quantum efficiencies and the background-limited (BLIP) detectivities under BLIP conditions of our own p-QWIPs are comparable to those of n-QWIPs; however, the responsivities are smaller. For our mid-IR p-QWIPs, the 2D doping densities of 1- 2x1012 cm-2 maximized the BLIP temperature and dark current limited detectivity by operating at around 100K. At 80K, the detectivity of the optimum doped sample was (formula available in paper)at 10V bias. Barrier widths greater than 200 A were sufficient to impede the tunneling dark current; resonant cavities enhanced absorption five-fold.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".