1.5- to 0.8-μm optical upconversion by wafer fusion
Bibliographic record
Abstract
An InGaAs photodetector array interconnected with a silicon readout IC is the industry standard for 1.2-1.6 μm imaging applications. However, the indium-bump technique it employs for interconnection makes it expensive. An alternative approach is to combine a CCD with a device that upconverts 1.2-1.6 μm radiation to a wavelength below 1 μm. Here we report the realization of a 1.5 μm to 0.87 μm optical upconversion device using wafer fusion technology. The device consists of an InGaAs/InP PIN photodetector and an AlGaAs/GaAs light emitting diode (LED). Incoming 1.5 μm light is absorbed by the InGaAs photodetector. The resulting photocurrent drives the GaAs LED, which emits at 0.87 μm. The PIN and LED structures are epitaxially grown on an InP and a GaAs substrate, respectively. The two wafers are wafer fused together, the GaAs substrate is removed, and the sample is processed using conventional microfabrication technology. In this paper, we first present the design and fabrication process of the device. We then discuss the approaches to increase device efficiency. We show, both experimentally and theoretically, that the active layer doping affects the LED internal quantum efficiency, especially under low current injection. An optimum doping value is obtained. The LED extraction efficiency is increased using several approaches, including micro-lens and surface scattering. Overall device efficiency is further improved by introducing a gain mechanism into the photodetector. Our results show the potentials of this integrated photodetector-LED device for 1.2-1.6 μm imaging applications.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".