1.5 μm to 0.87 μm optical upconversion using wafer fusion technology
Bibliographic record
Abstract
Wafer fusion is an important processing tool for heterogenous integration of different materials regardless of their lattice constants. It removes the limitation of conventional epitaxial growth techniques and introduces a design parameter for achieving high performance semiconductor devices. In this article, we propose and demonstrate a 1.5 μm to 0.87 μm optical upconversion device based on wafer fusion technology. The device consists of an In0.53Ga0.47As (InGaAs) p-i-n photodetector and an AlGaAs/GaAs light-emitting diode (LED) integrated with wafer fusion. Incoming 1.5 μm light is absorbed by the InGaAs photodetector and generates a photocurrent. The resultant photocurrent drives the GaAs LED, which emits radiation at 0.87 μm. An internal quantum efficiency of 20% and an external quantum efficiency of 0.27% was obtained at room temperature. The results show the potential of the upconversion device in near-infrared imaging applications.
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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) | 0.000 | 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) | 0.001 | 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".