Strain engineering in III-V photonic components through structuration of SiNx films
Bibliographic record
Abstract
We describe work to quantify the effects of structured dielectric thin films, such as SiNx, at the surface of III-V semiconductors, in terms of strain engineering with applications to photonic components such as waveguides and lasers. We show that the strain in the semiconductor can be engineered by controlling the stress in the dielectric thin film by tuning its deposition process. In the first part of this study, we describe how we can control the amount of this built-in mechanical stress, in the case of SiNx, over a large range, from highly tensile (300 MPa) to highly compressive (−800 MPa), using two different kinds of plasma-enhanced chemical vapor deposition reactors: a standard capacitively coupled reactor with radiofrequency excitation and an electron cyclotron resonance reactor with microwave excitation. We focused on characterizing and understanding these thin films' optical and chemical bonding properties through spectroscopic ellipsometry and Fourier transform infrared spectroscopy. We have also studied their mechanical properties experimentally using the wafer curvature measurement technique, microstructure fabrication, and nanoindentation measurements. In the second part, we show accurate measurements of the strain distribution induced within GaAs wafers when such thin films are structured in the shape of elongated stripes of variable width, using standard optical lithography and plasma etching. For this, we map the anisotropic deformation, measuring the degree of polarization of the spectrally integrated photoluminescence (PL) generated within GaAs by excitation with a red laser. PL from the bulk cubic semiconductors such as GaAs and InP is unpolarized, whereas anisotropic strain produces some degree of polarization. These maps were measured either from the semiconductor surface or from cleaved cross sections. They provide a detailed and complete image of the crystal deformation in the vicinity of the structured stressor film. Finally, we have performed some finite element simulations trying to reproduce the experimental maps. This investigation covering the different steps, including control of the built-in stress within the SiNx thin films, mapping of the anisotropic deformation field generated within the semiconductor beneath the structured films, and numerical simulation of these effects, allows us to propose a set of recipes that can be employed for strain engineering of III-V photonic components. Our simulation scheme is helpful for the design of the photonic components, e.g., to predict the local changes in the refractive index due to the photoelastic effect.
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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".