Strain analysis of highly scalable single InAs/InP quantum dots in a stress-sensitive environment
Bibliographic record
Abstract
We perform an experimental and computational study of the effects of external stress and intermixing on single site-selected InAs/InP quantum dots in a highly scalable stress-sensitive environment. While such effects are well known for their ability to tune emission spectra, little is known on how they influence emission shell spacing, electron-hole effective mass renormalization, and the physical size of the embedded quantum dot, which are all important parameters affecting the intended functionality. We show excellent agreement between experiment and finite-element solutions of the coupled Navier and Schrödinger equations, including recent atomistic pseudopotential calculations in the literature. These results indicate that using single self-assembled quantum dots in highly scalable, stress-sensitive settings as active elements in future bottom-up nanosystems offers greater versatility to not only quantum information systems where they serve as scalable single-photon sources but also to ultra-sensing capabilities in future nano-electro-mechanical architectures.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".