Electronic states of ultrathin InAs/InP (001) quantum wells: A tight-binding study of the effects of band offset, strain, and intermixing
Bibliographic record
Abstract
We investigate theoretically the electronic structure of strained ultrathin InAs/InP (001) quantum wells (QWs), using the semiempirical ${\mathrm{sp}}^{3}{d}^{5}{s}^{*}$ nearest-neighbors tight-binding model, the virtual crystal approximation, and the surface Green's function matching method. The energies of the bound states and the optical transitions are calculated for QW widths from 1 to 4 monolayers and for valence band offsets varying from 0.2 to 0.9 eV. The dependence of the transition energies on strain is investigated. The intermixing effects are studied for (i) graded interfaces with a diffusion concentration profile and (ii) ${\mathrm{InAs}}_{x}{\mathrm{P}}_{1\ensuremath{-}x}/\mathrm{InP}$ QWs of varying composition with abrupt interfaces. The effect of strain on the transition energies is found to be small for thin wells, whereas the effect of intermixing is significant and cannot be neglected. Comparing the results with experimental data, we conclude that the electronic structure of ultrathin InAs/InP (001) QWs cannot be accurately described within the simple model of a rectangular QW. The effect of intermixing however is sufficient to explain the experimental results within a reasonable range of band offsets and structure parameters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".