First-order <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi mathvariant="normal">k</mml:mi> <mml:mo>·</mml:mo> <mml:mi mathvariant="normal">p</mml:mi> </mml:mrow> </mml:math> methods for electron intersubband scatterings in quantum wells
Bibliographic record
Abstract
Using a first-order $\mathbf{k}\ifmmode\cdot\else\textperiodcentered\fi{}\mathbf{p}$ Kane model, this work studies the impact of band-mixing, which gives rise to nonparabolicity, on electron intersubband scattering in zinc-blende semiconductor quantum well structures. The eight-band model considers both spin-flip and spin-conserving processes as well as a nonparabolic subband dispersion. We examine the effects of considering multiple band components in the total eigenstate, as well as their k-dependent properties, on LO phonon, impurity, and interface roughness (IFR) scattering. These k-dependent eigenstates account for the effects of varying wave function composition, spatial confinement and Rashba spin-orbit coupling. The angular dependencies of spin-conserving and spin-flip transitions are analyzed in the case of LO phonon emission scattering, and the heavy-hole interaction is shown to have a strong influence. The total (spin-conserving plus spin-flip) scattering is more concentrated in the forward direction than in the standard three-band $\mathbf{k}\ifmmode\cdot\else\textperiodcentered\fi{}\mathbf{p}$ model. Furthermore, the neutrality of the scattering processes versus the spin-type of the initial state is discussed and is directly linked to the structural inversion asymmetry. The overall scattering rate is notably reduced when band-mixing is included within the framework of a first-order Kane model in comparison to a standard one-band $\mathbf{k}\ifmmode\cdot\else\textperiodcentered\fi{}\mathbf{p}$ model. As an example, the total 2-to-1 LO phonon scattering decreases by up to $\ensuremath{\sim}60%$ in narrow InAs/AlAsSb quantum wells (${\ensuremath{\lambda}}_{21}\ensuremath{\sim}2.7\phantom{\rule{4pt}{0ex}}\textmu{}\mathrm{m}$). Similarly significant reductions are also reported for IFR scattering. Interestingly, this slowing effect persists even for long wavelengths. Our results collectively emphasize the importance of band-mixing when modeling intersubband devices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".