Enhancement of TE polarized light extraction efficiency in nanoscale (AlN)<sub><i>m</i></sub>/(GaN)<sub><i>n</i></sub>(<i>m</i>><i>n</i>) superlattice substitution for Al-rich AlGaN disorder alloy: ultra-thin GaN layer modulation
Bibliographic record
Abstract
The problem of achieving high light extraction efficiency in Al-rich Al _x Ga $_{1-x}$ N is of paramount importance for the realization of AlGaN-based deep ultraviolet (DUV) optoelectronic devices. To solve this problem, we investigate the microscopic mechanism of valence band inversion and light polarization, a crucial factor for enhancing light extraction efficiency, in Al-rich Al _x Ga $_{1-x}$ N alloy using the Heyd–Scuseria–Ernzerhof hybrid functional, local-density approximation with 1/2 occupation, and the Perdew–Burke–Ernzerhof functional, in which the spin–orbit coupling effect is included. We find that the microscopic Ga-atom distribution can effectively modulate the valence band structure of Al-rich Al _x Ga $_{1-x}$ N. Moreover, we prove that the valence band arrangement in the decreasing order of heavy hole, light hole, and crystal-field split-off hole can be realized by using nanoscale (AlN) _m /(GaN) _n ( m > n ) superlattice (SL) substituting for Al-rich Al _x Ga $_{1-x}$ N disorder alloy as the active layer of optoelectronic devices due to the ultra-thin GaN layer modulation. The valence band maximum, i.e., the heavy hole band, has p _x - and p _y -like characteristics and is highly localized in the SL structure, which leads to the desired transverse electric (TE) polarized ( E ⊥ c ) light emission with improved light extraction efficiency in the DUV spectral region. Some important band-structure parameters and electron/hole effective masses are also given. The physical origin for the valence band inversion and TE polarization in (AlN) _m /(GaN) _n SL is analyzed in depth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".