InGaN Quantum Dot Superlattices as Ratchet Band Solar Cells
Bibliographic record
Abstract
In this article, we investigate the construction of ratchet band solar cells using InGaN quantum dots. The strong piezoelectric potentials can spatially separate electron and hole states. This spatial separation reduces both radiative and nonradiative recombination within the quantum dot, providing one of the key characteristics of a ratchet band system. Ratchet band solar cells have proven difficult to realize experimentally, and the piezoelectric potential in InGaN quantum dots could provide a spatial ratchet that can operate at room temperature with broadband absorption. We use a$\mathbf {k}{\cdot }\mathbf {p}$model to calculate the electronic structure and absorptance of a superlattice of InGaN/GaN quantum dots. We present an improved method to calculate the absorptance for the bound-to-continuum transition by using bulk$\mathbf {k}{\cdot }\mathbf {p}$states to approximate the host material continuum states. We show an example dot structure that could act as a ratchet band solar cell. Using the absorptances of the quantum dot array, we calculate a detailed balance efficiency of 36% for the system. Optimizing the dot geometry and alloy fraction allows detailed balance efficiencies up to 42% but at the cost of losing the spatial ratchet.
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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 | 0.001 |
| 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".