Onset of Quantum-Confined Stark Effects in Multijunction Photovoltaic Laser Power Converters Designed with Thin Subcells
Bibliographic record
Abstract
Photovoltaic multijunction power-converting III–V semiconductor devices generate electrical power from the optical energy of laser beams. They exhibit conversion efficiencies reaching values greater than 60% and 50% for the GaAs and the InP material systems, respectively. The applications of optical wireless power transmission and power-over-fiber greatly benefit from employing such laser power converters constructed with multiple subcells; each is designed with either thin GaAs or InGaAs absorber regions. This study elucidates how the application of electric fields on thin heterostructures can create specific current–voltage characteristics due to modifications of the absorption characteristics from Franz–Keldysh perturbations and the onset of quantum-confined Stark effects. Negative differential photocurrent behavior can be observed as the reverse bias voltage is increased, until the corresponding current-clamping subcell reaches its reverse breakdown condition. The reverse voltage breakdown characteristics of the subcells were also measured to depend on the thickness of the subcell and on the optical intensity. The onset of the reverse breakdown was found to be at ~2.0–2.5 V under illumination and the thinner subcells exhibited higher levels of reverse bias currents. These effects can produce distinctive current–voltage behavior under spectrally detuned operations affecting the thinner subcells’ biases, but have no significant impact on the performance and maximum power point of multijunction power converters.
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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 | 0.000 |
| 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".