Development of compact micro-CPV modules using advanced packaging technologies based on high-performance solar cells
Bibliographic record
Abstract
olar energy offers a sustainable solution to current energy and environmental challenges. III-V multi-junctions solar cells represent the photovoltaic technology with the highest effciencies among all solar technologies. Unfortunately, these cells are expensive. To reduce the cost of this technology, a concentrating optic can be placed above the cells, thereby reducing the amount of III-V materials needed. This strategy, known as concentrator photovoltaics (CPV), also increases the conversion efficiency of solar cells. However, CPV faces limitations such as resistive and thermal losses, as well as a lack of compactness, preventing its large-scale deployment. In response to these limitations, the miniaturization of CPV, referred to as micro-CPV, has been developing over the past several years. Reducing the cell size to below one millimeter decreases resistive losses, simplifes thermal management, and increases module compactness. To fully leverage the advantages of this technology, challenges related to micro-fabrication, packaging, and optics must be addressed. This thesis explores these three felds with the following goal : to fabricate a compact microCPV module with lightweight concentrating optics, using high-performance micro-solar cells while minimizing III-V material losses. The reduction in cell size increases the impact of perimeter recombinations, which decreases the open-circuit voltage (Voc) and thus the conversion efficiency. Sub-millimeter cells with low sensitivity to perimeter recombinations and Voc values exceeding those reported in the literature (to our knowledge) have been fabricated. A loss assessment related to non-radiative recombinations for each of the sub-cells (InGaP/InGaAs/Ge) was also conducted. This assessment demonstrated that the InGaP sub-cell is the most afected by perimeter recombinations. Reducing cell size also presents packaging challenges. Wire bonding, traditionally used for CPV, requires large busbars, generating signifcant shading losses for sub-millimeter cells. A new cell connection method has been developed to minimize shading losses. Throughout this thesis work, a lightweight and compact optic has been designed, fabricated, and characterized. This optic was used to create a prototype of a single module approximately 2 cm thick. Outdoor characterizations of this prototype have shown that integration losses in the module are less than 20%.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".