Ion-implanted PERC Solar Cells with Al2O3/SiNx Rear Passivation
Bibliographic record
Abstract
Ion implantation is an attractive candidate for PERC solar cells due to the single-sided emitter phosphorus doping. The oxide, which is formed during the implant anneal, can be used as rear passivation of PERC cells. However, the SiO 2 /SiN x rear passivation is very sensitive to the rear surface roughness and surface preparation. Hence, in this paper we evaluate Al 2 O 3 /SiN x rear passivation layers in combination with an oxide passivated ion-implanted emitter. We obtain emitter saturation current densities of 93 fA/cm 2 , which is significantly lower compared to a typical POCl 3 diffused emitter with 140 fA/cm 2 . Ion-implanted PERC cells with Al 2 O 3 /SiN x rear passivation show conversion efficiencies up to 20.0% which is comparable to POCl 3 -diffused PERC cells. The emitter dopant profile can be adjusted by the thermal budget of the anneal in order to optimize the process window between J sc and FF losses. The IQE and reflectance of implanted and POCl 3 -diffused PERC cells in the long wavelength regime are almost identical which demonstrates the successful implementation of the Al 2 O 3 /SiN x rear passivation to PERC cells with ion-implanted emitters. Future work will focus on simplifying the process flow in order to obtain a lean industrially manufacturable PERC process, leveraging the single side doping via ion implantation.
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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 | 0.001 |
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".