PERC+: industrial PERC solar cells with rear Al grid enabling bifaciality and reduced Al paste consumption
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Passivated emitter and rear cell (PERC) solar cells are currently being introduced into mass production. In this paper, we report a novel PERC solar cell design that applies a screen‐printed rear Al finger grid instead of the conventional full‐area aluminum (Al) rear layer while using the same PERC manufacturing sequence. We name this novel cell concept PERC+ because it offers several advantages. In particular, the Al paste consumption of the PERC+ cells is drastically reduced to 0.15 g instead of 1.6 g for the conventional PERC cells. The Al fingers create 2‐µm‐deeper aluminum back surface fields, which increases the open‐circuit voltage by 4 mV. The five‐busbar Al finger grid enables bifacial applications of the PERC+ cells with front‐side efficiencies up to 20.8% and rear‐side efficiencies up to 16.5% measured with a black chuck. The corresponding bifaciality is 79%. When applied in monofacial modules where the white back sheet acts as external rear reflector, the efficiency of the PERC+ cells is estimated to 20.9%, which is comparable with conventional PERC cells. Whereas Institute for Solar Energy Research Hamelin developed the aforementioned PERC+ results, SolarWorld independently pioneered a very similar bifacial PERC+ cell process starting in 2014. Transfer into mass production has been successfully accomplished, and novel glass–glass bifacial PERC+ modules have been launched at the Intersolar 2015 based on a most simple, lean, and cost‐effective bifacial cell process. These new bifacial PERC+ modules show an increase in annual energy yield between 5% and 25% in simulations, which is confirmed by first outdoor measurements. Copyright © 2015 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it