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Record W2067103027 · doi:10.1016/j.egypro.2013.07.291

Influence of Solder Pads to PERC Solar Cells for Module Integration

2013· article· en· W2067103027 on OpenAlexfundno aff
Fabian Kiefer, Till Brendemühl, M. N. Berger, Anja Lohse, Sabine Kirstein, Nadja Braun, Martin Lehr, Frank Heinemeyer, Verena Jung, Arnaud Morlier, Susanne Blankemeyer, I. Kunze, Renate Winter, Nils‐Peter Harder, Thorsten Dullweber, Marc Köntges, Rolf Brendel

Bibliographic record

VenueEnergy Procedia · 2013
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
FundersInstitute of Gender and Health
KeywordsPassivationMaterials scienceSolderingSolar cellScreen printingOptoelectronicsCommon emitterOpen-circuit voltageCrystalline siliconLayer (electronics)Composite materialVoltageElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

The majority of screen printed solar cells has silver pads at the rear side to enable soldering for the module manufacturing. The pads increase the recombination at the silicon/metal interface due to the absence of a back surface field (BSF) at the solder pads. This reduces the efficiency of full-area Al-BSF solar cells. For passivated emitter and rear cells (PERC), a large area fraction of the rear side is covered with the passivation layer. When using specially designed Ag pastes for the rear side of PERC cells, the passivation of this layer is maintained, and the rear recombination is reduced. A comparison of solar cells with and without solder pads confirms that there is no loss in solar cell performance, both cell types achieve an efficiency of 19.6%. We investigate the influence of solder pads to PERC solar cells by calculating the effective rear surface recombination. The calculations confirm that there is a loss in open circuit voltage of less than 2 mV due to the solder pads. A 54-cell PERC PV module is manufactured. The cell-to-module loss reveals that the module process is still to be optimized. Comparable modules made from 9 solar cells lost less than 1% relative in all J-V parameters after a 1000 h damp-heat test.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.186
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2013
Admission routes1
Has abstractyes

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