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Record W2896025115 · doi:10.1109/jphotov.2018.2873307

ITO-Free Silicon Heterojunction Solar Cells With ZnO:Al/SiO<sub>2</sub> Front Electrodes Reaching a Conversion Efficiency of 23%

2018· article· en· W2896025115 on OpenAlexfundno aff
Anna Belen Morales‐Vilches, Alexandros Cruz, S. Pingel, Sebastian Neubert, Luana Mazzarella, Daniel Meza, Lars Korte, Rutger Schlatmann, Bernd Stannowski

Bibliographic record

VenueIEEE Journal of Photovoltaics · 2018
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
FundersInstitute of Gender and Health
KeywordsIndium tin oxideMaterials scienceAnti-reflective coatingAmorphous siliconSiliconPhotovoltaic systemOptoelectronicsCrystalline siliconCoatingNanotechnologyElectrical engineeringLayer (electronics)

Abstract

fetched live from OpenAlex

Silicon heterojunction (SHJ) solar cells have been increasingly attracting attention to the photovoltaic community in the last years due to their high efficiency potential and the lean production process. We report on the development of a stable baseline process for SHJ cells with focus on the optical improvement of the solar cells' front side. An amorphous silicon oxide layer (a-SiO2) was used as an antireflective coating (AR) on the front side the finished SHJ devices. Both optical simulations and experimental results demonstrate a short-circuit current density (Jsc) improvement of 0.4 mA/cm2when applying the a-SiO2AR, yielding maximum conversion efficiencies of 23.0%. Full-size cells with 244 cm2total area have been produced using three front contact stacks: indium tin oxide (ITO) as reference, ZnO:Al, and ZnO:Al/SiO2showing the Jsc improvement with the double AR configuration. Damp-heat tests on those samples demonstrate an enhanced stability of cells with ZnO:Al front TCO when capped with SiO2.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.193
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), 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

Citations80
Published2018
Admission routes1
Has abstractyes

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