MétaCan
Menu
Back to cohort
Record W3080526340 · doi:10.3390/nano10091676

Low-Temperature Processed TiOx Electron Transport Layer for Efficient Planar Perovskite Solar Cells

2020· article· en· W3080526340 on OpenAlexaff
Md. Shahiduzzaman, Daiki Kuwahara, Masahiro Nakano, Makoto Karakawa, Kohshin Takahashi, Jean‐Michel Nunzi, Tetsuya Taima

Bibliographic record

VenueNanomaterials · 2020
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials sciencePerovskite (structure)FabricationEnergy conversion efficiencyLayer (electronics)SinteringOptoelectronicsPlanarPhotovoltaic systemChemical engineeringTitaniumOxideTitanium dioxideActive layerNanotechnologyComposite materialMetallurgy

Abstract

fetched live from OpenAlex

The most frequently used n-type electron transport layer (ETL) in high-efficiency perovskite solar cells (PSCs) is based on titanium oxide (TiO2) films, involving a high-temperature sintering (>450 °C) process. In this work, a dense, uniform, and pinhole-free compact titanium dioxide (TiOx) film was prepared via a facile chemical bath deposition process at a low temperature (80 °C), and was applied as a high-quality ETL for efficient planar PSCs. We tested and compared as-deposited substrates sintered at low temperatures (< 150 °C) and high temperatures (> 450 °C), as well as their corresponding photovoltaic properties. PSCs with a high-temperature treated TiO2 compact layer (CL) exhibited power conversion efficiencies (PCEs) as high as 15.50%, which was close to those of PSCs with low-temperature treated TiOx (14.51%). This indicates that low-temperature treated TiOx can be a potential ETL candidate for planar PSCs. In summary, this work reports on the fabrication of low-temperature processed PSCs, and can be of interest for the design and fabrication of future low-cost and flexible solar modules.

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 score0.025
Threshold uncertainty score0.975

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 head0.008
GPT teacher head0.206
Teacher spread0.197 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNanomaterialsSame topicPerovskite Materials and ApplicationsFrench-language works237,207