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Record W1995083125 · doi:10.1039/c4ta02637c

Effect of CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub>thickness on device efficiency in planar heterojunction perovskite solar cells

2014· article· en· W1995083125 on OpenAlexafffund
Dianyi Liu, Mahesh K. Gangishetty, Timothy L. Kelly

Bibliographic record

VenueJournal of Materials Chemistry A · 2014
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of Saskatchewan
KeywordsMaterials sciencePerovskite (structure)HeterojunctionEnergy conversion efficiencyOptoelectronicsPlanarFabricationMesoporous materialLayer (electronics)Perovskite solar cellAbsorption (acoustics)Solar cellNanotechnologyChemical engineeringChemistryComposite materialComputer science

Abstract

fetched live from OpenAlex

Recent advances in the development of perovskite solar cells based on CH3NH3PbI3 have produced devices with power conversion efficiencies of >15%. While initial work in this area assumed that the perovskite-based cells required a mesoporous TiO2 support, many recent reports have instead focused on the development of planar heterojunction structures. A better understanding of how both cell architecture and various design parameters (e.g., perovskite thickness and morphology) affect cell performance is needed. Here, we report the fabrication of perovskite solar cells based on a ZnO nanoparticle electron transport layer, CH3NH3PbI3 light absorber, and poly(3-hexylthiophene) (P3HT) hole transport layer. We show that vapor-phase deposition of the PbI2 precursor film produces devices with performances equivalent to those prepared using entirely solution-based techniques, but with very precise control over the thickness and morphology of the CH3NH3PbI3 layer. Optimization of the layer thickness yielded devices with efficiencies of up to 11.3%. The results further demonstrate that a delicate balance between light absorption and carrier transport is required in these planar heterojunction devices, with the thickest perovskite films producing only very low power conversion efficiencies.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.005
GPT teacher head0.202
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 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

Citations379
Published2014
Admission routes2
Has abstractyes

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Same venueJournal of Materials Chemistry ASame topicPerovskite Materials and ApplicationsFrench-language works237,207