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Record W4402215368 · doi:10.1051/epjap/2024240090

Effect of TiO<sub>2</sub> structure on hysteretic behaviors in CH<sub>3</sub>NH<sub>3</sub>PbI<sub>3</sub> perovskite solar cells

2024· article· en· W4402215368 on OpenAlexaff
William M Elcock, Ali Abdolahzadeh Ziabari, Gap Soo Chang

Bibliographic record

VenueThe European Physical Journal Applied Physics · 2024
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPerovskite (structure)Materials scienceHysteresisEngineering physicsOptoelectronicsCondensed matter physicsCrystallographyChemistryPhysics

Abstract

fetched live from OpenAlex

This work explores a mechanism behind hysteresis in CH 3 NH 3 PbI 3 perovskite solar cells. The solar cells in this work employed either compact TiO 2 , mesoporous TiO 2 , or a combination of compact and mesoporous TiO 2 as an electron transport layer. The solar cells using compact TiO 2 layer displayed the most pronounced hysteresis compared to those which made use of mesoporous TiO 2 . Different hysteretic behavior is attributed to difference in the built-in electric fields present in the architecture of perovskite solar cell. The solar cells with a compact TiO 2 layer have a built-in field which allows for iodide ions to migrate and accumulate near to the interface of indium-tin-oxide electrode, ultimately causing a reduction in the measured power conversion efficiency for forward bias scans. In case of the cells with a mesoporous TiO 2 layer, they have the built-in fields configured in such a way that iodide ions are blocked from migrating on a large scale to the vicinity of the ITO electrode. This results in the reduced hysteresis in perovskite solar cells when a mesoporous TiO 2 electron transport layer is employed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.107
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.203
Teacher spread0.198 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2024
Admission routes1
Has abstractyes

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