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Record W2521592849 · doi:10.1116/1.4963071

Abnormal thin film structures in vapor-phase deposited methylammonium lead iodide perovskite

2016· article· en· W2521592849 on OpenAlexaff
Adrian Llanos, Emmanuel S. Thibau, Zheng‐Hong Lu

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2016
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCrystallinityPerovskite (structure)Thin filmMaterials scienceIodideScanning electron microscopeDeposition (geology)Texture (cosmology)Phase (matter)Flux (metallurgy)DiffractionAnalytical Chemistry (journal)Chemical vapor depositionCharacterization (materials science)Chemical engineeringMineralogyCrystallographyOpticsNanotechnologyChemistryInorganic chemistryComposite materialMetallurgyGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

The authors report on the observation of abnormal growth features in methylammonium lead iodide thin films synthesized by vapor-phase deposition with high methylammonium iodide (MAI) flux. The morphological and crystallographic impact of varying flux of MAI is characterized using scanning electron microscopy and x-ray diffractometry. It was found that increasing organic flux results in large, angular, yet hollow nonuniformities growing within the film. Diffraction patterns show good perovskite crystallinity across all samples, but show texture development with the (220) diffraction peak growing in intensity relative to the (004) peak as organic content increases. A possible mechanism for the growth of these features is discussed. These results highlight some potential critical pitfalls for perovskite thin film deposition by coevaporation and emphasize the importance of microscopy-based characterization.

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 score0.002

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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