MétaCan
Menu
Back to cohort
Record W4392234142 · doi:10.1002/adma.202309154

An Integrated Deposition and Passivation Strategy for Controlled Crystallization of 2D/3D Halide Perovskite Films

2024· article· en· W4392234142 on OpenAlexaff
Tim Kodalle, Mahdi Malekshahi Byranvand, Meredith Goudreau, Chittaranjan Das, R. Mathew Roy, Małgorzata Kot, Simon Briesenick, Mohammadreza Zohdi, Monika Rai, Nobumichi Tamura, Jan Ingo Flege, Wolfram Hempel, Carolin M. Sutter‐Fella, Michael Saliba

Bibliographic record

VenueAdvanced Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsMcGill University
FundersLawrence Berkeley National LaboratoryBasic Energy SciencesAgencia Estatal de InvestigaciónEuropean Research CouncilHORIZON EUROPE Framework ProgrammeBundesministerium für Bildung und ForschungCentro para el Desarrollo Tecnológico IndustrialDeutsche ForschungsgemeinschaftOffice of ScienceMaterials Sciences and Engineering DivisionAlbert Ellis InstituteU.S. Department of EnergyBundesministerium für Wirtschaft und EnergieUniversity of California
KeywordsPassivationMaterials scienceCrystallizationHalidePerovskite (structure)Grain sizeAnnealing (glass)Chemical engineeringGrain boundaryPerovskite solar cellThin filmDeposition (geology)Solar cellNanotechnologyLayer (electronics)OptoelectronicsInorganic chemistryMicrostructureComposite material

Abstract

fetched live from OpenAlex

This work introduces a simplified deposition procedure for multidimensional (2D/3D) perovskite thin films, integrating a phenethylammonium chloride (PEACl)-treatment into the antisolvent step when forming the 3D perovskite. This simultaneous deposition and passivation strategy reduces the number of synthesis steps while simultaneously stabilizing the halide perovskite film and improving the photovoltaic performance of resulting solar cell devices to 20.8%. Using a combination of multimodal in situ and additional ex situ characterizations, it is demonstrated that the introduction of PEACl during the perovskite film formation slows down the crystal growth process, which leads to a larger average grain size and narrower grain size distribution, thus reducing carrier recombination at grain boundaries and improving the device's performance and stability. The data suggests that during annealing of the wet film, the PEACl diffuses to the surface of the film, forming hydrophobic (quasi-)2D structures that protect the bulk of the perovskite film from humidity-induced degradation.

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 integrity0.0000.001
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 head0.009
GPT teacher head0.257
Teacher spread0.248 · 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

Citations40
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced MaterialsSame topicPerovskite Materials and ApplicationsFrench-language works237,207