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Record W4382182420 · doi:10.1021/acs.jpclett.3c01156

Sterically Suppressed Phase Segregation in 3D Hollow Mixed-Halide Wide Band Gap Perovskites

2023· article· en· W4382182420 on OpenAlexafffund
Luke Grater, Mingcong Wang, Sam Teale, Suhas Mahesh, Aidan Maxwell, Yanjiang Liu, So Min Park, Bin Chen, Frédéric Laquai, Mercouri G. Kanatzidis, Edward H. Sargent

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Toronto
FundersOffice of Naval ResearchU.S. NavyOffice of ScienceUniversity of TorontoU.S. Department of Energy
KeywordsHalidePerovskite (structure)Band gapPassivationIodideMaterials scienceTrihalidePhotoluminescenceBromideIonPhase (matter)OptoelectronicsChemical physicsInorganic chemistryChemistryCrystallographyNanotechnology

Abstract

fetched live from OpenAlex

Band gap tuning in mixed-halide perovskites enables efficient multijunction solar cells and LEDs. However, these wide band gap perovskites, which contain a mixture of iodide and bromide ions, are known to phase segregate under illumination, introducing voltage losses that limit stability. Previous studies have employed inorganic perovskites, halide alloys, and grain/interface passivation to minimize halide segregation, yet photostability can be further advanced. By focusing on the role of halide vacancies in anion migration, one expects to be able to erect local barriers to ion migration. To achieve this, we employ a 3D "hollow" perovskite structure, wherein a molecule that is otherwise too large for the perovskite lattice is incorporated. The amount of hollowing agent, ethane-1,2-diammonium dihydroiodide (EDA), varies the density of the hollow sites. Photoluminescence measurements reveal that 1% EDA in the perovskite bulk can stabilize a 40% bromine mixed-halide perovskite at 1 sun illumination intensity. These, along with capacitance-frequency measurements, suggest that hollow sites limit the mobility of the halide vacancies.

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 score0.013
Threshold uncertainty score0.406

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 head0.011
GPT teacher head0.241
Teacher spread0.229 · 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

Citations18
Published2023
Admission routes2
Has abstractyes

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