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Record W4387054654 · doi:10.26434/chemrxiv-2023-k8zns

Long Live(d) CsPbBr3 Superlattices: Colloidal Atomic Layer Deposition for Structural Stability

2023· preprint· en· W4387054654 on OpenAlexafffund
Victoria Lapointe, Philippe B. Green, Alexander N. Chen, Raffaella Buonsanti, Marek B. Majewski

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsConcordia University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCentre québécois sur les matériaux fonctionnels
KeywordsSuperlatticePhotoluminescenceNanocrystalMaterials sciencePerovskite (structure)Atomic layer depositionOxideHalideDeposition (geology)Chemical engineeringEvaporationNanotechnologyLayer (electronics)Inorganic chemistryChemistryCrystallographyMetallurgyOptoelectronics

Abstract

fetched live from OpenAlex

Metal halide perovskite nanocrystals self-assemble under slow solvent evaporation leading to formation of superlattices that are interesting because of their collective photophysical properties, such as superfluorescence. These collective properties are, ostensibly, directly influenced by the stability of the perovskite nanocrystals and their dynamic surface chemistry, both factors that dictate the stability of the superlattice. In this work, we report on the formation of superlattices from aluminum oxide shelled CsPbBr3 perovskite nanocrystals where the oxide shell is grown by colloidal atomic layer deposition. We demonstrate that the structural stability of these superlattices is preserved over 25 days and that colloidal atomic layer deposition yields structural protection and an enhancement in photoluminescence quantum yields and radiative lifetimes as opposed to gas phase atomic layer deposition or excess capping group addition. Structural analyses found that shelling resulted in smaller nanocrystals that pack more tightly within the superlattice forming uniform supercrystals due to the aluminum oxide layers that cause increasingly hard cube behavior leading to a higher packing density than superlattices assembled from softer cubes without aluminum oxide. These effects are in addition to the increasingly static capping group chemistry initiated when oleic acid is used to terminate atomic layer deposition and is subsequently installed as a capping ligand directly on aluminum oxide. Together, these factors lead to fundamental observations that may influence future superlattice assembly design.

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 score0.005

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 head0.044
GPT teacher head0.269
Teacher spread0.226 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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