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Record W4399171212 · doi:10.1021/acs.chemmater.4c01006

Two-Dimensional Lead Halide Perovskites with Spirocyclic Intercalating Cations

2024· article· en· W4399171212 on OpenAlexafffund
Liang Zhao, Yilan Zhang, Huai Chen, Tao Zeng, Zhenyu Yang

Bibliographic record

VenueChemistry of Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsYork University
FundersSun Yat-sen UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaYork University
KeywordsHalideIntercalation (chemistry)Lead (geology)Materials scienceInorganic chemistryPerovskite (structure)ChemistryCrystallographyGeology

Abstract

fetched live from OpenAlex

Two-dimensional metal halide perovskites (TMHPs) are distinguished by their component-dependent material properties, and outstanding photophysical properties, positioning them as promising candidates for optoelectronic devices. Although numerous A-site cations have been integrated into TMHP scaffolds, only a few incorporate complex three-dimensional organic frameworks. Here we report the synthesis of five new TMHP single crystals incorporated with spirocyclic (SC) intercalating cations via a two-step synthetic approach. This method involves the formation of a thiazolidine-derived framework via condensation of zwitterionic ligands and cyclic ketones. Strong hydrogen bonding interactions between the ammonium termini of the SC ligands and the inorganic layers are observed in all the new TMHPs, drawing the SC cations closer to the [PbI 6 ] 4– octahedra and stretching the heterocyclic scaffolds. Computational analyses reveal that the sulfur-containing SC ligands may significantly enhance the charge carrier mobility. These results demonstrate the potential of three-dimensional intercalating cation synthesis for the development of new perovskite-derived structures.

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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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