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Record W4387570858 · doi:10.3390/nano13202750

Polymer Backbone Stabilized Methylammonium Lead Bromide Perovskite Nano Islands

2023· article· en· W4387570858 on OpenAlexaff
Chinna Bathula, Soniya Naik, Atanu Jana, Ramasubba Reddy Palem, Aditya Narayan Singh, Mohammad Rafe Hatshan, Suresh D. Mane, Hyun‐Seok Kim

Bibliographic record

VenueNanomaterials · 2023
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Alberta
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaDongguk UniversityKing Saud UniversityNational Research Foundation
KeywordsPerovskite (structure)Materials scienceX-ray photoelectron spectroscopyPhotoluminescencePolymerSpectroscopyNano-Chemical engineeringScanning electron microscopeHybrid materialAbsorption (acoustics)Field emission microscopyNanotechnologyOptoelectronicsDiffractionOpticsComposite material

Abstract

fetched live from OpenAlex

Organic-inorganic hybrid perovskite materials continue to attract significant interest due to their optoelectronic application. However, the degradation phenomenon associated with hybrid structures remains a challenging aspect of commercialization. To overcome the stability issue, we have assembled the methylammonium lead bromide nano islands (MNIs) on the backbone of poly-3-dodecyl-thiophene (PDT) for the first time. The structural and morphological properties of the MNI-PDT composite were confirmed with the aid of X-ray diffraction (XRD) studies, Field emission scanning electron microscope (FESEM), and X-ray photoelectron spectroscopy (XPS). The optical properties, namely absorption studies, were carried out by ultraviolet-visible spectroscopy. The fluorescent behavior is determined by photoluminescence (PL) spectroscopy. The emission peak for the MNI-PDT was observed at 536 nm. The morphology studies supported by FESEM indicated that the nano islands are completely covered on the surface of the polymer backbone, making the hybrid (MNI-PDT) stable under environmental conditions for three months. The interfacial interaction strategy developed in the present work will provide a new approach for the stabilization of hybrids for a longer time duration.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.003

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 head0.015
GPT teacher head0.237
Teacher spread0.222 · 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; both teacher heads agree on what is shown here.

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 routes1
Has abstractyes

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