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Record W4211239036 · doi:10.1002/smll.202107548

Ultra‐Stable CsPbX<sub>3</sub>@Pyrophosphate Nanoparticles in Water over One Year

2022· article· en· W4211239036 on OpenAlexaff
Qixuan Zhong, Xuchun Wang, Mingyu Chu, Yinghua Qiu, Di Yang, Tsun‐Kong Sham, Jinxing Chen, Lu Wang, Muhan Cao, Qiao Zhang

Bibliographic record

VenueSmall · 2022
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsWestern University
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsPyrophosphateMaterials scienceHalidePerovskite (structure)IrradiationNanocrystalThermal stabilityNanoparticleChemical engineeringNanotechnologyChemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract All‐inorganic lead halide perovskite (CsPb X 3 , X = Cl, Br, I, or their mixture) nanocrystals (NCs) have achieved inspiring advancements in optoelectronic fields but still suffer from poor durability when exposed to environmental stimuli such as water, irradiation and heat. Herein, a strategy of employing pyrophosphate as the inert shell for CsPbX 3 NCs is reported. The strong binding between pyrophosphate and CsPbBr 3 surface can stabilize the perovskite structure well. The as‐obtained core@shell CsPbBr 3 @NH 4 AlP 2 O 7 NCs exhibit impressive stability against water and maintain the initial optical properties with negligible change in 400 days. Furthermore, significant improvement of irradiation/thermal resistance is realized due to the protecting role of pyrophosphate. The NCs can retain 100% and ≈90% of the original PL after hundreds of heating/cooling cycles and several hundred hours of UV light irradiation, respectively. As a result, the core@shell products can be directly used for high‐resolution inkjet printing, enabling the printed fluorescent information to be resistant under harsh environmental conditions. This work provides a promising way for the synthesis of highly stable encapsulated perovskite NCs and demonstrates a great potential in practical applications.

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 score0.015
Threshold uncertainty score0.576

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)0.0010.000

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 head0.010
GPT teacher head0.175
Teacher spread0.165 · 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

Citations31
Published2022
Admission routes1
Has abstractyes

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