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Record W4289133589 · doi:10.1002/anie.202209615

Manipulating Reaction Intermediates to Aqueous‐Phase ZnSe Magic‐Size Clusters and Quantum Dots at Room Temperature

2022· article· en· W4289133589 on OpenAlexaff
Yang Li, Meng Zhang, Li He, N. L. Rowell, Theo Kreouzis, Chunchun Zhang, Shanling Wang, Chaoran Luan, Xiaoqin Chen, Sijie Zhang, Kui Yu

Bibliographic record

VenueAngewandte Chemie International Edition · 2022
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsNational Research Council Canada
FundersScience and Technology Facilities CouncilChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsNucleationQuantum dotAqueous solutionChemistryChemical physicsAbsorption (acoustics)PhotochemistryNanotechnologyMaterials sciencePhysical chemistry

Abstract

fetched live from OpenAlex

It is not resolved which model describes better the aqueous-phase nucleation and growth of semiconductor quantum dots (QDs), the classical one-step one or the nonclassical multi-step one. Here, we design a room-temperature reaction to trap reaction intermediates in the prenucleation stage of ZnSe QDs (as a model system). We show that the trapped intermediate can transform to magic-size clusters (MSCs) via intra-molecular reorganization and can fragment to enable the growth of QDs. The MSCs exhibit a sharp optical absorption peaking at 299 nm, labelled MSC-299. The intermediate, the precursor compound (PC-299) of MSC-299, is optically transparent at 299 nm and to longer wavelengths. This intermediate forms in various Zn and Se reaction systems. The present study provides unambiguous evidence that the nonclassical and classical pathways are both necessary to explain the nucleation and growth of aqueous-phase QDs, with the former pathway favored more by high reaction concentrations.

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 categoriesInsufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.999

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)0.0020.000

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 head0.018
GPT teacher head0.262
Teacher spread0.244 · 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.

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

Citations22
Published2022
Admission routes1
Has abstractyes

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